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harivansh-afk 84e1f534df
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"import numpy as np\n",
"import pandas as pd\n",
"import sklearn\n",
"import matplotlib.pyplot as plt\n",
"import sys\n",
"import seaborn as sns\n",
"\n",
"\n",
"import warnings\n",
"warnings.filterwarnings('ignore')\n",
"\n",
"%matplotlib inline\n",
"import plotly.graph_objs as go\n",
"#import plotly.plotly as py\n",
"import datetime as dt\n",
"import matplotlib.dates as mdates\n",
"\n",
"from keras.models import Sequential\n",
"from keras.layers import Dense, LSTM, Dropout, GRU\n",
"from keras.layers import *\n",
"from sklearn.preprocessing import MinMaxScaler\n",
"from sklearn.metrics import mean_squared_error, mean_absolute_error\n",
"from sklearn.model_selection import train_test_split\n",
"from keras.callbacks import EarlyStopping\n",
"from tensorflow.keras.optimizers import Adam, SGD"
]
},
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"text": [
"Saving crypto-markets.csv to crypto-markets.csv\n"
]
}
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"source": [
"from google.colab import files\n",
"uploaded = files.upload()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"id": "PLXtatQdIKkr"
},
"outputs": [],
"source": [
"import io\n",
"df = pd.read_csv(io.StringIO(uploaded['crypto-markets.csv'].decode('utf-8')))"
]
},
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" slug symbol name date ranknow open high low \\\n",
"0 bitcoin BTC Bitcoin 2013-04-28 1 135.30 135.98 132.10 \n",
"1 bitcoin BTC Bitcoin 2013-04-29 1 134.44 147.49 134.00 \n",
"2 bitcoin BTC Bitcoin 2013-04-30 1 144.00 146.93 134.05 \n",
"3 bitcoin BTC Bitcoin 2013-05-01 1 139.00 139.89 107.72 \n",
"4 bitcoin BTC Bitcoin 2013-05-02 1 116.38 125.60 92.28 \n",
"\n",
" close volume market close_ratio spread \n",
"0 134.21 0.0 1.488567e+09 0.5438 3.88 \n",
"1 144.54 0.0 1.603769e+09 0.7813 13.49 \n",
"2 139.00 0.0 1.542813e+09 0.3843 12.88 \n",
"3 116.99 0.0 1.298955e+09 0.2882 32.17 \n",
"4 105.21 0.0 1.168517e+09 0.3881 33.32 "
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" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
" })();\n",
" </script>\n",
"</div>\n",
"\n",
" </div>\n",
" </div>\n"
],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "df"
}
},
"metadata": {},
"execution_count": 6
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "TDuDU-SlIW8s",
"outputId": "0fee239b-aacf-42a8-bb6d-5cce33d1f1b5"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(942297, 13)"
]
},
"metadata": {},
"execution_count": 7
}
],
"source": [
"df.shape #total number of rows and columns"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 492
},
"id": "rSQy0La6Iaez",
"outputId": "072a4a90-209d-4c66-a8cd-da93c9f36469"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"slug 0\n",
"symbol 0\n",
"name 0\n",
"date 0\n",
"ranknow 0\n",
"open 0\n",
"high 0\n",
"low 0\n",
"close 0\n",
"volume 0\n",
"market 0\n",
"close_ratio 0\n",
"spread 0\n",
"dtype: int64"
],
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"source": [
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},
{
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{
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"text/plain": [
" ranknow open high low close \\\n",
"count 942297.000000 9.422970e+05 9.422970e+05 9.422970e+05 9.422970e+05 \n",
"mean 1000.170608 3.483522e+02 4.085930e+02 2.962526e+02 3.461018e+02 \n",
"std 587.575283 1.318436e+04 1.616386e+04 1.092931e+04 1.309822e+04 \n",
"min 1.000000 2.500000e-09 3.200000e-09 2.500000e-10 2.000000e-10 \n",
"25% 465.000000 2.321000e-03 2.628000e-03 2.044000e-03 2.314000e-03 \n",
"50% 1072.000000 2.398300e-02 2.680200e-02 2.143700e-02 2.389200e-02 \n",
"75% 1484.000000 2.268600e-01 2.508940e-01 2.043910e-01 2.259340e-01 \n",
"max 2072.000000 2.298390e+06 2.926100e+06 2.030590e+06 2.300740e+06 \n",
"\n",
" volume market close_ratio spread \n",
"count 9.422970e+05 9.422970e+05 942297.000000 9.422970e+05 \n",
"mean 8.720383e+06 1.725060e+08 0.459499 1.123400e+02 \n",
"std 1.839802e+08 3.575590e+09 0.326160 6.783713e+03 \n",
"min 0.000000e+00 0.000000e+00 -1.000000 0.000000e+00 \n",
"25% 1.750000e+02 2.958100e+04 0.162900 0.000000e+00 \n",
"50% 4.278000e+03 5.227960e+05 0.432400 0.000000e+00 \n",
"75% 1.190900e+05 6.874647e+06 0.745800 3.000000e-02 \n",
"max 2.384090e+10 3.265025e+11 1.000000 1.770563e+06 "
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" <td>3.483522e+02</td>\n",
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" <td>2.962526e+02</td>\n",
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" <td>2.500000e-10</td>\n",
" <td>2.000000e-10</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>-1.000000</td>\n",
" <td>0.000000e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>465.000000</td>\n",
" <td>2.321000e-03</td>\n",
" <td>2.628000e-03</td>\n",
" <td>2.044000e-03</td>\n",
" <td>2.314000e-03</td>\n",
" <td>1.750000e+02</td>\n",
" <td>2.958100e+04</td>\n",
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" <td>2.143700e-02</td>\n",
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" <td>4.278000e+03</td>\n",
" <td>5.227960e+05</td>\n",
" <td>0.432400</td>\n",
" <td>0.000000e+00</td>\n",
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" <td>2.268600e-01</td>\n",
" <td>2.508940e-01</td>\n",
" <td>2.043910e-01</td>\n",
" <td>2.259340e-01</td>\n",
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" <td>2.030590e+06</td>\n",
" <td>2.300740e+06</td>\n",
" <td>2.384090e+10</td>\n",
" <td>3.265025e+11</td>\n",
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"summary": "{\n \"name\": \"df\",\n \"rows\": 8,\n \"fields\": [\n {\n \"column\": \"ranknow\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 332815.4272106603,\n \"min\": 1.0,\n \"max\": 942297.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 1000.1706075685267,\n 1072.0,\n 942297.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"open\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 832118.7012457661,\n \"min\": 2.5e-09,\n \"max\": 2298390.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 348.3521989396375,\n 0.023983,\n 942297.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1039479.4408537038,\n \"min\": 3.2e-09,\n \"max\": 2926100.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 408.5929736812929,\n 0.026802,\n 942297.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 746249.93670663,\n \"min\": 2.5e-10,\n \"max\": 2030590.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 296.2526395650847,\n 0.021437,\n 942297.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"close\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 832887.9048562968,\n \"min\": 2e-10,\n \"max\": 2300740.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 346.1017511531896,\n 0.023892,\n 942297.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 8419486337.196726,\n \"min\": 0.0,\n \"max\": 23840899072.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 8720383.287837062,\n 4278.0,\n 942297.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"market\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 115253023461.45963,\n \"min\": 0.0,\n \"max\": 326502485530.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 172505976.1653693,\n 522796.0,\n 942297.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"close_ratio\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 333152.19187879324,\n \"min\": -1.0,\n \"max\": 942297.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 0.45949948201044916,\n 0.4324,\n 942297.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"spread\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 665284.9937926787,\n \"min\": 0.0,\n \"max\": 1770563.0,\n \"num_unique_values\": 6,\n \"samples\": [\n 942297.0,\n 112.33997064619756,\n 1770563.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 9
}
],
"source": [
"df.describe() #statistical readings of all the columns"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "t2R1q-FAIejT",
"outputId": "ca376529-8f0b-46e8-b370-33014b74a9b0"
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"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 942297 entries, 0 to 942296\n",
"Data columns (total 13 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 slug 942297 non-null object \n",
" 1 symbol 942297 non-null object \n",
" 2 name 942297 non-null object \n",
" 3 date 942297 non-null object \n",
" 4 ranknow 942297 non-null int64 \n",
" 5 open 942297 non-null float64\n",
" 6 high 942297 non-null float64\n",
" 7 low 942297 non-null float64\n",
" 8 close 942297 non-null float64\n",
" 9 volume 942297 non-null float64\n",
" 10 market 942297 non-null float64\n",
" 11 close_ratio 942297 non-null float64\n",
" 12 spread 942297 non-null float64\n",
"dtypes: float64(8), int64(1), object(4)\n",
"memory usage: 93.5+ MB\n"
]
}
],
"source": [
"df.info() #info on all the columns"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"id": "xdF9qRVBM82y"
},
"outputs": [],
"source": [
"data = df #copy of dataframe\n",
"\n",
"#set up a column with an index so I can only sample 1/10th of the dataset\n",
"data[\"row_id\"]= range(1, len(data) + 1)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
},
"id": "kEwAdAFzNGfa",
"outputId": "f89b0798-7a28-4fbd-fee4-c8e10b88cb8b"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" symbol name date open high low close close_ratio \\\n",
"0 BTC Bitcoin 2013-04-28 135.30 135.98 132.10 134.21 0.5438 \n",
"1 BTC Bitcoin 2013-04-29 134.44 147.49 134.00 144.54 0.7813 \n",
"2 BTC Bitcoin 2013-04-30 144.00 146.93 134.05 139.00 0.3843 \n",
"3 BTC Bitcoin 2013-05-01 139.00 139.89 107.72 116.99 0.2882 \n",
"4 BTC Bitcoin 2013-05-02 116.38 125.60 92.28 105.21 0.3881 \n",
"\n",
" spread row_id \n",
"0 3.88 1 \n",
"1 13.49 2 \n",
"2 12.88 3 \n",
"3 32.17 4 \n",
"4 33.32 5 "
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"metadata": {},
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}
],
"source": [
"#drop columns I'm not using\n",
"data_=data.drop(['slug','ranknow','volume','market'], axis=1)\n",
"data_.head()"
]
},
{
"cell_type": "code",
"execution_count": 13,
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{
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"text/plain": [
" symbol name date open high low close \\\n",
"row_id \n",
"1 BTC Bitcoin 2013-04-28 135.30 135.98 132.10 134.21 \n",
"2 BTC Bitcoin 2013-04-29 134.44 147.49 134.00 144.54 \n",
"3 BTC Bitcoin 2013-04-30 144.00 146.93 134.05 139.00 \n",
"4 BTC Bitcoin 2013-05-01 139.00 139.89 107.72 116.99 \n",
"5 BTC Bitcoin 2013-05-02 116.38 125.60 92.28 105.21 \n",
"\n",
" close_ratio spread \n",
"row_id \n",
"1 0.5438 3.88 \n",
"2 0.7813 13.49 \n",
"3 0.3843 12.88 \n",
"4 0.2882 32.17 \n",
"5 0.3881 33.32 "
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" <td>Bitcoin</td>\n",
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" <td>134.44</td>\n",
" <td>147.49</td>\n",
" <td>134.00</td>\n",
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" <td>0.7813</td>\n",
" <td>13.49</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-04-30</td>\n",
" <td>144.00</td>\n",
" <td>146.93</td>\n",
" <td>134.05</td>\n",
" <td>139.00</td>\n",
" <td>0.3843</td>\n",
" <td>12.88</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-05-01</td>\n",
" <td>139.00</td>\n",
" <td>139.89</td>\n",
" <td>107.72</td>\n",
" <td>116.99</td>\n",
" <td>0.2882</td>\n",
" <td>32.17</td>\n",
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" <tr>\n",
" <th>5</th>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-05-02</td>\n",
" <td>116.38</td>\n",
" <td>125.60</td>\n",
" <td>92.28</td>\n",
" <td>105.21</td>\n",
" <td>0.3881</td>\n",
" <td>33.32</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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"\n",
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" display: none;\n",
" fill: #1967D2;\n",
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" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
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"\n",
" .colab-df-buttons div {\n",
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" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
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"\n",
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" document.querySelector('#df-8a72de84-25c7-4da0-9c72-73d7dad7c078 button.colab-df-convert');\n",
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" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-8a72de84-25c7-4da0-9c72-73d7dad7c078');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
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" element.appendChild(docLink);\n",
" }\n",
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"\n",
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"<div id=\"df-535b2ca0-7cad-4fb7-88cf-7ecbdb137872\">\n",
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"</svg>\n",
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" .colab-df-quickchart {\n",
" --bg-color: #E8F0FE;\n",
" --fill-color: #1967D2;\n",
" --hover-bg-color: #E2EBFA;\n",
" --hover-fill-color: #174EA6;\n",
" --disabled-fill-color: #AAA;\n",
" --disabled-bg-color: #DDD;\n",
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"\n",
" [theme=dark] .colab-df-quickchart {\n",
" --bg-color: #3B4455;\n",
" --fill-color: #D2E3FC;\n",
" --hover-bg-color: #434B5C;\n",
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" --disabled-fill-color: #666;\n",
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"\n",
" .colab-df-quickchart {\n",
" background-color: var(--bg-color);\n",
" border: none;\n",
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" fill: var(--button-hover-fill-color);\n",
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" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
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],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "data_"
}
},
"metadata": {},
"execution_count": 13
}
],
"source": [
"data_.set_index('row_id', inplace=True)\n",
"data_.head()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Bynw95JgNUx6",
"outputId": "242f03af-22c1-4628-e5d0-a3923cda0061"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array(['Bitcoin', 'XRP', 'Ethereum', ..., '42-coin', 'Bit20', 'Project-X'],\n",
" dtype=object)"
]
},
"metadata": {},
"execution_count": 14
}
],
"source": [
"#counitng unique symbols\n",
"data[\"name\"].unique() #total number of unique cryptos"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"id": "xjq9b8pRNR9C"
},
"outputs": [],
"source": [
"#set date to timestamp format\n",
"data_['date'] = pd.to_datetime(data_['date']).dt.date"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"id": "OVpiyV4PS4wY"
},
"outputs": [],
"source": [
"#pick out the currency for two years span (2016>)\n",
"\n",
"date = data_[data_['date'] >= dt.date(2016, 1, 1)]"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"id": "Vvz_kNbgS5dQ"
},
"outputs": [],
"source": [
"#show if each one closed up or down each day\n",
"date['pos_neg']= date['open']-date['close']\n",
"date.head()\n",
"#create a binary column - 0 = gain, 1 = loss to have something to predict\n",
"date['Up/Down'] = np.where(date['pos_neg']>0, '0', '1')"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"id": "uZLR2R9WQyzR"
},
"outputs": [],
"source": [
"#create data sets for different crypto currencies\n",
"etherdate = date[date['symbol']=='ETH']\n",
"ltcdate = date[date['symbol']=='LTC']\n",
"tetherdate = date[date['symbol']=='USDT']\n",
"cardanodate = date[date['symbol']=='ADA']\n",
"rippledate = date[date['symbol']=='XRP']"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"id": "TQKkNj3wUM6B"
},
"outputs": [],
"source": [
"#concat the different frames into one\n",
"frames=[etherdate,ltcdate,tetherdate,cardanodate,rippledate]\n",
"five_crypto = pd.concat(frames)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Zjb4kqCzVXwY",
"outputId": "1ac1d18b-416a-43be-c423-7cbb5e801247"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 4681 entries, 4134 to 3986\n",
"Data columns (total 11 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 symbol 4681 non-null object \n",
" 1 name 4681 non-null object \n",
" 2 date 4681 non-null object \n",
" 3 open 4681 non-null float64\n",
" 4 high 4681 non-null float64\n",
" 5 low 4681 non-null float64\n",
" 6 close 4681 non-null float64\n",
" 7 close_ratio 4681 non-null float64\n",
" 8 spread 4681 non-null float64\n",
" 9 pos_neg 4681 non-null float64\n",
" 10 Up/Down 4681 non-null object \n",
"dtypes: float64(7), object(4)\n",
"memory usage: 438.8+ KB\n"
]
}
],
"source": [
"five_crypto.info()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 466
},
"id": "TXNuyzFoVevf",
"outputId": "4cde6470-3845-4275-b6c1-c625e404fe2d"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<Axes: xlabel='symbol', ylabel='count'>"
]
},
"metadata": {},
"execution_count": 21
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"#this chart shows each of the six and the number of times they closed up for the day.\n",
"sns.set_style('whitegrid')\n",
"import seaborn as sns\n",
"\n",
"# Set the style\n",
"sns.set(style=\"whitegrid\")\n",
"\n",
"# Use catplot instead of factorplot\n",
"g = sns.catplot(\n",
" x=\"symbol\",\n",
" y=\"close_ratio\",\n",
" hue=\"Up/Down\",\n",
" data=five_crypto,\n",
" kind=\"bar\",\n",
" height=6,\n",
" palette=\"muted\",\n",
" legend_out=True\n",
")\n",
"\n",
"# Customize the plot\n",
"g.despine(left=True)\n",
"g.set_ylabels(\"Ratio Count\")\n",
"sns.countplot(x='symbol',hue='Up/Down',data=five_crypto,palette='rainbow')"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 617
},
"id": "b-KaRiCFVlF3",
"outputId": "16581077-8af7-40d0-87a9-81b3f2444e6c"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x787961060dc0>"
]
},
"metadata": {},
"execution_count": 63
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 687.722x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"# Set the style\n",
"sns.set(style=\"whitegrid\")\n",
"\n",
"# Use catplot to create a single plot\n",
"g = sns.catplot(\n",
" x=\"symbol\",\n",
" y=\"close_ratio\",\n",
" hue=\"Up/Down\",\n",
" data=five_crypto,\n",
" kind=\"bar\",\n",
" height=6,\n",
" palette=\"muted\",\n",
" legend_out=True\n",
")\n",
"\n",
"# Customize the plot\n",
"g.despine(left=True)\n",
"g.set_ylabels(\"Ratio Count\")\n"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"id": "S3ZOHw0xW5RK"
},
"outputs": [],
"source": [
"data['market_billion'] = data['market'] / 1000000000\n",
"data['volume_million'] = data['volume'] / 1000000000\n",
"data['volume_billion'] = data['volume']"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 294
},
"id": "s86ZmNTCWvdf",
"outputId": "d180cad9-ac57-4778-f813-4631e7343ad7"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"name 0chain 0x 0xBitcoin 0xcert 1World 2GIVE 300 Token 42-coin \\\n",
"date \n",
"2013-04-28 NaN NaN NaN NaN NaN NaN NaN NaN \n",
"2013-04-29 NaN NaN NaN NaN NaN NaN NaN NaN \n",
"2013-04-30 NaN NaN NaN NaN NaN NaN NaN NaN \n",
"\n",
"name 4NEW 808Coin ... imbrex indaHash nDEX nUSD savedroid \\\n",
"date ... \n",
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],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "wide_format"
}
},
"metadata": {},
"execution_count": 28
}
],
"source": [
"# Let's prepare one dataframe where we will observe closing prices for each currency\n",
"wide_format = data.groupby(['date', 'name'])['close'].last().unstack()\n",
"wide_format.head(3)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 480
},
"id": "fKfl6z3bWxMP",
"outputId": "87153dd6-b57d-4164-b494-5a1be333bd20"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"ax = data.groupby(['name'])['market_billion'].last().sort_values(ascending=False).head(10).sort_values().plot(kind='barh');\n",
"ax.set_xlabel(\"Market cap (in billion USD)\");\n",
"plt.title(\"Top 10 Currencies by Market Cap\");"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 480
},
"id": "4MJQipOJXAlD",
"outputId": "10b1749b-8009-4e44-970a-388c0f342acb"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"ax = data.groupby(['name'])['volume_million'].last().sort_values(ascending=False).head(10).sort_values().plot(kind='barh');\n",
"ax.set_xlabel(\"Transaction Volume (in million)\");\n",
"plt.title(\"Top 10 Currencies by Transaction Volume\");"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 313
},
"id": "qfrzkuc2XbeX",
"outputId": "b0916fc9-28ed-4d0b-cfea-cb0cdef6719c"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" slug symbol name date ranknow open high low \\\n",
"0 bitcoin BTC Bitcoin 2013-04-28 1 135.30 135.98 132.10 \n",
"1 bitcoin BTC Bitcoin 2013-04-29 1 134.44 147.49 134.00 \n",
"2 bitcoin BTC Bitcoin 2013-04-30 1 144.00 146.93 134.05 \n",
"3 bitcoin BTC Bitcoin 2013-05-01 1 139.00 139.89 107.72 \n",
"4 bitcoin BTC Bitcoin 2013-05-02 1 116.38 125.60 92.28 \n",
"\n",
" close volume market close_ratio spread row_id market_billion \\\n",
"0 134.21 0.0 1.488567e+09 0.5438 3.88 1 1.488567 \n",
"1 144.54 0.0 1.603769e+09 0.7813 13.49 2 1.603769 \n",
"2 139.00 0.0 1.542813e+09 0.3843 12.88 3 1.542813 \n",
"3 116.99 0.0 1.298955e+09 0.2882 32.17 4 1.298955 \n",
"4 105.21 0.0 1.168517e+09 0.3881 33.32 5 1.168517 \n",
"\n",
" volume_million volume_billion \n",
"0 0.0 0.0 \n",
"1 0.0 0.0 \n",
"2 0.0 0.0 \n",
"3 0.0 0.0 \n",
"4 0.0 0.0 "
],
"text/html": [
"\n",
" <div id=\"df-14f07a8a-1534-4952-988e-2a3b70358198\" class=\"colab-df-container\">\n",
" <div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>slug</th>\n",
" <th>symbol</th>\n",
" <th>name</th>\n",
" <th>date</th>\n",
" <th>ranknow</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" <th>market</th>\n",
" <th>close_ratio</th>\n",
" <th>spread</th>\n",
" <th>row_id</th>\n",
" <th>market_billion</th>\n",
" <th>volume_million</th>\n",
" <th>volume_billion</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>bitcoin</td>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-04-28</td>\n",
" <td>1</td>\n",
" <td>135.30</td>\n",
" <td>135.98</td>\n",
" <td>132.10</td>\n",
" <td>134.21</td>\n",
" <td>0.0</td>\n",
" <td>1.488567e+09</td>\n",
" <td>0.5438</td>\n",
" <td>3.88</td>\n",
" <td>1</td>\n",
" <td>1.488567</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>bitcoin</td>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-04-29</td>\n",
" <td>1</td>\n",
" <td>134.44</td>\n",
" <td>147.49</td>\n",
" <td>134.00</td>\n",
" <td>144.54</td>\n",
" <td>0.0</td>\n",
" <td>1.603769e+09</td>\n",
" <td>0.7813</td>\n",
" <td>13.49</td>\n",
" <td>2</td>\n",
" <td>1.603769</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>bitcoin</td>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-04-30</td>\n",
" <td>1</td>\n",
" <td>144.00</td>\n",
" <td>146.93</td>\n",
" <td>134.05</td>\n",
" <td>139.00</td>\n",
" <td>0.0</td>\n",
" <td>1.542813e+09</td>\n",
" <td>0.3843</td>\n",
" <td>12.88</td>\n",
" <td>3</td>\n",
" <td>1.542813</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>bitcoin</td>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-05-01</td>\n",
" <td>1</td>\n",
" <td>139.00</td>\n",
" <td>139.89</td>\n",
" <td>107.72</td>\n",
" <td>116.99</td>\n",
" <td>0.0</td>\n",
" <td>1.298955e+09</td>\n",
" <td>0.2882</td>\n",
" <td>32.17</td>\n",
" <td>4</td>\n",
" <td>1.298955</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>bitcoin</td>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-05-02</td>\n",
" <td>1</td>\n",
" <td>116.38</td>\n",
" <td>125.60</td>\n",
" <td>92.28</td>\n",
" <td>105.21</td>\n",
" <td>0.0</td>\n",
" <td>1.168517e+09</td>\n",
" <td>0.3881</td>\n",
" <td>33.32</td>\n",
" <td>5</td>\n",
" <td>1.168517</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
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],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "data_top_6_currencies",
"summary": "{\n \"name\": \"data_top_6_currencies\",\n \"rows\": 7787,\n \"fields\": [\n {\n \"column\": \"slug\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"bitcoin\",\n \"ripple\",\n \"eos\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"symbol\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"BTC\",\n \"XRP\",\n \"EOS\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"name\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"Bitcoin\",\n \"XRP\",\n \"EOS\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"date\",\n \"properties\": {\n \"dtype\": \"object\",\n \"num_unique_values\": 2042,\n \"samples\": [\n \"2016-12-04\",\n \"2016-01-23\",\n \"2016-03-31\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ranknow\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 1,\n \"max\": 6,\n \"num_unique_values\": 6,\n \"samples\": [\n 1,\n 2,\n 6\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"open\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2021.9549399687044,\n \"min\": 0.001352,\n \"max\": 19475.8,\n \"num_unique_values\": 7042,\n \"samples\": [\n 10687.2,\n 586.2,\n 197.69\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2093.5248367238237,\n \"min\": 0.001509,\n \"max\": 20089.0,\n \"num_unique_values\": 7072,\n \"samples\": [\n 0.002962,\n 0.006189,\n 310.5\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1936.2166508577743,\n \"min\": 0.001227,\n \"max\": 18974.1,\n \"num_unique_values\": 7048,\n \"samples\": [\n 0.078704,\n 4269.81,\n 0.021744\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"close\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2022.1939101331898,\n \"min\": 0.001357,\n \"max\": 19497.4,\n \"num_unique_values\": 7082,\n \"samples\": [\n 0.006887,\n 0.290193,\n 224.63\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1783223435.3139007,\n \"min\": 0.0,\n \"max\": 23840899072.0,\n \"num_unique_values\": 7384,\n \"samples\": [\n 36825.0,\n 4569880064.0,\n 125594000.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"market\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 35663563386.883026,\n \"min\": 0.0,\n \"max\": 326502485530.0,\n \"num_unique_values\": 7774,\n \"samples\": [\n 17107266418.0,\n 273422464.0,\n 8937822572.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"close_ratio\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.309769181558466,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 4901,\n \"samples\": [\n 0.8167,\n 0.997,\n 0.6304\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"spread\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 198.11968044303455,\n \"min\": 0.0,\n \"max\": 4110.4,\n \"num_unique_values\": 2812,\n \"samples\": [\n 17.75,\n 16.74,\n 202.35\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"row_id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2248,\n \"min\": 1,\n \"max\": 7787,\n \"num_unique_values\": 7787,\n \"samples\": [\n 7325,\n 4695,\n 1323\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"market_billion\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 35.66356338688318,\n \"min\": 0.0,\n \"max\": 326.50248553,\n \"num_unique_values\": 7774,\n \"samples\": [\n 17.107266418,\n 0.273422464,\n 8.937822572\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume_million\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.7832234353139145,\n \"min\": 0.0,\n \"max\": 23.840899072,\n \"num_unique_values\": 7384,\n \"samples\": [\n 3.6825e-05,\n 4.569880064,\n 0.125594\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume_billion\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1783223435.3139007,\n \"min\": 0.0,\n \"max\": 23840899072.0,\n \"num_unique_values\": 7384,\n \"samples\": [\n 36825.0,\n 4569880064.0,\n 125594000.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 31
}
],
"source": [
"# For sake of convenience, let's define the top 6 currencies\n",
"\n",
"top_6_currency_names = data.groupby(['name'])['market'].last().sort_values(ascending=False).head(6).index\n",
"data_top_6_currencies = data[data['name'].isin(top_6_currency_names)]\n",
"data_top_6_currencies.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 480
},
"id": "X2vurY0xXmff",
"outputId": "2b6799e5-29d6-45d2-f3d0-122c4666f8f5"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"ax = data_top_6_currencies.groupby(['date', 'name'])['close'].mean().unstack().plot();\n",
"ax.set_ylabel(\"Price per 1 unit (in USD)\");\n",
"plt.title(\"Price per unit currency\");"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 480
},
"id": "0XQYcAf8Xy2o",
"outputId": "ac40a890-3d5d-4a02-d3b6-ad326784bad0"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"ax = data_top_6_currencies.groupby(['date', 'name'])['market_billion'].mean().unstack().plot();\n",
"ax.set_ylabel(\"Market Cap (in billion USD)\");\n",
"plt.title(\"Market cap per unit currency\");"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 710
},
"id": "_Ezp2S7NX9sI",
"outputId": "b51c7ab4-68b3-42f8-f20e-1e35ed044f06"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1400x800 with 2 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"#co-relation between different cryptos\n",
"plt.figure(figsize=(14,8))\n",
"sns.heatmap(wide_format[top_6_currency_names].corr(),vmin=0, vmax=1, cmap='coolwarm', annot=True);"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 313
},
"id": "NbAmRhK-CrQV",
"outputId": "0e8cbb22-d023-4442-d20a-4a071b2260ad"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" slug symbol name date ranknow open high low \\\n",
"0 bitcoin BTC Bitcoin 2013-04-28 1 135.30 135.98 132.10 \n",
"1 bitcoin BTC Bitcoin 2013-04-29 1 134.44 147.49 134.00 \n",
"2 bitcoin BTC Bitcoin 2013-04-30 1 144.00 146.93 134.05 \n",
"3 bitcoin BTC Bitcoin 2013-05-01 1 139.00 139.89 107.72 \n",
"4 bitcoin BTC Bitcoin 2013-05-02 1 116.38 125.60 92.28 \n",
"\n",
" close volume market close_ratio spread row_id market_billion \\\n",
"0 134.21 0.0 1.488567e+09 0.5438 3.88 1 1.488567 \n",
"1 144.54 0.0 1.603769e+09 0.7813 13.49 2 1.603769 \n",
"2 139.00 0.0 1.542813e+09 0.3843 12.88 3 1.542813 \n",
"3 116.99 0.0 1.298955e+09 0.2882 32.17 4 1.298955 \n",
"4 105.21 0.0 1.168517e+09 0.3881 33.32 5 1.168517 \n",
"\n",
" volume_million volume_billion \n",
"0 0.0 0.0 \n",
"1 0.0 0.0 \n",
"2 0.0 0.0 \n",
"3 0.0 0.0 \n",
"4 0.0 0.0 "
],
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" <td>bitcoin</td>\n",
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" <td>2013-04-29</td>\n",
" <td>1</td>\n",
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" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-04-30</td>\n",
" <td>1</td>\n",
" <td>144.00</td>\n",
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" <td>1</td>\n",
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" <td>0.0</td>\n",
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" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-05-02</td>\n",
" <td>1</td>\n",
" <td>116.38</td>\n",
" <td>125.60</td>\n",
" <td>92.28</td>\n",
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"type": "dataframe",
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"summary": "{\n \"name\": \"data_top_6_currencies\",\n \"rows\": 7787,\n \"fields\": [\n {\n \"column\": \"slug\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"bitcoin\",\n \"ripple\",\n \"eos\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"symbol\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"BTC\",\n \"XRP\",\n \"EOS\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"name\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"Bitcoin\",\n \"XRP\",\n \"EOS\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"date\",\n \"properties\": {\n \"dtype\": \"object\",\n \"num_unique_values\": 2042,\n \"samples\": [\n \"2016-12-04\",\n \"2016-01-23\",\n \"2016-03-31\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ranknow\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1,\n \"min\": 1,\n \"max\": 6,\n \"num_unique_values\": 6,\n \"samples\": [\n 1,\n 2,\n 6\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"open\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2021.9549399687044,\n \"min\": 0.001352,\n \"max\": 19475.8,\n \"num_unique_values\": 7042,\n \"samples\": [\n 10687.2,\n 586.2,\n 197.69\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2093.5248367238237,\n \"min\": 0.001509,\n \"max\": 20089.0,\n \"num_unique_values\": 7072,\n \"samples\": [\n 0.002962,\n 0.006189,\n 310.5\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1936.2166508577743,\n \"min\": 0.001227,\n \"max\": 18974.1,\n \"num_unique_values\": 7048,\n \"samples\": [\n 0.078704,\n 4269.81,\n 0.021744\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"close\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2022.1939101331898,\n \"min\": 0.001357,\n \"max\": 19497.4,\n \"num_unique_values\": 7082,\n \"samples\": [\n 0.006887,\n 0.290193,\n 224.63\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1783223435.3139007,\n \"min\": 0.0,\n \"max\": 23840899072.0,\n \"num_unique_values\": 7384,\n \"samples\": [\n 36825.0,\n 4569880064.0,\n 125594000.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"market\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 35663563386.883026,\n \"min\": 0.0,\n \"max\": 326502485530.0,\n \"num_unique_values\": 7774,\n \"samples\": [\n 17107266418.0,\n 273422464.0,\n 8937822572.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"close_ratio\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.309769181558466,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 4901,\n \"samples\": [\n 0.8167,\n 0.997,\n 0.6304\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"spread\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 198.11968044303455,\n \"min\": 0.0,\n \"max\": 4110.4,\n \"num_unique_values\": 2812,\n \"samples\": [\n 17.75,\n 16.74,\n 202.35\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"row_id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2248,\n \"min\": 1,\n \"max\": 7787,\n \"num_unique_values\": 7787,\n \"samples\": [\n 7325,\n 4695,\n 1323\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"market_billion\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 35.66356338688318,\n \"min\": 0.0,\n \"max\": 326.50248553,\n \"num_unique_values\": 7774,\n \"samples\": [\n 17.107266418,\n 0.273422464,\n 8.937822572\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume_million\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.7832234353139145,\n \"min\": 0.0,\n \"max\": 23.840899072,\n \"num_unique_values\": 7384,\n \"samples\": [\n 3.6825e-05,\n 4.569880064,\n 0.125594\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume_billion\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1783223435.3139007,\n \"min\": 0.0,\n \"max\": 23840899072.0,\n \"num_unique_values\": 7384,\n \"samples\": [\n 36825.0,\n 4569880064.0,\n 125594000.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
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},
"metadata": {},
"execution_count": 35
}
],
"source": [
"data_top_6_currencies.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
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"height": 617
},
"id": "yy3-xD2qJ8lI",
"outputId": "9c7299f4-9ad4-49f2-b94d-631f18923d01"
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"outputs": [
{
"output_type": "execute_result",
"data": {
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" slug symbol name date open high low close \\\n",
"0 bitcoin BTC Bitcoin 2013-04-28 135.30 135.98 132.10 134.21 \n",
"1 bitcoin BTC Bitcoin 2013-04-29 134.44 147.49 134.00 144.54 \n",
"2 bitcoin BTC Bitcoin 2013-04-30 144.00 146.93 134.05 139.00 \n",
"3 bitcoin BTC Bitcoin 2013-05-01 139.00 139.89 107.72 116.99 \n",
"4 bitcoin BTC Bitcoin 2013-05-02 116.38 125.60 92.28 105.21 \n",
"... ... ... ... ... ... ... ... ... \n",
"7782 eos EOS EOS 2018-11-25 3.27 3.43 3.03 3.35 \n",
"7783 eos EOS EOS 2018-11-26 3.35 3.41 3.08 3.18 \n",
"7784 eos EOS EOS 2018-11-27 3.18 3.18 2.90 3.03 \n",
"7785 eos EOS EOS 2018-11-28 3.03 3.37 3.03 3.28 \n",
"7786 eos EOS EOS 2018-11-29 3.29 3.30 2.93 3.02 \n",
"\n",
" volume market close_ratio spread row_id market_billion \\\n",
"0 0.000000e+00 1.488567e+09 0.5438 3.88 1 1.488567 \n",
"1 0.000000e+00 1.603769e+09 0.7813 13.49 2 1.603769 \n",
"2 0.000000e+00 1.542813e+09 0.3843 12.88 3 1.542813 \n",
"3 0.000000e+00 1.298955e+09 0.2882 32.17 4 1.298955 \n",
"4 0.000000e+00 1.168517e+09 0.3881 33.32 5 1.168517 \n",
"... ... ... ... ... ... ... \n",
"7782 1.057330e+09 3.035994e+09 0.8000 0.40 7783 3.035994 \n",
"7783 9.845280e+08 2.885294e+09 0.3030 0.33 7784 2.885294 \n",
"7784 9.577230e+08 2.746077e+09 0.4643 0.28 7785 2.746077 \n",
"7785 8.601480e+08 2.971913e+09 0.7353 0.34 7786 2.971913 \n",
"7786 8.963941e+08 2.738537e+09 0.2432 0.37 7787 2.738537 \n",
"\n",
" volume_million volume_billion \n",
"0 0.000000 0.000000e+00 \n",
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"... ... ... \n",
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"7786 0.896394 8.963941e+08 \n",
"\n",
"[7787 rows x 16 columns]"
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" <th>7786</th>\n",
" <td>eos</td>\n",
" <td>EOS</td>\n",
" <td>EOS</td>\n",
" <td>2018-11-29</td>\n",
" <td>3.29</td>\n",
" <td>3.30</td>\n",
" <td>2.93</td>\n",
" <td>3.02</td>\n",
" <td>8.963941e+08</td>\n",
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" <td>0.37</td>\n",
" <td>7787</td>\n",
" <td>2.738537</td>\n",
" <td>0.896394</td>\n",
" <td>8.963941e+08</td>\n",
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"summary": "{\n \"name\": \"data_top_6_currencies\",\n \"rows\": 7787,\n \"fields\": [\n {\n \"column\": \"slug\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"bitcoin\",\n \"ripple\",\n \"eos\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"symbol\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"BTC\",\n \"XRP\",\n \"EOS\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"name\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"Bitcoin\",\n \"XRP\",\n \"EOS\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"date\",\n \"properties\": {\n \"dtype\": \"object\",\n \"num_unique_values\": 2042,\n \"samples\": [\n \"2016-12-04\",\n \"2016-01-23\",\n \"2016-03-31\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"open\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2021.9549399687044,\n \"min\": 0.001352,\n \"max\": 19475.8,\n \"num_unique_values\": 7042,\n \"samples\": [\n 10687.2,\n 586.2,\n 197.69\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2093.5248367238237,\n \"min\": 0.001509,\n \"max\": 20089.0,\n \"num_unique_values\": 7072,\n \"samples\": [\n 0.002962,\n 0.006189,\n 310.5\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1936.2166508577743,\n \"min\": 0.001227,\n \"max\": 18974.1,\n \"num_unique_values\": 7048,\n \"samples\": [\n 0.078704,\n 4269.81,\n 0.021744\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"close\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2022.1939101331898,\n \"min\": 0.001357,\n \"max\": 19497.4,\n \"num_unique_values\": 7082,\n \"samples\": [\n 0.006887,\n 0.290193,\n 224.63\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1783223435.3139007,\n \"min\": 0.0,\n \"max\": 23840899072.0,\n \"num_unique_values\": 7384,\n \"samples\": [\n 36825.0,\n 4569880064.0,\n 125594000.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"market\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 35663563386.883026,\n \"min\": 0.0,\n \"max\": 326502485530.0,\n \"num_unique_values\": 7774,\n \"samples\": [\n 17107266418.0,\n 273422464.0,\n 8937822572.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"close_ratio\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.309769181558466,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 4901,\n \"samples\": [\n 0.8167,\n 0.997,\n 0.6304\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"spread\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 198.11968044303455,\n \"min\": 0.0,\n \"max\": 4110.4,\n \"num_unique_values\": 2812,\n \"samples\": [\n 17.75,\n 16.74,\n 202.35\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"row_id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2248,\n \"min\": 1,\n \"max\": 7787,\n \"num_unique_values\": 7787,\n \"samples\": [\n 7325,\n 4695,\n 1323\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"market_billion\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 35.66356338688318,\n \"min\": 0.0,\n \"max\": 326.50248553,\n \"num_unique_values\": 7774,\n \"samples\": [\n 17.107266418,\n 0.273422464,\n 8.937822572\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume_million\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.7832234353139145,\n \"min\": 0.0,\n \"max\": 23.840899072,\n \"num_unique_values\": 7384,\n \"samples\": [\n 3.6825e-05,\n 4.569880064,\n 0.125594\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume_billion\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1783223435.3139007,\n \"min\": 0.0,\n \"max\": 23840899072.0,\n \"num_unique_values\": 7384,\n \"samples\": [\n 36825.0,\n 4569880064.0,\n 125594000.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 36
}
],
"source": [
"data_top_6_currencies.drop(['ranknow'],axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "O1V5XiRaF1DU",
"outputId": "b3fc27fa-0990-4579-90b2-baec9d4b1b55"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(7787, 17)"
]
},
"metadata": {},
"execution_count": 37
}
],
"source": [
"data_top_6_currencies.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "TNJ2Lwm3KDAX"
},
"source": [
"#Bitcoin"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "49_WACQuDBll",
"outputId": "7887b55b-8fdd-44f3-fd0c-05214b41c0b0"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(2042, 17)"
]
},
"metadata": {},
"execution_count": 38
}
],
"source": [
"#bitcoin\n",
"df1 = data_top_6_currencies[data_top_6_currencies['name']=='Bitcoin']\n",
"\n",
"df1.shape"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "JjcbrGKDQTQC",
"outputId": "77ca99bd-f03a-4349-e747-247b2f2c3651"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" slug symbol name date ranknow open high low \\\n",
"0 bitcoin BTC Bitcoin 2013-04-28 1 135.30 135.98 132.10 \n",
"1 bitcoin BTC Bitcoin 2013-04-29 1 134.44 147.49 134.00 \n",
"2 bitcoin BTC Bitcoin 2013-04-30 1 144.00 146.93 134.05 \n",
"3 bitcoin BTC Bitcoin 2013-05-01 1 139.00 139.89 107.72 \n",
"4 bitcoin BTC Bitcoin 2013-05-02 1 116.38 125.60 92.28 \n",
"... ... ... ... ... ... ... ... ... \n",
"2037 bitcoin BTC Bitcoin 2018-11-25 1 3880.78 4120.87 3585.06 \n",
"2038 bitcoin BTC Bitcoin 2018-11-26 1 4015.07 4107.14 3643.92 \n",
"2039 bitcoin BTC Bitcoin 2018-11-27 1 3765.95 3862.96 3661.01 \n",
"2040 bitcoin BTC Bitcoin 2018-11-28 1 3822.47 4385.90 3822.47 \n",
"2041 bitcoin BTC Bitcoin 2018-11-29 1 4269.00 4413.02 4145.77 \n",
"\n",
" close volume market close_ratio spread row_id \\\n",
"0 134.21 0.000000e+00 1.488567e+09 0.5438 3.88 1 \n",
"1 144.54 0.000000e+00 1.603769e+09 0.7813 13.49 2 \n",
"2 139.00 0.000000e+00 1.542813e+09 0.3843 12.88 3 \n",
"3 116.99 0.000000e+00 1.298955e+09 0.2882 32.17 4 \n",
"4 105.21 0.000000e+00 1.168517e+09 0.3881 33.32 5 \n",
"... ... ... ... ... ... ... \n",
"2037 4009.97 6.825640e+09 6.974927e+10 0.7930 535.81 2038 \n",
"2038 3779.13 6.476900e+09 6.573929e+10 0.2919 463.22 2039 \n",
"2039 3820.72 5.998720e+09 6.646897e+10 0.7908 201.95 2040 \n",
"2040 4257.42 7.280280e+09 7.407256e+10 0.7720 563.43 2041 \n",
"2041 4278.85 6.503348e+09 7.445102e+10 0.4980 267.25 2042 \n",
"\n",
" market_billion volume_million volume_billion \n",
"0 1.488567 0.000000 0.000000e+00 \n",
"1 1.603769 0.000000 0.000000e+00 \n",
"2 1.542813 0.000000 0.000000e+00 \n",
"3 1.298955 0.000000 0.000000e+00 \n",
"4 1.168517 0.000000 0.000000e+00 \n",
"... ... ... ... \n",
"2037 69.749266 6.825640 6.825640e+09 \n",
"2038 65.739289 6.476900 6.476900e+09 \n",
"2039 66.468970 5.998720 5.998720e+09 \n",
"2040 74.072560 7.280280 7.280280e+09 \n",
"2041 74.451017 6.503348 6.503348e+09 \n",
"\n",
"[2042 rows x 17 columns]\n"
]
}
],
"source": [
"print(df1)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 313
},
"id": "l6R9yP7G_7C9",
"outputId": "2f4740ef-d6c7-4e72-d6e8-0a16d4a930f7"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" slug symbol name date ranknow open high low \\\n",
"0 bitcoin BTC Bitcoin 2013-04-28 1 135.30 135.98 132.10 \n",
"1 bitcoin BTC Bitcoin 2013-04-29 1 134.44 147.49 134.00 \n",
"2 bitcoin BTC Bitcoin 2013-04-30 1 144.00 146.93 134.05 \n",
"3 bitcoin BTC Bitcoin 2013-05-01 1 139.00 139.89 107.72 \n",
"4 bitcoin BTC Bitcoin 2013-05-02 1 116.38 125.60 92.28 \n",
"\n",
" close volume market close_ratio spread row_id market_billion \\\n",
"0 134.21 0.0 1.488567e+09 0.5438 3.88 1 1.488567 \n",
"1 144.54 0.0 1.603769e+09 0.7813 13.49 2 1.603769 \n",
"2 139.00 0.0 1.542813e+09 0.3843 12.88 3 1.542813 \n",
"3 116.99 0.0 1.298955e+09 0.2882 32.17 4 1.298955 \n",
"4 105.21 0.0 1.168517e+09 0.3881 33.32 5 1.168517 \n",
"\n",
" volume_million volume_billion \n",
"0 0.0 0.0 \n",
"1 0.0 0.0 \n",
"2 0.0 0.0 \n",
"3 0.0 0.0 \n",
"4 0.0 0.0 "
],
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"\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>slug</th>\n",
" <th>symbol</th>\n",
" <th>name</th>\n",
" <th>date</th>\n",
" <th>ranknow</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" <th>market</th>\n",
" <th>close_ratio</th>\n",
" <th>spread</th>\n",
" <th>row_id</th>\n",
" <th>market_billion</th>\n",
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" <th>volume_billion</th>\n",
" </tr>\n",
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" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>bitcoin</td>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-04-28</td>\n",
" <td>1</td>\n",
" <td>135.30</td>\n",
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" <td>0.0</td>\n",
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" <td>0.5438</td>\n",
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" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>bitcoin</td>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-04-29</td>\n",
" <td>1</td>\n",
" <td>134.44</td>\n",
" <td>147.49</td>\n",
" <td>134.00</td>\n",
" <td>144.54</td>\n",
" <td>0.0</td>\n",
" <td>1.603769e+09</td>\n",
" <td>0.7813</td>\n",
" <td>13.49</td>\n",
" <td>2</td>\n",
" <td>1.603769</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>bitcoin</td>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-04-30</td>\n",
" <td>1</td>\n",
" <td>144.00</td>\n",
" <td>146.93</td>\n",
" <td>134.05</td>\n",
" <td>139.00</td>\n",
" <td>0.0</td>\n",
" <td>1.542813e+09</td>\n",
" <td>0.3843</td>\n",
" <td>12.88</td>\n",
" <td>3</td>\n",
" <td>1.542813</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>bitcoin</td>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-05-01</td>\n",
" <td>1</td>\n",
" <td>139.00</td>\n",
" <td>139.89</td>\n",
" <td>107.72</td>\n",
" <td>116.99</td>\n",
" <td>0.0</td>\n",
" <td>1.298955e+09</td>\n",
" <td>0.2882</td>\n",
" <td>32.17</td>\n",
" <td>4</td>\n",
" <td>1.298955</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>bitcoin</td>\n",
" <td>BTC</td>\n",
" <td>Bitcoin</td>\n",
" <td>2013-05-02</td>\n",
" <td>1</td>\n",
" <td>116.38</td>\n",
" <td>125.60</td>\n",
" <td>92.28</td>\n",
" <td>105.21</td>\n",
" <td>0.0</td>\n",
" <td>1.168517e+09</td>\n",
" <td>0.3881</td>\n",
" <td>33.32</td>\n",
" <td>5</td>\n",
" <td>1.168517</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
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"\n",
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" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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" .colab-df-buttons div {\n",
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" }\n",
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" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
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"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
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" }\n",
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" --bg-color: #E8F0FE;\n",
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"\n",
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" fill: var(--button-hover-fill-color);\n",
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"\n",
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"\n",
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" border: 2px solid var(--fill-color);\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" animation:\n",
" spin 1s steps(1) infinite;\n",
" }\n",
"\n",
" @keyframes spin {\n",
" 0% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" border-left-color: var(--fill-color);\n",
" }\n",
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" border-bottom-color: var(--fill-color);\n",
" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
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" }\n",
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" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
" }\n",
" (() => {\n",
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" document.querySelector('#df-fea13da4-151e-47d8-a66e-ba8bec9c91fb button');\n",
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"</div>\n",
"\n",
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],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "df1",
"summary": "{\n \"name\": \"df1\",\n \"rows\": 2042,\n \"fields\": [\n {\n \"column\": \"slug\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 1,\n \"samples\": [\n \"bitcoin\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"symbol\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 1,\n \"samples\": [\n \"BTC\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"name\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 1,\n \"samples\": [\n \"Bitcoin\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"date\",\n \"properties\": {\n \"dtype\": \"object\",\n \"num_unique_values\": 2042,\n \"samples\": [\n \"2016-12-04\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ranknow\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 1,\n \"max\": 1,\n \"num_unique_values\": 1,\n \"samples\": [\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"open\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 3438.652272308993,\n \"min\": 68.5,\n \"max\": 19475.8,\n \"num_unique_values\": 2016,\n \"samples\": [\n 577.59\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 3563.970933818215,\n \"min\": 74.56,\n \"max\": 20089.0,\n \"num_unique_values\": 2012,\n \"samples\": [\n 1044.08\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 3285.670083319126,\n \"min\": 65.53,\n \"max\": 18974.1,\n \"num_unique_values\": 2024,\n \"samples\": [\n 638.66\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"close\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 3438.366701697527,\n \"min\": 68.43,\n \"max\": 19497.4,\n \"num_unique_values\": 2013,\n \"samples\": [\n 998.33\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 3042556003.8233366,\n \"min\": 0.0,\n \"max\": 23840899072.0,\n \"num_unique_values\": 1800,\n \"samples\": [\n 7651939840.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"market\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 58536111323.00077,\n \"min\": 778411179.0,\n \"max\": 326502485530.0,\n \"num_unique_values\": 2041,\n \"samples\": [\n 12159115875.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"close_ratio\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.2999006113822839,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 1737,\n \"samples\": [\n 0.2954\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"spread\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 355.9942922404676,\n \"min\": 0.0,\n \"max\": 4110.4,\n \"num_unique_values\": 1740,\n \"samples\": [\n 12.97\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"row_id\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 589,\n \"min\": 1,\n \"max\": 2042,\n \"num_unique_values\": 2042,\n \"samples\": [\n 1317\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"market_billion\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 58.53611132300076,\n \"min\": 0.778411179,\n \"max\": 326.50248553,\n \"num_unique_values\": 2041,\n \"samples\": [\n 12.159115875\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume_million\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 3.0425560038233352,\n \"min\": 0.0,\n \"max\": 23.840899072,\n \"num_unique_values\": 1800,\n \"samples\": [\n 7.65193984\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"volume_billion\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 3042556003.8233366,\n \"min\": 0.0,\n \"max\": 23840899072.0,\n \"num_unique_values\": 1800,\n \"samples\": [\n 7651939840.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 40
}
],
"source": [
"df1.head()"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "X4QbNB76AUtO",
"outputId": "eacce8af-8808-4bc0-cd80-a746a520dd4a"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" open high low close volume\n",
"0 135.30 135.98 132.10 134.21 0.0\n",
"1 134.44 147.49 134.00 144.54 0.0\n",
"2 144.00 146.93 134.05 139.00 0.0\n",
"3 139.00 139.89 107.72 116.99 0.0\n",
"4 116.38 125.60 92.28 105.21 0.0\n",
"(2042, 5)\n"
]
}
],
"source": [
"d = df1.iloc[:, 5:10]\n",
"print(d.head())\n",
"print(d.shape)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 590
},
"id": "zDuTpvheHFQ-",
"outputId": "c0506dc5-9e48-4f88-c039-43c5017f2cf4"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Price of Bitcoin')"
]
},
"metadata": {},
"execution_count": 42
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"plt.figure(figsize=(12,6))\n",
"sns.lineplot(x=d.index, y=\"open\", data=d).set_title(\"Price of Bitcoin\")"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "35cpNfDfHFUN",
"outputId": "7dbf249b-3197-4d06-cc21-2e3c17b303f4"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2042\n",
"0 135.30\n",
"1 134.44\n",
"2 144.00\n",
"3 139.00\n",
"4 116.38\n",
" ... \n",
"2037 3880.78\n",
"2038 4015.07\n",
"2039 3765.95\n",
"2040 3822.47\n",
"2041 4269.00\n",
"Name: open, Length: 2042, dtype: float64\n"
]
}
],
"source": [
"data = d.iloc[:, 0]\n",
"print(len(data))\n",
"print(data)\n",
"hist = []\n",
"target = []\n",
"length = 90\n",
"for i in range(len(data)-length):\n",
" x = data[i:i+length]\n",
" y = data[i+length]\n",
" hist.append(x)\n",
" target.append(y)"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ybiiTeB7HFad",
"outputId": "b2c0faaf-2bc7-4918-e697-ec6705366b75"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"96.95\n",
"96.02\n",
"96.02\n"
]
}
],
"source": [
"print(hist[1][89])\n",
"print(data[90])\n",
"print(target[0])"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"id": "e5cpw-VsHTGw"
},
"outputs": [],
"source": [
"hist = np.array(hist)\n",
"target = np.array(target)\n",
"target = target.reshape(-1,1)"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"id": "Ook8PYf9HTLD"
},
"outputs": [],
"source": [
"from sklearn.preprocessing import MinMaxScaler\n",
"sc = MinMaxScaler()\n",
"hist_scaled = sc.fit_transform(hist)\n",
"target_scaled = sc.fit_transform(target)"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "T_-csG_1HTON",
"outputId": "9c3e7366-638a-4e67-fd19-ddd5b2d47b5f"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(1952, 90, 1)\n"
]
}
],
"source": [
"hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
"print(hist_scaled.shape)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"id": "Ui0ppeSGHTRf"
},
"outputs": [],
"source": [
"X_train = hist_scaled[:1900,:,:]\n",
"X_test = hist_scaled[1900:,:,:]\n",
"y_train = target_scaled[:1900,:]\n",
"y_test = target_scaled[1900:,:]"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"id": "T5o66_7XHTUm"
},
"outputs": [],
"source": [
"import tensorflow as tf\n",
"from tensorflow.keras import layers"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 272
},
"id": "9C8DS-c7Hgp1",
"outputId": "9e297bae-c143-4a19-d1ac-8e9823df822b"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1mModel: \"sequential\"\u001b[0m\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential\"</span>\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m4,352\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_1 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_2 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m) │ \u001b[38;5;34m33\u001b[0m │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃<span style=\"font-weight: bold\"> Layer (type) </span>┃<span style=\"font-weight: bold\"> Output Shape </span>┃<span style=\"font-weight: bold\"> Param # </span>┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">4,352</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span> │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
"</pre>\n"
]
},
"metadata": {}
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" input_shape=(90,1), dropout=0.2))\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" dropout=0.2))\n",
"model.add(layers.LSTM(units=32, dropout=0.2))\n",
"model.add(layers.Dense(units=1))\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"id": "0x4KIth9kAiG"
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {
"id": "P91hyF2GHgzR"
},
"outputs": [],
"source": [
"model.compile(optimizer='adam', loss='mean_squared_error')"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "I5uoPY81Hmy4",
"outputId": "fa460f6f-5307-4b64-e542-5c842a500685"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 1/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 97ms/step - loss: 0.0166\n",
"Epoch 2/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 121ms/step - loss: 0.0111\n",
"Epoch 3/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 122ms/step - loss: 0.0092\n",
"Epoch 4/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 130ms/step - loss: 0.0095\n",
"Epoch 5/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 170ms/step - loss: 0.0091\n",
"Epoch 6/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 120ms/step - loss: 0.0160\n",
"Epoch 7/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 153ms/step - loss: 0.0091\n",
"Epoch 8/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 122ms/step - loss: 0.0095\n",
"Epoch 9/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 158ms/step - loss: 0.0102\n",
"Epoch 10/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 122ms/step - loss: 0.0100\n",
"Epoch 11/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m13s\u001b[0m 169ms/step - loss: 0.0084\n",
"Epoch 12/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 157ms/step - loss: 0.0074\n",
"Epoch 13/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 118ms/step - loss: 0.0096\n",
"Epoch 14/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 141ms/step - loss: 0.0093\n",
"Epoch 15/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 155ms/step - loss: 0.0105\n",
"Epoch 16/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 125ms/step - loss: 0.0091\n",
"Epoch 17/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 121ms/step - loss: 0.0101\n",
"Epoch 18/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 142ms/step - loss: 0.0096\n",
"Epoch 19/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 134ms/step - loss: 0.0084\n",
"Epoch 20/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 122ms/step - loss: 0.0121\n",
"Epoch 21/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 158ms/step - loss: 0.0071\n",
"Epoch 22/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 110ms/step - loss: 0.0079\n",
"Epoch 23/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 97ms/step - loss: 0.0080\n",
"Epoch 24/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 124ms/step - loss: 0.0085\n",
"Epoch 25/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 111ms/step - loss: 0.0086\n",
"Epoch 26/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 109ms/step - loss: 0.0096\n",
"Epoch 27/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 128ms/step - loss: 0.0074\n",
"Epoch 28/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 96ms/step - loss: 0.0075\n",
"Epoch 29/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 97ms/step - loss: 0.0084\n",
"Epoch 30/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 100ms/step - loss: 0.0078\n"
]
}
],
"source": [
"history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 704
},
"id": "_2skqc4uHoo4",
"outputId": "e6b99861-4ed2-487e-b532-879ca978851a"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x800 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"loss = history.history['loss']\n",
"epoch_count = range(1, len(loss) + 1)\n",
"plt.figure(figsize=(12,8))\n",
"plt.plot(epoch_count, loss, 'r--')\n",
"plt.legend(['Training Loss'])\n",
"plt.xlabel('Epoch')\n",
"plt.ylabel('Loss')\n",
"plt.show();"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 720
},
"id": "XeNxAYOlHg8b",
"outputId": "7fe0b504-fbb4-4d4f-b1ca-b5f3bc5c98eb"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[1m2/2\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 728ms/step\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x800 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"pred = model.predict(X_test)\n",
"plt.figure(figsize=(12,8))\n",
"plt.plot(y_test, color='blue', label='Real')\n",
"plt.plot(pred, color='red', label='Prediction')\n",
"plt.title('Bitcoin Price Prediction')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "I7VuAnbfJByj"
},
"source": [
"#XRP (Ripple)"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ZK38bhh6JByj",
"outputId": "6e2edc2d-6d6b-428f-d510-df69536c869d"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(1944, 17)"
]
},
"metadata": {},
"execution_count": 55
}
],
"source": [
"#bitcoin\n",
"df2 = data_top_6_currencies[data_top_6_currencies['name']=='XRP']\n",
"\n",
"df2.shape"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "jV8de94uJByj",
"outputId": "2f4e0517-2586-4316-f015-929277f00068"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" slug symbol name date ranknow open high low \\\n",
"2042 ripple XRP XRP 2013-08-04 2 0.005874 0.005927 0.005874 \n",
"2043 ripple XRP XRP 2013-08-05 2 0.005875 0.005980 0.005613 \n",
"2044 ripple XRP XRP 2013-08-06 2 0.005637 0.005661 0.004629 \n",
"2045 ripple XRP XRP 2013-08-07 2 0.004669 0.004682 0.004333 \n",
"2046 ripple XRP XRP 2013-08-08 2 0.004397 0.004424 0.004175 \n",
"... ... ... ... ... ... ... ... ... \n",
"3981 ripple XRP XRP 2018-11-25 2 0.374511 0.386333 0.324953 \n",
"3982 ripple XRP XRP 2018-11-26 2 0.375553 0.388696 0.342019 \n",
"3983 ripple XRP XRP 2018-11-27 2 0.353977 0.367645 0.342991 \n",
"3984 ripple XRP XRP 2018-11-28 2 0.360313 0.401583 0.360313 \n",
"3985 ripple XRP XRP 2018-11-29 2 0.391862 0.392465 0.373789 \n",
"\n",
" close volume market close_ratio spread row_id \\\n",
"2042 0.005882 0.000000e+00 4.598358e+07 0.1509 0.00 2043 \n",
"2043 0.005613 0.000000e+00 4.387916e+07 0.0000 0.00 2044 \n",
"2044 0.004680 0.000000e+00 3.659101e+07 0.0494 0.00 2045 \n",
"2045 0.004417 0.000000e+00 3.453412e+07 0.2407 0.00 2046 \n",
"2046 0.004254 0.000000e+00 3.325863e+07 0.3173 0.00 2047 \n",
"... ... ... ... ... ... ... \n",
"3981 0.374551 1.296590e+09 1.510465e+10 0.8080 0.06 3982 \n",
"3982 0.355451 1.032000e+09 1.433439e+10 0.2878 0.05 3983 \n",
"3983 0.360163 6.001690e+08 1.452442e+10 0.6965 0.02 3984 \n",
"3984 0.390557 7.748180e+08 1.575013e+10 0.7328 0.04 3985 \n",
"3985 0.379562 6.299006e+08 1.530674e+10 0.3091 0.02 3986 \n",
"\n",
" market_billion volume_million volume_billion \n",
"2042 0.045984 0.000000 0.000000e+00 \n",
"2043 0.043879 0.000000 0.000000e+00 \n",
"2044 0.036591 0.000000 0.000000e+00 \n",
"2045 0.034534 0.000000 0.000000e+00 \n",
"2046 0.033259 0.000000 0.000000e+00 \n",
"... ... ... ... \n",
"3981 15.104646 1.296590 1.296590e+09 \n",
"3982 14.334394 1.032000 1.032000e+09 \n",
"3983 14.524416 0.600169 6.001690e+08 \n",
"3984 15.750126 0.774818 7.748180e+08 \n",
"3985 15.306739 0.629901 6.299006e+08 \n",
"\n",
"[1944 rows x 17 columns]\n"
]
}
],
"source": [
"print(df2)"
]
},
{
"cell_type": "code",
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{
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"data": {
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" slug symbol name date ranknow open high low \\\n",
"2042 ripple XRP XRP 2013-08-04 2 0.005874 0.005927 0.005874 \n",
"2043 ripple XRP XRP 2013-08-05 2 0.005875 0.005980 0.005613 \n",
"2044 ripple XRP XRP 2013-08-06 2 0.005637 0.005661 0.004629 \n",
"2045 ripple XRP XRP 2013-08-07 2 0.004669 0.004682 0.004333 \n",
"2046 ripple XRP XRP 2013-08-08 2 0.004397 0.004424 0.004175 \n",
"\n",
" close volume market close_ratio spread row_id \\\n",
"2042 0.005882 0.0 45983577.0 0.1509 0.0 2043 \n",
"2043 0.005613 0.0 43879157.0 0.0000 0.0 2044 \n",
"2044 0.004680 0.0 36591008.0 0.0494 0.0 2045 \n",
"2045 0.004417 0.0 34534121.0 0.2407 0.0 2046 \n",
"2046 0.004254 0.0 33258632.0 0.3173 0.0 2047 \n",
"\n",
" market_billion volume_million volume_billion \n",
"2042 0.045984 0.0 0.0 \n",
"2043 0.043879 0.0 0.0 \n",
"2044 0.036591 0.0 0.0 \n",
"2045 0.034534 0.0 0.0 \n",
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],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "df2",
"repr_error": "0"
}
},
"metadata": {},
"execution_count": 57
}
],
"source": [
"df2.head()"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "bOfzu0IhJByk",
"outputId": "51edaece-2898-4bb1-80f7-68b573e28eee"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" open high low close volume\n",
"2042 0.005874 0.005927 0.005874 0.005882 0.0\n",
"2043 0.005875 0.005980 0.005613 0.005613 0.0\n",
"2044 0.005637 0.005661 0.004629 0.004680 0.0\n",
"2045 0.004669 0.004682 0.004333 0.004417 0.0\n",
"2046 0.004397 0.004424 0.004175 0.004254 0.0\n",
"(1944, 5)\n"
]
}
],
"source": [
"d2 = df2.iloc[:, 5:10]\n",
"print(d2.head())\n",
"print(d2.shape)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 590
},
"id": "hSNYPEm7JByk",
"outputId": "87f7454e-1129-4442-e3ff-6fa4815da193"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Price of Ripple')"
]
},
"metadata": {},
"execution_count": 64
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"plt.figure(figsize=(12,6))\n",
"sns.lineplot(x=d2.index, y=\"open\", data=d2).set_title(\"Price of Ripple\")"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "pcllm_j2JByk",
"outputId": "699ff576-1ead-4ec5-c418-d0fa13bf265f"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2042 0.005874\n",
"2043 0.005875\n",
"2044 0.005637\n",
"2045 0.004669\n",
"2046 0.004397\n",
" ... \n",
"3981 0.374511\n",
"3982 0.375553\n",
"3983 0.353977\n",
"3984 0.360313\n",
"3985 0.391862\n",
"Name: open, Length: 1944, dtype: float64\n"
]
}
],
"source": [
"data = d2.iloc[:, 0]\n",
"\n",
"print(data)"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {
"id": "JoAgH76ZLPjI"
},
"outputs": [],
"source": [
"hist = []\n",
"target = []\n",
"length = 90\n",
"for i in range(2042,len(data)-length):\n",
" x = data[2042:i+length]\n",
" y = data[i+length]\n",
" hist.append(x)\n",
" target.append(y)"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {
"id": "jGSDstNAJByl"
},
"outputs": [],
"source": [
"hist = np.array(hist)\n",
"target = np.array(target)\n",
"target = target.reshape(-1,1)"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {
"id": "FpugPkG9NAtl"
},
"outputs": [],
"source": [
"hist = hist.reshape(-1,1)"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {
"id": "icGR5bLNJByl"
},
"outputs": [],
"source": [
"import numpy as np\n",
"from sklearn.preprocessing import MinMaxScaler\n",
"\n",
"hist = []\n",
"target = []\n",
"length = 90\n",
"\n",
"# Get the starting index of the data\n",
"start_index = data.index.min()\n",
"\n",
"# Iterate through the data, ensuring you stay within the valid index range\n",
"for i in range(len(data) - length):\n",
" # Use iloc to access by position, as the index may not be consecutive integers\n",
" x = data.iloc[i : i + length]\n",
" y = data.iloc[i + length]\n",
" hist.append(x.values) # Store values as numpy array\n",
" target.append(y)\n",
"\n",
"hist = np.array(hist)\n",
"target = np.array(target)\n",
"target = target.reshape(-1, 1)\n",
"\n",
"# Reshape hist\n",
"hist = hist.reshape(hist.shape[0], -1)\n",
"\n",
"sc = MinMaxScaler"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "AXyWLswgJByl",
"outputId": "7a3367fe-13d3-4357-8401-8befd5aa3847"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(1952, 90, 1)\n"
]
}
],
"source": [
"hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
"print(hist_scaled.shape)"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {
"id": "j9I5SQkPJByl"
},
"outputs": [],
"source": [
"X_train = hist_scaled[:1900,:,:]\n",
"X_test = hist_scaled[1900:,:,:]\n",
"y_train = target_scaled[:1900,:]\n",
"y_test = target_scaled[1900:,:]"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {
"id": "wMmrZ7hFJByl"
},
"outputs": [],
"source": [
"import tensorflow as tf\n",
"from tensorflow.keras import layers"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 272
},
"id": "Tfb5_8l6JByl",
"outputId": "5a05c245-68b9-4ef3-ccba-aeb6db9442a6"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1mModel: \"sequential_1\"\u001b[0m\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_1\"</span>\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm_3 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m4,352\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_4 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_5 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense_1 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m) │ \u001b[38;5;34m33\u001b[0m │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃<span style=\"font-weight: bold\"> Layer (type) </span>┃<span style=\"font-weight: bold\"> Output Shape </span>┃<span style=\"font-weight: bold\"> Param # </span>┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">4,352</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_5 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span> │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
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"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
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"metadata": {}
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"text/plain": [
"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
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"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
"</pre>\n"
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"metadata": {}
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],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" input_shape=(90,1), dropout=0.2))\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" dropout=0.2))\n",
"model.add(layers.LSTM(units=32, dropout=0.2))\n",
"model.add(layers.Dense(units=1))\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {
"id": "XblbdTVWJByl"
},
"outputs": [],
"source": [
"model.compile(optimizer='adam', loss='mean_squared_error')"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "wCu3FeoiJBym",
"outputId": "f1c6c5a9-d594-49be-9643-3a75fbccb060"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 1/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 99ms/step - loss: 0.0197\n",
"Epoch 2/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 111ms/step - loss: 0.0088\n",
"Epoch 3/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 106ms/step - loss: 0.0098\n",
"Epoch 4/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 128ms/step - loss: 0.0103\n",
"Epoch 5/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 99ms/step - loss: 0.0096\n",
"Epoch 6/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 123ms/step - loss: 0.0083\n",
"Epoch 7/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 117ms/step - loss: 0.0078\n",
"Epoch 8/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 96ms/step - loss: 0.0084\n",
"Epoch 9/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0100\n",
"Epoch 10/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 119ms/step - loss: 0.0080\n",
"Epoch 11/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 96ms/step - loss: 0.0078\n",
"Epoch 12/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 95ms/step - loss: 0.0110\n",
"Epoch 13/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 119ms/step - loss: 0.0081\n",
"Epoch 14/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 95ms/step - loss: 0.0096\n",
"Epoch 15/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0086\n",
"Epoch 16/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 119ms/step - loss: 0.0105\n",
"Epoch 17/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 95ms/step - loss: 0.0091\n",
"Epoch 18/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 128ms/step - loss: 0.0085\n",
"Epoch 19/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 100ms/step - loss: 0.0077\n",
"Epoch 20/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0117\n",
"Epoch 21/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0086\n",
"Epoch 22/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 137ms/step - loss: 0.0084\n",
"Epoch 23/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 119ms/step - loss: 0.0072\n",
"Epoch 24/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 113ms/step - loss: 0.0121\n",
"Epoch 25/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 99ms/step - loss: 0.0070\n",
"Epoch 26/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 123ms/step - loss: 0.0070\n",
"Epoch 27/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 97ms/step - loss: 0.0094\n",
"Epoch 28/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 129ms/step - loss: 0.0086\n",
"Epoch 29/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 101ms/step - loss: 0.0070\n",
"Epoch 30/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0076\n"
]
}
],
"source": [
"history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 720
},
"id": "jqnFts9HJBym",
"outputId": "ade7c445-6351-4c8e-e480-64b9fd3f059d"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[1m2/2\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 495ms/step\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x800 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"pred = model.predict(X_test)\n",
"plt.figure(figsize=(12,8))\n",
"plt.plot(y_test, color='blue', label='Real')\n",
"plt.plot(pred, color='red', label='Prediction')\n",
"plt.title('Ripple Price Prediction')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "HVw69BHsP-SH"
},
"source": [
"#Ethereum"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "6Gf_B5zeP-SI",
"outputId": "05c5ce7f-ce25-4b9e-f658-2cda6bf17082"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(1211, 17)"
]
},
"metadata": {},
"execution_count": 80
}
],
"source": [
"#bitcoin\n",
"df3 = data_top_6_currencies[data_top_6_currencies['slug']=='ethereum']\n",
"\n",
"df3.shape"
]
},
{
"cell_type": "code",
"execution_count": 81,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "wTrWsHkZP-SI",
"outputId": "9ea81312-eea8-4816-85ac-a49fc75098f6"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" slug symbol name date ranknow open high \\\n",
"3986 ethereum ETH Ethereum 2015-08-07 3 2.830000 3.540000 \n",
"3987 ethereum ETH Ethereum 2015-08-08 3 2.790000 2.800000 \n",
"3988 ethereum ETH Ethereum 2015-08-09 3 0.706136 0.879810 \n",
"3989 ethereum ETH Ethereum 2015-08-10 3 0.713989 0.729854 \n",
"3990 ethereum ETH Ethereum 2015-08-11 3 0.708087 1.130000 \n",
"... ... ... ... ... ... ... ... \n",
"5192 ethereum ETH Ethereum 2018-11-25 3 113.130000 118.880000 \n",
"5193 ethereum ETH Ethereum 2018-11-26 3 116.340000 118.200000 \n",
"5194 ethereum ETH Ethereum 2018-11-27 3 107.910000 111.840000 \n",
"5195 ethereum ETH Ethereum 2018-11-28 3 110.200000 126.050000 \n",
"5196 ethereum ETH Ethereum 2018-11-29 3 122.720000 123.230000 \n",
"\n",
" low close volume market close_ratio spread \\\n",
"3986 2.520000 2.770000 1.643290e+05 1.666106e+08 0.2451 1.02 \n",
"3987 0.714725 0.753325 6.741880e+05 4.548689e+07 0.0185 2.09 \n",
"3988 0.629191 0.701897 5.321700e+05 4.239957e+07 0.2901 0.25 \n",
"3989 0.636546 0.708448 4.052830e+05 4.281836e+07 0.7706 0.09 \n",
"3990 0.663235 1.070000 1.463100e+06 6.456929e+07 0.8715 0.47 \n",
"... ... ... ... ... ... ... \n",
"5192 101.770000 116.450000 2.466750e+09 1.204390e+10 0.8580 17.11 \n",
"5193 104.890000 108.330000 2.139490e+09 1.120678e+10 0.2585 13.31 \n",
"5194 102.450000 110.010000 2.320010e+09 1.138222e+10 0.8051 9.39 \n",
"5195 110.200000 122.440000 2.673470e+09 1.267049e+10 0.7722 15.85 \n",
"5196 115.300000 117.540000 2.196099e+09 1.216629e+10 0.2825 7.93 \n",
"\n",
" row_id market_billion volume_million volume_billion \n",
"3986 3987 0.166611 0.000164 1.643290e+05 \n",
"3987 3988 0.045487 0.000674 6.741880e+05 \n",
"3988 3989 0.042400 0.000532 5.321700e+05 \n",
"3989 3990 0.042818 0.000405 4.052830e+05 \n",
"3990 3991 0.064569 0.001463 1.463100e+06 \n",
"... ... ... ... ... \n",
"5192 5193 12.043901 2.466750 2.466750e+09 \n",
"5193 5194 11.206775 2.139490 2.139490e+09 \n",
"5194 5195 11.382217 2.320010 2.320010e+09 \n",
"5195 5196 12.670491 2.673470 2.673470e+09 \n",
"5196 5197 12.166286 2.196099 2.196099e+09 \n",
"\n",
"[1211 rows x 17 columns]\n"
]
}
],
"source": [
"print(df3)"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 313
},
"id": "zsvIQYO3P-SI",
"outputId": "ef321f2a-255f-4534-8d99-c3b9798e7ab4"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" slug symbol name date ranknow open high \\\n",
"3986 ethereum ETH Ethereum 2015-08-07 3 2.830000 3.540000 \n",
"3987 ethereum ETH Ethereum 2015-08-08 3 2.790000 2.800000 \n",
"3988 ethereum ETH Ethereum 2015-08-09 3 0.706136 0.879810 \n",
"3989 ethereum ETH Ethereum 2015-08-10 3 0.713989 0.729854 \n",
"3990 ethereum ETH Ethereum 2015-08-11 3 0.708087 1.130000 \n",
"\n",
" low close volume market close_ratio spread row_id \\\n",
"3986 2.520000 2.770000 164329.0 166610555.0 0.2451 1.02 3987 \n",
"3987 0.714725 0.753325 674188.0 45486894.0 0.0185 2.09 3988 \n",
"3988 0.629191 0.701897 532170.0 42399573.0 0.2901 0.25 3989 \n",
"3989 0.636546 0.708448 405283.0 42818364.0 0.7706 0.09 3990 \n",
"3990 0.663235 1.070000 1463100.0 64569288.0 0.8715 0.47 3991 \n",
"\n",
" market_billion volume_million volume_billion \n",
"3986 0.166611 0.000164 164329.0 \n",
"3987 0.045487 0.000674 674188.0 \n",
"3988 0.042400 0.000532 532170.0 \n",
"3989 0.042818 0.000405 405283.0 \n",
"3990 0.064569 0.001463 1463100.0 "
],
"text/html": [
"\n",
" <div id=\"df-5da10ba2-9176-4dde-8600-a12832ccfe46\" class=\"colab-df-container\">\n",
" <div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>slug</th>\n",
" <th>symbol</th>\n",
" <th>name</th>\n",
" <th>date</th>\n",
" <th>ranknow</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" <th>market</th>\n",
" <th>close_ratio</th>\n",
" <th>spread</th>\n",
" <th>row_id</th>\n",
" <th>market_billion</th>\n",
" <th>volume_million</th>\n",
" <th>volume_billion</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>3986</th>\n",
" <td>ethereum</td>\n",
" <td>ETH</td>\n",
" <td>Ethereum</td>\n",
" <td>2015-08-07</td>\n",
" <td>3</td>\n",
" <td>2.830000</td>\n",
" <td>3.540000</td>\n",
" <td>2.520000</td>\n",
" <td>2.770000</td>\n",
" <td>164329.0</td>\n",
" <td>166610555.0</td>\n",
" <td>0.2451</td>\n",
" <td>1.02</td>\n",
" <td>3987</td>\n",
" <td>0.166611</td>\n",
" <td>0.000164</td>\n",
" <td>164329.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3987</th>\n",
" <td>ethereum</td>\n",
" <td>ETH</td>\n",
" <td>Ethereum</td>\n",
" <td>2015-08-08</td>\n",
" <td>3</td>\n",
" <td>2.790000</td>\n",
" <td>2.800000</td>\n",
" <td>0.714725</td>\n",
" <td>0.753325</td>\n",
" <td>674188.0</td>\n",
" <td>45486894.0</td>\n",
" <td>0.0185</td>\n",
" <td>2.09</td>\n",
" <td>3988</td>\n",
" <td>0.045487</td>\n",
" <td>0.000674</td>\n",
" <td>674188.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3988</th>\n",
" <td>ethereum</td>\n",
" <td>ETH</td>\n",
" <td>Ethereum</td>\n",
" <td>2015-08-09</td>\n",
" <td>3</td>\n",
" <td>0.706136</td>\n",
" <td>0.879810</td>\n",
" <td>0.629191</td>\n",
" <td>0.701897</td>\n",
" <td>532170.0</td>\n",
" <td>42399573.0</td>\n",
" <td>0.2901</td>\n",
" <td>0.25</td>\n",
" <td>3989</td>\n",
" <td>0.042400</td>\n",
" <td>0.000532</td>\n",
" <td>532170.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3989</th>\n",
" <td>ethereum</td>\n",
" <td>ETH</td>\n",
" <td>Ethereum</td>\n",
" <td>2015-08-10</td>\n",
" <td>3</td>\n",
" <td>0.713989</td>\n",
" <td>0.729854</td>\n",
" <td>0.636546</td>\n",
" <td>0.708448</td>\n",
" <td>405283.0</td>\n",
" <td>42818364.0</td>\n",
" <td>0.7706</td>\n",
" <td>0.09</td>\n",
" <td>3990</td>\n",
" <td>0.042818</td>\n",
" <td>0.000405</td>\n",
" <td>405283.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3990</th>\n",
" <td>ethereum</td>\n",
" <td>ETH</td>\n",
" <td>Ethereum</td>\n",
" <td>2015-08-11</td>\n",
" <td>3</td>\n",
" <td>0.708087</td>\n",
" <td>1.130000</td>\n",
" <td>0.663235</td>\n",
" <td>1.070000</td>\n",
" <td>1463100.0</td>\n",
" <td>64569288.0</td>\n",
" <td>0.8715</td>\n",
" <td>0.47</td>\n",
" <td>3991</td>\n",
" <td>0.064569</td>\n",
" <td>0.001463</td>\n",
" <td>1463100.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <div class=\"colab-df-buttons\">\n",
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" </svg>\n",
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"\n",
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" .colab-df-container {\n",
" display:flex;\n",
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" background-color: #E8F0FE;\n",
" border: none;\n",
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" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
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"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-5da10ba2-9176-4dde-8600-a12832ccfe46 button.colab-df-convert');\n",
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" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-5da10ba2-9176-4dde-8600-a12832ccfe46');\n",
" const dataTable =\n",
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" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
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" </g>\n",
"</svg>\n",
" </button>\n",
"\n",
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" .colab-df-quickchart {\n",
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" border-bottom-color: var(--fill-color);\n",
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" @keyframes spin {\n",
" 0% {\n",
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" }\n",
" 20% {\n",
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" 30% {\n",
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" border-right-color: var(--fill-color);\n",
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" 40% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
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" 60% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" 90% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
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" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
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"</div>\n",
"\n",
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],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "df3",
"repr_error": "0"
}
},
"metadata": {},
"execution_count": 82
}
],
"source": [
"df3.head()"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "TnheAbnAP-SI",
"outputId": "421405be-aed9-405e-fe83-bf2383db4e45"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" open high low close volume\n",
"3986 2.830000 3.540000 2.520000 2.770000 164329.0\n",
"3987 2.790000 2.800000 0.714725 0.753325 674188.0\n",
"3988 0.706136 0.879810 0.629191 0.701897 532170.0\n",
"3989 0.713989 0.729854 0.636546 0.708448 405283.0\n",
"3990 0.708087 1.130000 0.663235 1.070000 1463100.0\n",
"(1211, 5)\n"
]
}
],
"source": [
"d3 = df3.iloc[:, 5:10]\n",
"print(d3.head())\n",
"print(d3.shape)"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 590
},
"id": "T3xP1Eo8P-SJ",
"outputId": "2b78d76f-9df0-49bb-ebc8-d2b170c3b59a"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Price of Ethereum')"
]
},
"metadata": {},
"execution_count": 84
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"plt.figure(figsize=(12,6))\n",
"sns.lineplot(x=d3.index, y=\"open\", data=d3).set_title(\"Price of Ethereum\")"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "kbwR0m7RP-SJ",
"outputId": "7a777e15-ed4b-4239-cac8-0d3bf56a1edd"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"3986 2.830000\n",
"3987 2.790000\n",
"3988 0.706136\n",
"3989 0.713989\n",
"3990 0.708087\n",
" ... \n",
"5192 113.130000\n",
"5193 116.340000\n",
"5194 107.910000\n",
"5195 110.200000\n",
"5196 122.720000\n",
"Name: open, Length: 1211, dtype: float64\n"
]
}
],
"source": [
"data = d3.iloc[:, 0]\n",
"\n",
"print(data)"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {
"id": "KPzSexH2P-SJ"
},
"outputs": [],
"source": [
"hist = []\n",
"target = []\n",
"length = 90\n",
"for i in range(3986,len(data)-length):\n",
" x = data[3986:i+length]\n",
" y = data[i+length]\n",
" hist.append(x)\n",
" target.append(y)"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {
"id": "I5QVQECtP-SJ"
},
"outputs": [],
"source": [
"hist = np.array(hist)\n",
"target = np.array(target)\n",
"target = target.reshape(-1,1)"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {
"id": "rhe9sKH3P-SJ"
},
"outputs": [],
"source": [
"hist = hist.reshape(-1,1)"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "FNSDMq0mP-SK",
"outputId": "c222149f-5fbb-4ffb-a03f-0815d08190d9"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(1952, 90, 1)\n"
]
}
],
"source": [
"hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
"print(hist_scaled.shape)"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {
"id": "bBrwRQLsP-SK"
},
"outputs": [],
"source": [
"X_train = hist_scaled[:1900,:,:]\n",
"X_test = hist_scaled[1900:,:,:]\n",
"y_train = target_scaled[:1900,:]\n",
"y_test = target_scaled[1900:,:]"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {
"id": "zvGPHlb2P-SK"
},
"outputs": [],
"source": [
"import tensorflow as tf\n",
"from tensorflow.keras import layers"
]
},
{
"cell_type": "code",
"execution_count": 92,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 272
},
"id": "aWFjURq-P-SK",
"outputId": "8b8343e2-87b2-4482-964f-16aa94f1bba9"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1mModel: \"sequential_2\"\u001b[0m\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_2\"</span>\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm_6 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m4,352\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_7 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_8 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense_2 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m) │ \u001b[38;5;34m33\u001b[0m │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃<span style=\"font-weight: bold\"> Layer (type) </span>┃<span style=\"font-weight: bold\"> Output Shape </span>┃<span style=\"font-weight: bold\"> Param # </span>┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">4,352</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_7 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_8 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span> │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
"</pre>\n"
]
},
"metadata": {}
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" input_shape=(90,1), dropout=0.2))\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" dropout=0.2))\n",
"model.add(layers.LSTM(units=32, dropout=0.2))\n",
"model.add(layers.Dense(units=1))\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {
"id": "gcUc1ZBHP-SK"
},
"outputs": [],
"source": [
"model.compile(optimizer='adam', loss='mean_squared_error')"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ZfAB0JWTP-SK",
"outputId": "db6822b6-be09-4a76-fa80-cfd7939f4fe7"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 1/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 127ms/step - loss: 0.0218\n",
"Epoch 2/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 99ms/step - loss: 0.0091\n",
"Epoch 3/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0105\n",
"Epoch 4/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 97ms/step - loss: 0.0101\n",
"Epoch 5/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 121ms/step - loss: 0.0087\n",
"Epoch 6/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 97ms/step - loss: 0.0100\n",
"Epoch 7/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0085\n",
"Epoch 8/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 127ms/step - loss: 0.0089\n",
"Epoch 9/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 96ms/step - loss: 0.0105\n",
"Epoch 10/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 113ms/step - loss: 0.0080\n",
"Epoch 11/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 128ms/step - loss: 0.0093\n",
"Epoch 12/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 97ms/step - loss: 0.0087\n",
"Epoch 13/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0097\n",
"Epoch 14/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 131ms/step - loss: 0.0089\n",
"Epoch 15/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 97ms/step - loss: 0.0101\n",
"Epoch 16/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 121ms/step - loss: 0.0068\n",
"Epoch 17/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 96ms/step - loss: 0.0072\n",
"Epoch 18/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 128ms/step - loss: 0.0114\n",
"Epoch 19/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 105ms/step - loss: 0.0078\n",
"Epoch 20/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0097\n",
"Epoch 21/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 127ms/step - loss: 0.0086\n",
"Epoch 22/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 97ms/step - loss: 0.0099\n",
"Epoch 23/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 102ms/step - loss: 0.0087\n",
"Epoch 24/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 125ms/step - loss: 0.0090\n",
"Epoch 25/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 106ms/step - loss: 0.0077\n",
"Epoch 26/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 115ms/step - loss: 0.0096\n",
"Epoch 27/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 125ms/step - loss: 0.0080\n",
"Epoch 28/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 96ms/step - loss: 0.0130\n",
"Epoch 29/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0067\n",
"Epoch 30/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 128ms/step - loss: 0.0089\n"
]
}
],
"source": [
"history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 704
},
"id": "DT2SuvDdP-SK",
"outputId": "8ac5e27e-4521-400a-8df3-4af7f792d9b1"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x800 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"loss = history.history['loss']\n",
"epoch_count = range(1, len(loss) + 1)\n",
"plt.figure(figsize=(12,8))\n",
"plt.plot(epoch_count, loss, 'r--')\n",
"plt.legend(['Training Loss'])\n",
"plt.xlabel('Epoch')\n",
"plt.ylabel('Loss')\n",
"plt.show();"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 775
},
"id": "eArbMF4TP-SL",
"outputId": "47aef989-1839-4a53-ce6c-012973feb307"
},
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"WARNING:tensorflow:5 out of the last 5 calls to <function TensorFlowTrainer.make_predict_function.<locals>.one_step_on_data_distributed at 0x787955c40280> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\r\u001b[1m1/2\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 513ms/step"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"WARNING:tensorflow:6 out of the last 6 calls to <function TensorFlowTrainer.make_predict_function.<locals>.one_step_on_data_distributed at 0x787955c40280> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[1m2/2\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 484ms/step\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x800 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"pred = model.predict(X_test)\n",
"plt.figure(figsize=(12,8))\n",
"plt.plot(y_test, color='blue', label='Real')\n",
"plt.plot(pred, color='red', label='Prediction')\n",
"plt.title('Ethereum Price Prediction')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "k4_p4ZjbUJWo"
},
"source": [
"#Bitcoin Cash (BCH)"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "O4H46vFAUJWo",
"outputId": "cabb32eb-5236-4ab1-b051-79f16b4481f0"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(495, 17)"
]
},
"metadata": {},
"execution_count": 97
}
],
"source": [
"\n",
"df4 = data_top_6_currencies[data_top_6_currencies['symbol']=='BCH']\n",
"\n",
"df4.shape"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "5-4itcj_UJWo",
"outputId": "3a45f0c0-0f63-4bf8-d7ae-2510e333b547"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" slug symbol name date ranknow open high \\\n",
"6775 bitcoin-cash BCH Bitcoin Cash 2017-07-23 5 555.89 578.97 \n",
"6776 bitcoin-cash BCH Bitcoin Cash 2017-07-24 5 412.58 578.89 \n",
"6777 bitcoin-cash BCH Bitcoin Cash 2017-07-25 5 441.35 541.66 \n",
"6778 bitcoin-cash BCH Bitcoin Cash 2017-07-26 5 407.08 486.16 \n",
"6779 bitcoin-cash BCH Bitcoin Cash 2017-07-27 5 417.10 460.97 \n",
"... ... ... ... ... ... ... ... \n",
"7265 bitcoin-cash BCH Bitcoin Cash 2018-11-25 5 181.13 189.25 \n",
"7266 bitcoin-cash BCH Bitcoin Cash 2018-11-26 5 184.83 215.77 \n",
"7267 bitcoin-cash BCH Bitcoin Cash 2018-11-27 5 182.00 192.99 \n",
"7268 bitcoin-cash BCH Bitcoin Cash 2018-11-28 5 179.14 198.55 \n",
"7269 bitcoin-cash BCH Bitcoin Cash 2018-11-29 5 190.10 191.15 \n",
"\n",
" low close volume market close_ratio spread row_id \\\n",
"6775 411.78 413.06 85013.0 0.000000e+00 0.0077 167.19 6776 \n",
"6776 409.21 440.70 190952.0 0.000000e+00 0.1856 169.68 6777 \n",
"6777 338.09 406.90 524908.0 0.000000e+00 0.3380 203.57 6778 \n",
"6778 321.79 365.82 1784640.0 0.000000e+00 0.2679 164.37 6779 \n",
"6779 367.78 385.48 533207.0 0.000000e+00 0.1899 93.19 6780 \n",
"... ... ... ... ... ... ... ... \n",
"7265 154.28 184.58 164581000.0 3.226002e+09 0.8665 34.97 7266 \n",
"7266 170.62 182.04 283429000.0 3.181916e+09 0.2529 45.15 7267 \n",
"7267 171.22 179.06 136514000.0 3.130144e+09 0.3601 21.77 7268 \n",
"7268 176.36 190.07 127871000.0 3.322936e+09 0.6178 22.19 7269 \n",
"7269 176.83 180.98 89166901.0 3.164359e+09 0.2898 14.32 7270 \n",
"\n",
" market_billion volume_million volume_billion \n",
"6775 0.000000 0.000085 85013.0 \n",
"6776 0.000000 0.000191 190952.0 \n",
"6777 0.000000 0.000525 524908.0 \n",
"6778 0.000000 0.001785 1784640.0 \n",
"6779 0.000000 0.000533 533207.0 \n",
"... ... ... ... \n",
"7265 3.226002 0.164581 164581000.0 \n",
"7266 3.181916 0.283429 283429000.0 \n",
"7267 3.130144 0.136514 136514000.0 \n",
"7268 3.322936 0.127871 127871000.0 \n",
"7269 3.164359 0.089167 89166901.0 \n",
"\n",
"[495 rows x 17 columns]\n"
]
}
],
"source": [
"print(df4)"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 313
},
"id": "mn_n52xrUJWo",
"outputId": "ee6a6a96-3869-4ea3-a3f2-7fefeb51bd3c"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" slug symbol name date ranknow open high \\\n",
"6775 bitcoin-cash BCH Bitcoin Cash 2017-07-23 5 555.89 578.97 \n",
"6776 bitcoin-cash BCH Bitcoin Cash 2017-07-24 5 412.58 578.89 \n",
"6777 bitcoin-cash BCH Bitcoin Cash 2017-07-25 5 441.35 541.66 \n",
"6778 bitcoin-cash BCH Bitcoin Cash 2017-07-26 5 407.08 486.16 \n",
"6779 bitcoin-cash BCH Bitcoin Cash 2017-07-27 5 417.10 460.97 \n",
"\n",
" low close volume market close_ratio spread row_id \\\n",
"6775 411.78 413.06 85013.0 0.0 0.0077 167.19 6776 \n",
"6776 409.21 440.70 190952.0 0.0 0.1856 169.68 6777 \n",
"6777 338.09 406.90 524908.0 0.0 0.3380 203.57 6778 \n",
"6778 321.79 365.82 1784640.0 0.0 0.2679 164.37 6779 \n",
"6779 367.78 385.48 533207.0 0.0 0.1899 93.19 6780 \n",
"\n",
" market_billion volume_million volume_billion \n",
"6775 0.0 0.000085 85013.0 \n",
"6776 0.0 0.000191 190952.0 \n",
"6777 0.0 0.000525 524908.0 \n",
"6778 0.0 0.001785 1784640.0 \n",
"6779 0.0 0.000533 533207.0 "
],
"text/html": [
"\n",
" <div id=\"df-5b4a4917-179a-4d33-8b59-bb104abbb1e1\" class=\"colab-df-container\">\n",
" <div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>slug</th>\n",
" <th>symbol</th>\n",
" <th>name</th>\n",
" <th>date</th>\n",
" <th>ranknow</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" <th>market</th>\n",
" <th>close_ratio</th>\n",
" <th>spread</th>\n",
" <th>row_id</th>\n",
" <th>market_billion</th>\n",
" <th>volume_million</th>\n",
" <th>volume_billion</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>6775</th>\n",
" <td>bitcoin-cash</td>\n",
" <td>BCH</td>\n",
" <td>Bitcoin Cash</td>\n",
" <td>2017-07-23</td>\n",
" <td>5</td>\n",
" <td>555.89</td>\n",
" <td>578.97</td>\n",
" <td>411.78</td>\n",
" <td>413.06</td>\n",
" <td>85013.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0077</td>\n",
" <td>167.19</td>\n",
" <td>6776</td>\n",
" <td>0.0</td>\n",
" <td>0.000085</td>\n",
" <td>85013.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6776</th>\n",
" <td>bitcoin-cash</td>\n",
" <td>BCH</td>\n",
" <td>Bitcoin Cash</td>\n",
" <td>2017-07-24</td>\n",
" <td>5</td>\n",
" <td>412.58</td>\n",
" <td>578.89</td>\n",
" <td>409.21</td>\n",
" <td>440.70</td>\n",
" <td>190952.0</td>\n",
" <td>0.0</td>\n",
" <td>0.1856</td>\n",
" <td>169.68</td>\n",
" <td>6777</td>\n",
" <td>0.0</td>\n",
" <td>0.000191</td>\n",
" <td>190952.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6777</th>\n",
" <td>bitcoin-cash</td>\n",
" <td>BCH</td>\n",
" <td>Bitcoin Cash</td>\n",
" <td>2017-07-25</td>\n",
" <td>5</td>\n",
" <td>441.35</td>\n",
" <td>541.66</td>\n",
" <td>338.09</td>\n",
" <td>406.90</td>\n",
" <td>524908.0</td>\n",
" <td>0.0</td>\n",
" <td>0.3380</td>\n",
" <td>203.57</td>\n",
" <td>6778</td>\n",
" <td>0.0</td>\n",
" <td>0.000525</td>\n",
" <td>524908.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6778</th>\n",
" <td>bitcoin-cash</td>\n",
" <td>BCH</td>\n",
" <td>Bitcoin Cash</td>\n",
" <td>2017-07-26</td>\n",
" <td>5</td>\n",
" <td>407.08</td>\n",
" <td>486.16</td>\n",
" <td>321.79</td>\n",
" <td>365.82</td>\n",
" <td>1784640.0</td>\n",
" <td>0.0</td>\n",
" <td>0.2679</td>\n",
" <td>164.37</td>\n",
" <td>6779</td>\n",
" <td>0.0</td>\n",
" <td>0.001785</td>\n",
" <td>1784640.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6779</th>\n",
" <td>bitcoin-cash</td>\n",
" <td>BCH</td>\n",
" <td>Bitcoin Cash</td>\n",
" <td>2017-07-27</td>\n",
" <td>5</td>\n",
" <td>417.10</td>\n",
" <td>460.97</td>\n",
" <td>367.78</td>\n",
" <td>385.48</td>\n",
" <td>533207.0</td>\n",
" <td>0.0</td>\n",
" <td>0.1899</td>\n",
" <td>93.19</td>\n",
" <td>6780</td>\n",
" <td>0.0</td>\n",
" <td>0.000533</td>\n",
" <td>533207.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <div class=\"colab-df-buttons\">\n",
"\n",
" <div class=\"colab-df-container\">\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5b4a4917-179a-4d33-8b59-bb104abbb1e1')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
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"\n",
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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" </svg>\n",
" </button>\n",
"\n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" gap: 12px;\n",
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"\n",
" .colab-df-convert {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
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"\n",
" .colab-df-buttons div {\n",
" margin-bottom: 4px;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
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"\n",
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" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-5b4a4917-179a-4d33-8b59-bb104abbb1e1 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-5b4a4917-179a-4d33-8b59-bb104abbb1e1');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
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"\n",
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"<div id=\"df-a1235833-b036-4a9c-ba2f-5d602e08363f\">\n",
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" title=\"Suggest charts\"\n",
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" </g>\n",
"</svg>\n",
" </button>\n",
"\n",
"<style>\n",
" .colab-df-quickchart {\n",
" --bg-color: #E8F0FE;\n",
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" --hover-bg-color: #E2EBFA;\n",
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" [theme=dark] .colab-df-quickchart {\n",
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" --disabled-fill-color: #666;\n",
" }\n",
"\n",
" .colab-df-quickchart {\n",
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" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
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" fill: var(--fill-color);\n",
" height: 32px;\n",
" padding: 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-quickchart:hover {\n",
" background-color: var(--hover-bg-color);\n",
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: var(--button-hover-fill-color);\n",
" }\n",
"\n",
" .colab-df-quickchart-complete:disabled,\n",
" .colab-df-quickchart-complete:disabled:hover {\n",
" background-color: var(--disabled-bg-color);\n",
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" box-shadow: none;\n",
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"\n",
" .colab-df-spinner {\n",
" border: 2px solid var(--fill-color);\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" animation:\n",
" spin 1s steps(1) infinite;\n",
" }\n",
"\n",
" @keyframes spin {\n",
" 0% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" border-left-color: var(--fill-color);\n",
" }\n",
" 20% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 30% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 40% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 60% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" 90% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
" console.error('Error during call to suggestCharts:', error);\n",
" }\n",
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
" }\n",
" (() => {\n",
" let quickchartButtonEl =\n",
" document.querySelector('#df-a1235833-b036-4a9c-ba2f-5d602e08363f button');\n",
" quickchartButtonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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"</div>\n",
"\n",
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],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "df4",
"repr_error": "0"
}
},
"metadata": {},
"execution_count": 99
}
],
"source": [
"df4.head()"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "lNOi437hUJWp",
"outputId": "6d6a74ab-1e42-4caf-ead2-7ad72574f9b7"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" open high low close volume\n",
"6775 555.89 578.97 411.78 413.06 85013.0\n",
"6776 412.58 578.89 409.21 440.70 190952.0\n",
"6777 441.35 541.66 338.09 406.90 524908.0\n",
"6778 407.08 486.16 321.79 365.82 1784640.0\n",
"6779 417.10 460.97 367.78 385.48 533207.0\n",
"(495, 5)\n"
]
}
],
"source": [
"d4 = df4.iloc[:, 5:10]\n",
"print(d4.head())\n",
"print(d4.shape)"
]
},
{
"cell_type": "code",
"execution_count": 101,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 590
},
"id": "WHrBesaXUJWp",
"outputId": "2bd34026-c468-4c40-c5b9-2ed66c5dff0f"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Price of Bitcoin Cash')"
]
},
"metadata": {},
"execution_count": 101
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"plt.figure(figsize=(12,6))\n",
"sns.lineplot(x=d4.index, y=\"open\", data=d4).set_title(\"Price of Bitcoin Cash\")"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "YIlXzSaUUJWp",
"outputId": "eecc0588-7f4c-4fb2-9bd7-19b941d92433"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"6775 555.89\n",
"6776 412.58\n",
"6777 441.35\n",
"6778 407.08\n",
"6779 417.10\n",
" ... \n",
"7265 181.13\n",
"7266 184.83\n",
"7267 182.00\n",
"7268 179.14\n",
"7269 190.10\n",
"Name: open, Length: 495, dtype: float64\n"
]
}
],
"source": [
"data = d4.iloc[:, 0]\n",
"\n",
"print(data)"
]
},
{
"cell_type": "code",
"execution_count": 103,
"metadata": {
"id": "sZeAotUnUJWp"
},
"outputs": [],
"source": [
"hist = []\n",
"target = []\n",
"length = 90\n",
"for i in range(6775,len(data)-length):\n",
" x = data[6775:i+length]\n",
" y = data[i+length]\n",
" hist.append(x)\n",
" target.append(y)"
]
},
{
"cell_type": "code",
"execution_count": 104,
"metadata": {
"id": "SBJAZqjGUJWp"
},
"outputs": [],
"source": [
"hist = np.array(hist)\n",
"target = np.array(target)\n",
"target = target.reshape(-1,1)"
]
},
{
"cell_type": "code",
"execution_count": 105,
"metadata": {
"id": "jLGddq22UJWp"
},
"outputs": [],
"source": [
"hist = hist.reshape(1,-1)"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "hC4XeVpMUJWq",
"outputId": "05677558-1a58-4b16-c4c2-729c1b29fdaf"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(1952, 90, 1)\n"
]
}
],
"source": [
"hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
"print(hist_scaled.shape)"
]
},
{
"cell_type": "code",
"execution_count": 107,
"metadata": {
"id": "xctoaT_KUJWq"
},
"outputs": [],
"source": [
"X_train = hist_scaled[:1900,:,:]\n",
"X_test = hist_scaled[1900:,:,:]\n",
"y_train = target_scaled[:1900,:]\n",
"y_test = target_scaled[1900:,:]"
]
},
{
"cell_type": "code",
"execution_count": 108,
"metadata": {
"id": "kTzfwpunUJWq"
},
"outputs": [],
"source": [
"import tensorflow as tf\n",
"from tensorflow.keras import layers"
]
},
{
"cell_type": "code",
"execution_count": 109,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 272
},
"id": "RoZrj801UJWq",
"outputId": "f468cda2-4111-4610-d2f0-981c39c86037"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1mModel: \"sequential_3\"\u001b[0m\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_3\"</span>\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm_9 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m4,352\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_10 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_11 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense_3 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m) │ \u001b[38;5;34m33\u001b[0m │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃<span style=\"font-weight: bold\"> Layer (type) </span>┃<span style=\"font-weight: bold\"> Output Shape </span>┃<span style=\"font-weight: bold\"> Param # </span>┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm_9 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">4,352</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_10 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_11 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span> │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
"</pre>\n"
]
},
"metadata": {}
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" input_shape=(90,1), dropout=0.2))\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" dropout=0.2))\n",
"model.add(layers.LSTM(units=32, dropout=0.2))\n",
"model.add(layers.Dense(units=1))\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 110,
"metadata": {
"id": "bb-ArUEIUJWq"
},
"outputs": [],
"source": [
"model.compile(optimizer='adam', loss='mean_squared_error')"
]
},
{
"cell_type": "code",
"execution_count": 111,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "bQebGMcsUJWq",
"outputId": "950b2d20-9580-4e25-fc04-6ec1e2be9a69"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 1/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m13s\u001b[0m 124ms/step - loss: 0.0234\n",
"Epoch 2/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 96ms/step - loss: 0.0096\n",
"Epoch 3/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0123\n",
"Epoch 4/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 105ms/step - loss: 0.0104\n",
"Epoch 5/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 129ms/step - loss: 0.0085\n",
"Epoch 6/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 97ms/step - loss: 0.0106\n",
"Epoch 7/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 97ms/step - loss: 0.0064\n",
"Epoch 8/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 115ms/step - loss: 0.0084\n",
"Epoch 9/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 97ms/step - loss: 0.0078\n",
"Epoch 10/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0103\n",
"Epoch 11/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 116ms/step - loss: 0.0104\n",
"Epoch 12/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 124ms/step - loss: 0.0091\n",
"Epoch 13/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 97ms/step - loss: 0.0064\n",
"Epoch 14/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 97ms/step - loss: 0.0093\n",
"Epoch 15/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 103ms/step - loss: 0.0101\n",
"Epoch 16/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 125ms/step - loss: 0.0112\n",
"Epoch 17/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 110ms/step - loss: 0.0083\n",
"Epoch 18/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 97ms/step - loss: 0.0111\n",
"Epoch 19/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 130ms/step - loss: 0.0087\n",
"Epoch 20/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 99ms/step - loss: 0.0076\n",
"Epoch 21/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 97ms/step - loss: 0.0083\n",
"Epoch 22/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 98ms/step - loss: 0.0093\n",
"Epoch 23/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 114ms/step - loss: 0.0089\n",
"Epoch 24/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 98ms/step - loss: 0.0109\n",
"Epoch 25/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 98ms/step - loss: 0.0050\n",
"Epoch 26/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 116ms/step - loss: 0.0105\n",
"Epoch 27/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 98ms/step - loss: 0.0097\n",
"Epoch 28/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 124ms/step - loss: 0.0102\n",
"Epoch 29/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 119ms/step - loss: 0.0094\n",
"Epoch 30/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 103ms/step - loss: 0.0104\n"
]
}
],
"source": [
"history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
]
},
{
"cell_type": "code",
"execution_count": 112,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 720
},
"id": "UH77ijSZUJWq",
"outputId": "b98040c2-3d10-4824-b4f0-abfae8075dba"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[1m2/2\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 488ms/step\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x800 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"pred = model.predict(X_test)\n",
"plt.figure(figsize=(12,8))\n",
"plt.plot(y_test, color='blue', label='Real')\n",
"plt.plot(pred, color='red', label='Prediction')\n",
"plt.title('Bitcoin Cash Prediction')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 112,
"metadata": {
"id": "zIyf6qzoX2oL"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "pBEwefqtX3kW"
},
"source": [
"#EOS"
]
},
{
"cell_type": "code",
"execution_count": 113,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "TjCsw9DNX3kW",
"outputId": "54fbdc68-fb9f-469d-daed-528e3b96a68c"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(517, 17)"
]
},
"metadata": {},
"execution_count": 113
}
],
"source": [
"df5 = data_top_6_currencies[data_top_6_currencies['symbol']=='EOS']\n",
"\n",
"df5.shape"
]
},
{
"cell_type": "code",
"execution_count": 114,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "7VzpsN7TX3kW",
"outputId": "bc1413f9-449e-4f46-ed4b-1d949ebc0d83"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" slug symbol name date ranknow open high low close \\\n",
"7270 eos EOS EOS 2017-07-01 6 1.030000 1.07 0.989566 1.01 \n",
"7271 eos EOS EOS 2017-07-02 6 0.996521 2.88 0.822648 2.71 \n",
"7272 eos EOS EOS 2017-07-03 6 2.720000 5.40 2.630000 4.09 \n",
"7273 eos EOS EOS 2017-07-04 6 4.100000 4.19 2.930000 3.37 \n",
"7274 eos EOS EOS 2017-07-05 6 3.360000 3.52 2.730000 3.00 \n",
"... ... ... ... ... ... ... ... ... ... \n",
"7782 eos EOS EOS 2018-11-25 6 3.270000 3.43 3.030000 3.35 \n",
"7783 eos EOS EOS 2018-11-26 6 3.350000 3.41 3.080000 3.18 \n",
"7784 eos EOS EOS 2018-11-27 6 3.180000 3.18 2.900000 3.03 \n",
"7785 eos EOS EOS 2018-11-28 6 3.030000 3.37 3.030000 3.28 \n",
"7786 eos EOS EOS 2018-11-29 6 3.290000 3.30 2.930000 3.02 \n",
"\n",
" volume market close_ratio spread row_id market_billion \\\n",
"7270 1.361300e+07 0.000000e+00 0.2540 0.08 7271 0.000000 \n",
"7271 3.204520e+08 0.000000e+00 0.9174 2.06 7272 0.000000 \n",
"7272 4.149500e+08 6.549307e+08 0.5271 2.77 7273 0.654931 \n",
"7273 2.185590e+08 5.501552e+08 0.3492 1.26 7274 0.550155 \n",
"7274 1.243390e+08 5.006264e+08 0.3418 0.79 7275 0.500626 \n",
"... ... ... ... ... ... ... \n",
"7782 1.057330e+09 3.035994e+09 0.8000 0.40 7783 3.035994 \n",
"7783 9.845280e+08 2.885294e+09 0.3030 0.33 7784 2.885294 \n",
"7784 9.577230e+08 2.746077e+09 0.4643 0.28 7785 2.746077 \n",
"7785 8.601480e+08 2.971913e+09 0.7353 0.34 7786 2.971913 \n",
"7786 8.963941e+08 2.738537e+09 0.2432 0.37 7787 2.738537 \n",
"\n",
" volume_million volume_billion \n",
"7270 0.013613 1.361300e+07 \n",
"7271 0.320452 3.204520e+08 \n",
"7272 0.414950 4.149500e+08 \n",
"7273 0.218559 2.185590e+08 \n",
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"... ... ... \n",
"7782 1.057330 1.057330e+09 \n",
"7783 0.984528 9.845280e+08 \n",
"7784 0.957723 9.577230e+08 \n",
"7785 0.860148 8.601480e+08 \n",
"7786 0.896394 8.963941e+08 \n",
"\n",
"[517 rows x 17 columns]\n"
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],
"source": [
"print(df5)"
]
},
{
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" slug symbol name date ranknow open high low close \\\n",
"7270 eos EOS EOS 2017-07-01 6 1.030000 1.07 0.989566 1.01 \n",
"7271 eos EOS EOS 2017-07-02 6 0.996521 2.88 0.822648 2.71 \n",
"7272 eos EOS EOS 2017-07-03 6 2.720000 5.40 2.630000 4.09 \n",
"7273 eos EOS EOS 2017-07-04 6 4.100000 4.19 2.930000 3.37 \n",
"7274 eos EOS EOS 2017-07-05 6 3.360000 3.52 2.730000 3.00 \n",
"\n",
" volume market close_ratio spread row_id market_billion \\\n",
"7270 13613000.0 0.0 0.2540 0.08 7271 0.000000 \n",
"7271 320452000.0 0.0 0.9174 2.06 7272 0.000000 \n",
"7272 414950016.0 654930711.0 0.5271 2.77 7273 0.654931 \n",
"7273 218559008.0 550155157.0 0.3492 1.26 7274 0.550155 \n",
"7274 124339000.0 500626422.0 0.3418 0.79 7275 0.500626 \n",
"\n",
" volume_million volume_billion \n",
"7270 0.013613 13613000.0 \n",
"7271 0.320452 320452000.0 \n",
"7272 0.414950 414950016.0 \n",
"7273 0.218559 218559008.0 \n",
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"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "df5",
"repr_error": "0"
}
},
"metadata": {},
"execution_count": 115
}
],
"source": [
"df5.head()"
]
},
{
"cell_type": "code",
"execution_count": 116,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "stGfWD9YX3kX",
"outputId": "464a2456-d30b-44c7-e463-38af7e84aded"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" open high low close volume\n",
"7270 1.030000 1.07 0.989566 1.01 13613000.0\n",
"7271 0.996521 2.88 0.822648 2.71 320452000.0\n",
"7272 2.720000 5.40 2.630000 4.09 414950016.0\n",
"7273 4.100000 4.19 2.930000 3.37 218559008.0\n",
"7274 3.360000 3.52 2.730000 3.00 124339000.0\n",
"(517, 5)\n"
]
}
],
"source": [
"d5 = df5.iloc[:, 5:10]\n",
"print(d5.head())\n",
"print(d5.shape)"
]
},
{
"cell_type": "code",
"execution_count": 117,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 590
},
"id": "Y8SdLCNNX3kX",
"outputId": "a4f8a694-ebd8-4a49-e7a9-d7d05eda4330"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Price of EOS')"
]
},
"metadata": {},
"execution_count": 117
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"plt.figure(figsize=(12,6))\n",
"sns.lineplot(x=d5.index, y=\"open\", data=d5).set_title(\"Price of EOS\")"
]
},
{
"cell_type": "code",
"execution_count": 118,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "wvdmLlFsX3kX",
"outputId": "e12298bc-4654-4dee-c8eb-37b8200f1e59"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"7270 1.030000\n",
"7271 0.996521\n",
"7272 2.720000\n",
"7273 4.100000\n",
"7274 3.360000\n",
" ... \n",
"7782 3.270000\n",
"7783 3.350000\n",
"7784 3.180000\n",
"7785 3.030000\n",
"7786 3.290000\n",
"Name: open, Length: 517, dtype: float64\n"
]
}
],
"source": [
"data = d5.iloc[:, 0]\n",
"\n",
"print(data)"
]
},
{
"cell_type": "code",
"execution_count": 119,
"metadata": {
"id": "yawhGJ_rX3kX"
},
"outputs": [],
"source": [
"hist = []\n",
"target = []\n",
"length = 90\n",
"for i in range(7270,len(data)-length):\n",
" x = data[7270:i+length]\n",
" y = data[i+length]\n",
" hist.append(x)\n",
" target.append(y)"
]
},
{
"cell_type": "code",
"execution_count": 120,
"metadata": {
"id": "ldt2BGLhX3kX"
},
"outputs": [],
"source": [
"hist = np.array(hist)\n",
"target = np.array(target)\n",
"target = target.reshape(-1,1)"
]
},
{
"cell_type": "code",
"execution_count": 121,
"metadata": {
"id": "ylr7fwbAX3kX"
},
"outputs": [],
"source": [
"hist = hist.reshape(1,-1)"
]
},
{
"cell_type": "code",
"execution_count": 122,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ejlHo8paX3kX",
"outputId": "4f65292d-d749-4d86-acad-17a4c17b4021"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(1952, 90, 1)\n"
]
}
],
"source": [
"hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
"print(hist_scaled.shape)"
]
},
{
"cell_type": "code",
"execution_count": 123,
"metadata": {
"id": "TOFbdITuX3kX"
},
"outputs": [],
"source": [
"X_train = hist_scaled[:1900,:,:]\n",
"X_test = hist_scaled[1900:,:,:]\n",
"y_train = target_scaled[:1900,:]\n",
"y_test = target_scaled[1900:,:]"
]
},
{
"cell_type": "code",
"execution_count": 124,
"metadata": {
"id": "2q1aJEr5X3kY"
},
"outputs": [],
"source": [
"import tensorflow as tf\n",
"from tensorflow.keras import layers"
]
},
{
"cell_type": "code",
"execution_count": 125,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 272
},
"id": "zAml_KZ4X3kY",
"outputId": "46f4e3c4-ac9b-4264-c0da-6ff49abfbebb"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1mModel: \"sequential_4\"\u001b[0m\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_4\"</span>\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm_12 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m4,352\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_13 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_14 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense_4 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m) │ \u001b[38;5;34m33\u001b[0m │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃<span style=\"font-weight: bold\"> Layer (type) </span>┃<span style=\"font-weight: bold\"> Output Shape </span>┃<span style=\"font-weight: bold\"> Param # </span>┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm_12 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">4,352</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_13 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_14 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span> │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
"</pre>\n"
]
},
"metadata": {}
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" input_shape=(90,1), dropout=0.2))\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" dropout=0.2))\n",
"model.add(layers.LSTM(units=32, dropout=0.2))\n",
"model.add(layers.Dense(units=1))\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 126,
"metadata": {
"id": "blIv5kwJX3kY"
},
"outputs": [],
"source": [
"model.compile(optimizer='adam', loss='mean_squared_error')"
]
},
{
"cell_type": "code",
"execution_count": 127,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "PYbQNxSRX3kY",
"outputId": "f2cc9ddf-45fa-4c91-fc97-c7bf213f5608"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 1/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 101ms/step - loss: 0.0202\n",
"Epoch 2/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 109ms/step - loss: 0.0084\n",
"Epoch 3/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 98ms/step - loss: 0.0120\n",
"Epoch 4/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0131\n",
"Epoch 5/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 119ms/step - loss: 0.0119\n",
"Epoch 6/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 103ms/step - loss: 0.0111\n",
"Epoch 7/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 127ms/step - loss: 0.0115\n",
"Epoch 8/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 104ms/step - loss: 0.0105\n",
"Epoch 9/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 97ms/step - loss: 0.0086\n",
"Epoch 10/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 96ms/step - loss: 0.0104\n",
"Epoch 11/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 121ms/step - loss: 0.0100\n",
"Epoch 12/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 124ms/step - loss: 0.0117\n",
"Epoch 13/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 102ms/step - loss: 0.0082\n",
"Epoch 14/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 100ms/step - loss: 0.0114\n",
"Epoch 15/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 123ms/step - loss: 0.0078\n",
"Epoch 16/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 101ms/step - loss: 0.0080\n",
"Epoch 17/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 101ms/step - loss: 0.0068\n",
"Epoch 18/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 135ms/step - loss: 0.0077\n",
"Epoch 19/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 103ms/step - loss: 0.0087\n",
"Epoch 20/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 106ms/step - loss: 0.0087\n",
"Epoch 21/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 119ms/step - loss: 0.0074\n",
"Epoch 22/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 110ms/step - loss: 0.0067\n",
"Epoch 23/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 123ms/step - loss: 0.0073\n",
"Epoch 24/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 130ms/step - loss: 0.0103\n",
"Epoch 25/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 103ms/step - loss: 0.0066\n",
"Epoch 26/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 130ms/step - loss: 0.0080\n",
"Epoch 27/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 103ms/step - loss: 0.0090\n",
"Epoch 28/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 101ms/step - loss: 0.0082\n",
"Epoch 29/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 137ms/step - loss: 0.0077\n",
"Epoch 30/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 102ms/step - loss: 0.0080\n"
]
}
],
"source": [
"history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
]
},
{
"cell_type": "code",
"execution_count": 128,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 720
},
"id": "TT6qgo_iX3kY",
"outputId": "9e2e0307-3f85-425b-9d1a-c422d00687da"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[1m2/2\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 534ms/step\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x800 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"pred = model.predict(X_test)\n",
"plt.figure(figsize=(12,8))\n",
"plt.plot(y_test, color='blue', label='Real')\n",
"plt.plot(pred, color='red', label='Prediction')\n",
"plt.title('EOS Prediction')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "F087Ykqwazgx"
},
"source": [
"#Stellar"
]
},
{
"cell_type": "code",
"execution_count": 129,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "gSZO1_fBa5Oe",
"outputId": "9cc8eaae-18c9-4b27-b76f-674a76ff66de"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(1578, 17)"
]
},
"metadata": {},
"execution_count": 129
}
],
"source": [
"df6 = data_top_6_currencies[data_top_6_currencies['name']=='Stellar']\n",
"\n",
"df6.shape"
]
},
{
"cell_type": "code",
"execution_count": 130,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "mejmybDCa5Of",
"outputId": "5e78a4f9-e7f8-4f40-c40c-3b53fefe624a"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" slug symbol name date ranknow open high \\\n",
"5197 stellar XLM Stellar 2014-08-05 4 0.002976 0.003387 \n",
"5198 stellar XLM Stellar 2014-08-06 4 0.002373 0.003402 \n",
"5199 stellar XLM Stellar 2014-08-07 4 0.002686 0.003042 \n",
"5200 stellar XLM Stellar 2014-08-08 4 0.002493 0.003243 \n",
"5201 stellar XLM Stellar 2014-08-09 4 0.002884 0.003710 \n",
"... ... ... ... ... ... ... ... \n",
"6770 stellar XLM Stellar 2018-11-25 4 0.155430 0.159619 \n",
"6771 stellar XLM Stellar 2018-11-26 4 0.159195 0.163263 \n",
"6772 stellar XLM Stellar 2018-11-27 4 0.144355 0.146664 \n",
"6773 stellar XLM Stellar 2018-11-28 4 0.144111 0.167606 \n",
"6774 stellar XLM Stellar 2018-11-29 4 0.161831 0.172107 \n",
"\n",
" low close volume market close_ratio spread \\\n",
"5197 0.002349 0.002440 30316.0 7.676790e+05 0.0877 0.00 \n",
"5198 0.002266 0.002657 35820.0 9.663700e+05 0.3442 0.00 \n",
"5199 0.002455 0.002501 142864.0 1.079148e+06 0.0784 0.00 \n",
"5200 0.002493 0.002881 93708.0 1.260109e+06 0.5173 0.00 \n",
"5201 0.002873 0.003481 233579.0 1.645185e+06 0.7264 0.00 \n",
"... ... ... ... ... ... ... \n",
"6770 0.133734 0.159607 137467000.0 3.056464e+09 0.9995 0.03 \n",
"6771 0.137487 0.144795 105913000.0 2.772933e+09 0.2835 0.03 \n",
"6772 0.137987 0.144374 81742500.0 2.765411e+09 0.7361 0.01 \n",
"6773 0.144111 0.162237 101285000.0 3.107568e+09 0.7715 0.02 \n",
"6774 0.155423 0.165080 88862064.0 3.162026e+09 0.5788 0.02 \n",
"\n",
" row_id market_billion volume_million volume_billion \n",
"5197 5198 0.000768 0.000030 30316.0 \n",
"5198 5199 0.000966 0.000036 35820.0 \n",
"5199 5200 0.001079 0.000143 142864.0 \n",
"5200 5201 0.001260 0.000094 93708.0 \n",
"5201 5202 0.001645 0.000234 233579.0 \n",
"... ... ... ... ... \n",
"6770 6771 3.056464 0.137467 137467000.0 \n",
"6771 6772 2.772933 0.105913 105913000.0 \n",
"6772 6773 2.765411 0.081742 81742500.0 \n",
"6773 6774 3.107568 0.101285 101285000.0 \n",
"6774 6775 3.162026 0.088862 88862064.0 \n",
"\n",
"[1578 rows x 17 columns]\n"
]
}
],
"source": [
"print(df6)"
]
},
{
"cell_type": "code",
"execution_count": 131,
"metadata": {
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"base_uri": "https://localhost:8080/",
"height": 313
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{
"output_type": "execute_result",
"data": {
"text/plain": [
" slug symbol name date ranknow open high \\\n",
"5197 stellar XLM Stellar 2014-08-05 4 0.002976 0.003387 \n",
"5198 stellar XLM Stellar 2014-08-06 4 0.002373 0.003402 \n",
"5199 stellar XLM Stellar 2014-08-07 4 0.002686 0.003042 \n",
"5200 stellar XLM Stellar 2014-08-08 4 0.002493 0.003243 \n",
"5201 stellar XLM Stellar 2014-08-09 4 0.002884 0.003710 \n",
"\n",
" low close volume market close_ratio spread row_id \\\n",
"5197 0.002349 0.002440 30316.0 767679.0 0.0877 0.0 5198 \n",
"5198 0.002266 0.002657 35820.0 966370.0 0.3442 0.0 5199 \n",
"5199 0.002455 0.002501 142864.0 1079148.0 0.0784 0.0 5200 \n",
"5200 0.002493 0.002881 93708.0 1260109.0 0.5173 0.0 5201 \n",
"5201 0.002873 0.003481 233579.0 1645185.0 0.7264 0.0 5202 \n",
"\n",
" market_billion volume_million volume_billion \n",
"5197 0.000768 0.000030 30316.0 \n",
"5198 0.000966 0.000036 35820.0 \n",
"5199 0.001079 0.000143 142864.0 \n",
"5200 0.001260 0.000094 93708.0 \n",
"5201 0.001645 0.000234 233579.0 "
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" <td>2014-08-09</td>\n",
" <td>4</td>\n",
" <td>0.002884</td>\n",
" <td>0.003710</td>\n",
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],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "df6",
"repr_error": "0"
}
},
"metadata": {},
"execution_count": 131
}
],
"source": [
"df6.head()"
]
},
{
"cell_type": "code",
"execution_count": 132,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "u4YVMNKha5Of",
"outputId": "4b786477-d357-424a-8d4b-94a6b2e008e1"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" open high low close volume\n",
"5197 0.002976 0.003387 0.002349 0.002440 30316.0\n",
"5198 0.002373 0.003402 0.002266 0.002657 35820.0\n",
"5199 0.002686 0.003042 0.002455 0.002501 142864.0\n",
"5200 0.002493 0.003243 0.002493 0.002881 93708.0\n",
"5201 0.002884 0.003710 0.002873 0.003481 233579.0\n",
"(1578, 5)\n"
]
}
],
"source": [
"d = df6.iloc[:, 5:10]\n",
"print(d.head())\n",
"print(d.shape)"
]
},
{
"cell_type": "code",
"execution_count": 133,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 590
},
"id": "Pib0FOL3a5Of",
"outputId": "be936554-d75a-4cba-f499-758e02ecfe0c"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Price of Stellar')"
]
},
"metadata": {},
"execution_count": 133
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"plt.figure(figsize=(12,6))\n",
"sns.lineplot(x=d.index, y=\"open\", data=d).set_title(\"Price of Stellar\")"
]
},
{
"cell_type": "code",
"execution_count": 134,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "1FPPamzibSiL",
"outputId": "7427a6f9-676f-4db0-a0ed-a1b2a0301f5f"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" open high low close volume\n",
"5197 0.002976 0.003387 0.002349 0.002440 30316.0\n",
"5198 0.002373 0.003402 0.002266 0.002657 35820.0\n",
"5199 0.002686 0.003042 0.002455 0.002501 142864.0\n",
"5200 0.002493 0.003243 0.002493 0.002881 93708.0\n",
"5201 0.002884 0.003710 0.002873 0.003481 233579.0\n",
"... ... ... ... ... ...\n",
"6770 0.155430 0.159619 0.133734 0.159607 137467000.0\n",
"6771 0.159195 0.163263 0.137487 0.144795 105913000.0\n",
"6772 0.144355 0.146664 0.137987 0.144374 81742500.0\n",
"6773 0.144111 0.167606 0.144111 0.162237 101285000.0\n",
"6774 0.161831 0.172107 0.155423 0.165080 88862064.0\n",
"\n",
"[1578 rows x 5 columns]\n"
]
}
],
"source": [
"print(d)"
]
},
{
"cell_type": "code",
"execution_count": 135,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "O5snSz7Aa5Of",
"outputId": "3f724e13-0729-4789-efe2-c1a5a50325fb"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"1578\n",
"5197 0.002976\n",
"5198 0.002373\n",
"5199 0.002686\n",
"5200 0.002493\n",
"5201 0.002884\n",
" ... \n",
"6770 0.155430\n",
"6771 0.159195\n",
"6772 0.144355\n",
"6773 0.144111\n",
"6774 0.161831\n",
"Name: open, Length: 1578, dtype: float64\n"
]
}
],
"source": [
"data = d.iloc[:, 0]\n",
"print(len(data))\n",
"print(data)\n",
"hist = []\n",
"target = []\n",
"length = 90\n",
"for i in range(5197, len(data)-length):\n",
" x = data[5197,:i+length]\n",
" y = data[i+length]\n",
" hist.append(x)\n",
" target.append(y)"
]
},
{
"cell_type": "code",
"execution_count": 136,
"metadata": {
"id": "5wCLydLha5Og"
},
"outputs": [],
"source": [
"hist = np.array(hist)\n",
"target = np.array(target)\n",
"target = target.reshape(-1,1)\n",
"hist=hist.reshape(-1,1)"
]
},
{
"cell_type": "code",
"execution_count": 139,
"metadata": {
"id": "PxEu7xN0a5Og",
"outputId": "c5387772-30ff-461e-e1c5-9d7db332c6bd",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"1578\n",
"5197 0.002976\n",
"5198 0.002373\n",
"5199 0.002686\n",
"5200 0.002493\n",
"5201 0.002884\n",
" ... \n",
"6770 0.155430\n",
"6771 0.159195\n",
"6772 0.144355\n",
"6773 0.144111\n",
"6774 0.161831\n",
"Name: open, Length: 1578, dtype: float64\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([[0.002976],\n",
" [0.002373],\n",
" [0.002686],\n",
" ...,\n",
" [0.15543 ],\n",
" [0.159195],\n",
" [0.144355]])"
]
},
"metadata": {},
"execution_count": 139
}
],
"source": [
"data = d.iloc[:, 0]\n",
"print(len(data))\n",
"print(data)\n",
"hist = []\n",
"target = []\n",
"length = 90\n",
"\n",
"# Adjust the loop range to ensure it executes\n",
"for i in range(len(data) - length - 1): # Iterate through the entire data\n",
" x = data.iloc[i : i + length].values # Extract data slice using iloc and convert to numpy array\n",
" y = data.iloc[i + length] # Extract target value using iloc\n",
" hist.append(x)\n",
" target.append(y)\n",
"\n",
"hist = np.array(hist)\n",
"target = np.array(target)\n",
"target = target.reshape(-1, 1)\n",
"hist = hist.reshape(-1, 1)\n",
"\n",
"from sklearn.preprocessing import MinMaxScaler\n",
"\n",
"sc = MinMaxScaler()\n",
"hist"
]
},
{
"cell_type": "code",
"execution_count": 140,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "JBgXLlZAa5Og",
"outputId": "a93e5441-fe2f-4fb9-fe42-fca133317730"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(1952, 90, 1)\n"
]
}
],
"source": [
"hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
"print(hist_scaled.shape)"
]
},
{
"cell_type": "code",
"execution_count": 141,
"metadata": {
"id": "wmqhRFVUa5Og"
},
"outputs": [],
"source": [
"X_train = hist_scaled[:1900,:,:]\n",
"X_test = hist_scaled[1900:,:,:]\n",
"y_train = target_scaled[:1900,:]\n",
"y_test = target_scaled[1900:,:]"
]
},
{
"cell_type": "code",
"execution_count": 142,
"metadata": {
"id": "hKMNQyGna5Og"
},
"outputs": [],
"source": [
"import tensorflow as tf\n",
"from tensorflow.keras import layers"
]
},
{
"cell_type": "code",
"execution_count": 143,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 272
},
"id": "wIUvXFUCa5Og",
"outputId": "c7428ab9-1ee6-41a3-f65c-1a741fe60b4a"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1mModel: \"sequential_5\"\u001b[0m\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_5\"</span>\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm_15 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m4,352\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_16 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m90\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_17 (\u001b[38;5;33mLSTM\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m8,320\u001b[0m │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense_5 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m) │ \u001b[38;5;34m33\u001b[0m │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
"┃<span style=\"font-weight: bold\"> Layer (type) </span>┃<span style=\"font-weight: bold\"> Output Shape </span>┃<span style=\"font-weight: bold\"> Param # </span>┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
"│ lstm_15 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">4,352</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_16 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">90</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ lstm_17 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">8,320</span> │\n",
"├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
"│ dense_5 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span> │\n",
"└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m21,025\u001b[0m (82.13 KB)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">21,025</span> (82.13 KB)\n",
"</pre>\n"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
],
"text/html": [
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
"</pre>\n"
]
},
"metadata": {}
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" input_shape=(90,1), dropout=0.2))\n",
"model.add(layers.LSTM(units=32, return_sequences=True,\n",
" dropout=0.2))\n",
"model.add(layers.LSTM(units=32, dropout=0.2))\n",
"model.add(layers.Dense(units=1))\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 144,
"metadata": {
"id": "2JVd7TxPa5Og"
},
"outputs": [],
"source": [
"model.compile(optimizer='adam', loss='mean_squared_error')"
]
},
{
"cell_type": "code",
"execution_count": 145,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "m5lWh3Yba5Oh",
"outputId": "8817e447-91ee-47c1-eaec-5572753223c5"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 1/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m13s\u001b[0m 102ms/step - loss: 0.0117\n",
"Epoch 2/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 133ms/step - loss: 0.0119\n",
"Epoch 3/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 101ms/step - loss: 0.0086\n",
"Epoch 4/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 122ms/step - loss: 0.0101\n",
"Epoch 5/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 133ms/step - loss: 0.0110\n",
"Epoch 6/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 102ms/step - loss: 0.0076\n",
"Epoch 7/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 134ms/step - loss: 0.0082\n",
"Epoch 8/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 102ms/step - loss: 0.0088\n",
"Epoch 9/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 132ms/step - loss: 0.0082\n",
"Epoch 10/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 114ms/step - loss: 0.0097\n",
"Epoch 11/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 121ms/step - loss: 0.0071\n",
"Epoch 12/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 105ms/step - loss: 0.0088\n",
"Epoch 13/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 100ms/step - loss: 0.0093\n",
"Epoch 14/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 102ms/step - loss: 0.0105\n",
"Epoch 15/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 132ms/step - loss: 0.0101\n",
"Epoch 16/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 119ms/step - loss: 0.0090\n",
"Epoch 17/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 101ms/step - loss: 0.0110\n",
"Epoch 18/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 102ms/step - loss: 0.0076\n",
"Epoch 19/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 124ms/step - loss: 0.0074\n",
"Epoch 20/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 103ms/step - loss: 0.0073\n",
"Epoch 21/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 101ms/step - loss: 0.0106\n",
"Epoch 22/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 126ms/step - loss: 0.0104\n",
"Epoch 23/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 127ms/step - loss: 0.0067\n",
"Epoch 24/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 102ms/step - loss: 0.0096\n",
"Epoch 25/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 101ms/step - loss: 0.0115\n",
"Epoch 26/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 133ms/step - loss: 0.0091\n",
"Epoch 27/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 102ms/step - loss: 0.0104\n",
"Epoch 28/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 100ms/step - loss: 0.0081\n",
"Epoch 29/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 116ms/step - loss: 0.0091\n",
"Epoch 30/30\n",
"\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 136ms/step - loss: 0.0078\n"
]
}
],
"source": [
"history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
]
},
{
"cell_type": "code",
"execution_count": 146,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 720
},
"id": "bCmQ1HDRa5Oh",
"outputId": "ff2a516c-305f-47f0-a4b3-df0b965fd33d"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[1m2/2\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 521ms/step\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x800 with 1 Axes>"
],
"image/png": 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AANwYwR0AAAAAADdGcAcAAAAAwI0xOB0AAAAA5JKkpCQlJCS4uox85fLlyylrD4/8e6/Z29tbnp6eTjkWwR0AAAAAnMxqterEiROKiooqFNOaOVNycrK8vLx07NixfB3cLRaLgoODVaZMGVkslhwdi+AOAAAAAE4WFRWl8+fPq2TJkgoMDMxxcCtMkpKSdPnyZfn6+jrtjnVes1qtunTpkk6fPi1/f38VK1YsR8cjuAMAAACAE1mtVp06dUpBQUG67rrrXF1OvpOUlCRJ8vPzy7fBXZL8/f11+fJlnTp1SsHBwTn68Cb/tjsAAAAAADeUlJSkpKQkBQUFuboUuFhQUFDK9ZATBHcAAAAAcKLExERJkpcXDZwLO9s1YLsmsovgDgAAAAC5gH7tcNY1QHAHAAAAAMCNEdwBAAAAABmaMmWKwsPDU5amTZuqa9euWr16da6cr3v37nrqqady5dj5GcEdAAAAAJApPz8/zZ8/X/Pnz9eoUaN0+fJl9e3bV1u3bnV1aYUGoyUAAAAAADLl4eGhiIiIlMcNGjRQy5YttWDBAjVq1Mh1hRUi3HEHAAAAAGRZ6dKlFRISomPHjqU8t23bNj366KOKiIhQ48aNNWjQIJ05c8budRMmTNA999yjhg0b6pZbbtHzzz+vU6dO5XX5+RJ33AEAAAAgD1itUkyMa84dECA5a5D7S5cuKSoqShUqVJBkQnv37t3VsmVLTZo0SbGxsZo8ebL69eun+fPnp7zuzJkz6tOnj0qVKqWzZ8/q448/Vvfu3bV48WKmzrsGvjsAAAAAkMusVunmm6X1611z/ubNpV9+yX54t81DfurUKb311lsKDAzUo48+KkmaOHGi6tatq6lTp6ZMf1ajRg3dfffdWr16tVq2bClJGjt2bMrxkpKS1LBhQ7Vo0UIbN27UzTffnIN3V/AR3AEAAAAgD+TXad1jYmJUp06dlMeenp6aPn26wsLCFBsbq61bt+rFF19UUlJSyj6hoaEqW7asdu7cmRLcV69erRkzZujPP//UxYsXU/Y9dOgQwf0aCO4AAAAAkMssFnPHOz82lffz89Onn34qq9WqQ4cOaeLEiXrppZe0cOFCWa1WJSUlaezYsXZ31G2OHz8uSfr999/Vr18/tW7dWr169VKJEiVksVj04IMP6vLlyzl5a4UCwR0AAAAA8oDFIgUGuroKx3l4eKhevXqSpPr166tKlSp68MEHNW3aNL300kuyWCzq06ePbr/99nSvLV68uCRpxYoVKlKkiCZPniwPDzNG+tGjR/PuTeRzBHcAAAAAQJbVq1dP7du31zfffKOnn35aERERioyMTAn3GYmLi5O3t3dKH3hJWrhwYV6UWyAwHRwAAAAAwCH9+vVTUlKSZs+erRdffFE///yzBg4cqOXLl2vTpk367rvv9NJLL2nTpk2SpObNm+v06dMaNWqUNmzYoOnTp+vbb7918bvIPwjuAAAAAACHhIWF6a677tLcuXNVvXp1ff7554qJidHQoUPVu3dvTZ8+XX5+fqpcubIkqWXLlho8eLBWrlypp556Sps3b9Z7773n4neRf9BUPp85c0b6809/lStnBpgAAAAAgNzyzDPP6JlnnsnwaxMmTEjZrlevnt5///2rHqtXr17q1auX3XP79u2zezxnzhwlJSUpLi4umxUXTAT3fCQxUWrUyF///ltbklSsmBQaKlWunPG6ePH8O+UEAAAAAMAguOcjXl7SXXcl6bvvpKgoL50/L23fbpaMFCmScagPC5MaNZI86CgBAAAAAG6P4J7PzJgRrwED9qhixVo6fTpAhw9Lhw4p3frkSeniRWn3brNcqW5daeRI6b77uCsPAAAAAO6M4J5PFSkilSol1amT8ddjY6UjR1KDfNpQv3OntGuX1LGjufM+apTUrh0BHgAAAADcEcG9gPL3l8LDzXKlc+ekt9+WJk+Wtm6V2reXmjWTRo+WWrXK81IBAAAAAFdBL+dCqHhxc5c9MlIaPFjy85M2bJBatzbBff16V1cIAAAAALAhuBdiJUtKb71lAvwzz0g+PtJPP0nNm0t33SVt2eLqCgEAAAAABHeobFnpnXekP/+UevWSPD2lJUuk6683/eB37XJ1hQAAAABQeBHckaJSJen996W9e6Xu3c1gdd9+K9WvL3XrJu3f7+oKC5akJNM9IShIqlnTbD/6qDR0qDRlivTNN9KmTdI//0iJia6uFgAAAICrMDgd0qlWTfrkE2nIEGn4cOnLL6W5c6X586UePaRhw8yc8MiZdeukVavM9r59ZsmMxSKVLi2VL5+6lCtn1hUrSjffbMYqAAAAAFDwcMcdmapdW/riC2nbNumee6TkZOnjj6UaNUyot1pdXWH+9sUXZt25swnwn34qvfmmNGCA9MAD0o03mlDu5WW+1ydOmHEHvv9emjFDeu016fHHpTZtpMqVpTFjzIwBAAAAgLNMmTJF4eHhKcuNN96oRx99VJs3b861c44dO1bt27dPefzNN98oPDxcZ8+ezfIxVqxYoc8++yzd80OGDNHdd9/tlDrzEnfccU0RESYsbtpkwuLy5SZg3nWX1KKFq6vLn5KSpK++MtuPPy7ddlvm+yYnS6dPS0eP2i/Hjpn1zp1m+5VXpLFjpT59pIEDpQoV8uStAAAAoIDz8/PT7NmzJUknTpzQ9OnT1bNnT33zzTeqUaNGrp//1ltv1fz58xUUFJTl16xYsUK7du3Sww8/bPd8v379FBMT4+wScx3BHVnWtKm0bJnp7z53rrRoEcE9u375RTp50kzN17r11ff18DDN5EuXlho1Sv/1hATTjWH8eBPiJ040gw0+/LD0wgum5QQAAACQXR4eHoqIiEh5XL9+fbVq1Urz5s3TsGHD7Pa1Wq1KSEiQj4+P084fEhKikJAQpxyrUqVKTjlOXqOpPBzWoYNZL1zo2jryM1sz+Y4dJW/vnB3L21t65BFpxw5p8WKpZUsT5mfNkurUke691/SnBwAAAJyhXLlyCgkJ0T///JPS9Hz16tW69957Va9ePa36byCnbdu26dFHH1VERIQaN26sQYMG6cyZM3bHOnnypPr27asGDRrolltu0cyZM9OdL6Om8vHx8Zo0aZJat26tunXrqkWLFhoyZIgk0xz+22+/1Z9//pnSxD/t165sKr9v3z498cQTKXUOGDBAx44ds9snPDxcM2fO1JQpU3TTTTepadOmGjp0aJ7dveeOOxx2xx2m3/XevdJff5nB7JB1iYmpzeQffNB5x7VYTPeFu+4y3RrefFNasMB8wLJwodS8ufTSS1L79uYuPgAAAPKY1Sq5qpl2QID5g9EJLl68qPPnz6tUqVJKTEzUqVOnNHr0aD311FMqW7asypUrp23btql79+5q2bKlJk2apNjYWE2ePFn9+vXT/PnzU47Vr18/nTx5UsOHD1fRokU1c+ZMHT9+XB7X+IP1mWee0caNG9WnTx9FRETo7NmzWrZsWcoxz549q8jISE2YMEGSMr1jf/z4cT3yyCOqWLGi3nrrLV2+fFmTJk3SI488ou+//15FihRJ2fezzz5T48aNNW7cOB06dEjjx49XiRIlNHjw4Jx+S6+J4A6HFSsm3XKL9NNPprn8wIGurih/Wb3a9FkvUeLqfdtzomlTM53cvn3ShAlmloB168zd99q1pRdflLp2lZzYggkAAABXY7WaqYDWr3fN+Zs3N/01sxneE/+bn/jEiRN68803lZSUpDvuuEOLFy9WVFSUZs6cqQYNGqTs/8orr6hu3bqaOnWqLP+ds0aNGil351u2bKk1a9Zo165dmjVrlpo1ayZJatq0qVq2bHnV/uzr1q3Tzz//rIkTJ9rdPbdtV6pUSSEhITp27JhdE/+MzJo1S4mJifroo49UrFgxSVKtWrXUvn17ffvtt+revXvKviVLltTEiRMlSS1atNAff/yhH3/8MU+CO/fdkC333GPWNJd3nK2Z/AMP5LyZ/LWEh0szZ0qHDpm77UFB0h9/SD17SlWrSm+/LUVH524NAAAA+I+T7njntZiYGNWpU0d16tRR69attWnTJg0bNky33HKLJKlYsWJ2oT02NlZbt27VnXfeqaSkJCUmJioxMVGhoaEqW7asdu7cKUn6/fffVbRo0ZTQLind44xs2LBB/v7+diPPZ9fmzZvVtGnTlNAuSVWrVlXNmjW1ZcsWu31vuukmu8dVq1bViRMnclxDVnDHHdlyzz3S889La9ZIUVFScLCrK8ofEhOlr782285sJn8tZctK48ZJQ4dK770nTZ4s/fOPNGiQNGqU9PTTJtinaQkEAAAAZ7JYzB3vfNhU3s/PT59++qksFouKFy+usmXL2jVlv+666+z2v3DhgpKSkjR27FiNHTs23fGOHz8uSTp16lSGTdhLlChx1XrOnz+vkiVLptzJz4kLFy6oVq1aGdYQFRVl99yVrQC8vb0VHx+f4xqyguCObKlWzdzN3bdP+vHHvA2h+dlPP0lnzkglS5pB5PJacLBpJv/ss2be+LfeMv+Go0dLs2dLU6akDj4IAAAAJ7NYpMBAV1fhMA8PD9WrVy/Tr18ZoIsWLSqLxaI+ffro9ttvT7d/8eLFJUmlSpXKcG72Kwewu1KxYsV0+vRpWa3WHIf34ODgDM935swZhYaG5ujYzkRTeWSbrbn8okWurSM/SdtM3suFH5v5+kpPPGGazX/1lRQaKv39t3TffWY5csR1tQEAACB/CwgIUEREhCIjI1WvXr10S4UKFSRJ9erVU3R0tDZs2JDy2isfZ+Smm25SbGyslixZkuk+3t7eunz58jVrbdy4sTZu3Gh3dz0yMlL79u1T48aNr/n6vEJwR7bZxoH44QcpKcm1teQHCQlmwDjJfVooeHiYDxF27zbN6L28pO++k2rVMoPaJSS4ukIAKDiOHrVo48aiSk52dSUAkPtefPFF/fzzzxo4cKCWL1+uTZs26bvvvtNLL72kTZs2STIDvNWpU0cvvPCCFixYoJUrV+rJJ5+0G8k9IzfddJNatmypl19+We+++642bNigJUuWaGCaUbOrVq2qo0ePatGiRdq5c6f++eefDI/Vs2dPeXl56fHHH9eKFSu0ePFi9enTR2XLltX999/vtO9HThHckW3Nm5sR5s+ckTZudHU17m/VKunsWalUKalFC1dXYy8gQBozRtq+3Qx2GhMjvfCCdP31/NsCQE6dOCENGCDVreunp5+uoc6dfZVBy1AAKFAaNWqkzz//XDExMRo6dKh69+6t6dOny8/PT5UrV5ZkmthPnz5dderU0bBhw/T666+rVatWatu27TWPP2XKFHXv3l3z589Xr169NG7cOAUEBKR8vVOnTrrzzjs1atQoderUSVOnTs3wOGXLltWcOXMUHByswYMH67XXXlPNmjU1Z86ca36AkJcsVqvV6uoi3IFtZMOr9d1wBzExMdqzZ49q1apld2G6Srdu0ty5ZmCzceNcXY17e/xx6eOPpX79pGnTXF1N5pKTpVmzTHA/e9Z0xerdWxo7VvqvO1I67nZdAhLXJVzvzBlp/HgzfkhsrHnOw8Oq5GSLKlc2XZWuv961NQL8rMwdcXFxOnjwoKpUqSI/Pz9Xl5PvJCUlKS4uTn5+fvL09HR1OTlyrWshqzmUO+7IEfq5Z018vPTtt2bbXZrJZ8bDw3zIsG+fmTbOajUj0desaQa046M+ALi6Cxek4cOlKlVMcI+NlW68UVq8OE5z5uxRWFiyDh82LddmzODnKgDg2gjuyJE775Q8PU0f6YMHXV2N+1qxQjp/3kzLdvPNrq4ma667zrQQ+Pln0+f91Cmpe3fp9ttNqAcA2Lt0SXrzTRPYR4yQoqOliAjz4fb69dKttyYrPDxWa9fG6b77zIe6/fqZn62XLrm6egCAOyO4I0eKF08Notx1z5xtNPlOncwHHflJy5am7/uYMZKfn+mrX7++9PrrUlycq6szrFZp/37pt99SP0Q6edL80ZyY6OrqkNtiYsy/+YYNpmXLjBnm+hwyxFvHj/u4ujwUApcvS++8I1WtKg0ZYroZ1aolffmltGWL1L69/dTJwcFmsNIJE8zvhM8+k5o0kfbudd17AAC4N+ZxR47dc4+0erW0cKH0zDOursb9XL4sLVhgtt29mXxmfHzMqPMPPST17y8tXSqNHGnGN5g+XbrppryvKSrKfIiwdKlZrjaFnY+PGYAvo8XfP3W7SBGpUiUpLCx1KVYsz96SQ6xW6eJF0yT3ysVikWrUkKpVMx+25CdWq5nNIDHRtFI5cSLj5eTJ1O0LFzI7mrdWrgzTNWaUAbItIcGMCTJqlJlSUzI/N4YPN2PAXO2DWotFGjTIBPaHHjLTc15/vfTBB1KXLnlRPQAgPyG4I8fuvlsaPNg0qY6OlooWdXVF7mX5chMyy5VzTcB1prAwM/3fV19Jzz4r/fmn1KaN9OCDPrr77gBVqmQCcG5ITjZ3/m1Bff16+2kIfX2l0qVNX9KYGLPY+o3Gx5vl/HnHz1usmH2Qr1IldbtSJfOhQHbey4ULpp6Mlqio9GE8o+eu1S/Ww8PUGx5uxihIu1x3nf0dwOywWk29R45Ihw/br0+cMN/zxMTUIJ6VdXanyfLzk8qUSV1Kl5bmz7fqjz8CNWlSvF5/PWfvFUgrKcl8cDl8uHTggHmufHlp2DDpscckb++sH+uWW6Rt26SuXaWffjLrdevM3Xhf31wpH0AeYhxwOOsaILgjx8LDperVTYhbtszMC45UtmbynTubIJXfWSzmvdxxh/Tqq2aE/C++8NIXX9SSJIWGSrVrS3XqmHXt2qbJaHY+0Dl92nzwsXSp9OOPpp99WuHhZpyFO+4wTfrTfmhgtZrWDrYQn5UlKsoEz8hIs5w8aYLp1q1muZKHh1Shgn2oL1rUHOf8eencucyDubN+j3t6SkFBpultUJBZ4uPNOARRUSZUHDhgPnBJKyQkfZivWdO8B6//fjMkJUnHj6cP5WnX0dHOeR+ZvbdSpewD+ZXh3LYdFJT+g4hGjeLVp4+vxozx1gMPSHXr5l6tKBySk013jGHDzB1yyVyjL78s9emT/RYupUubn3Wvvy698YY0dar066/m98d/MyYByGe8//sELyYmRv7+/i6uBq4UExMjKfWayC6mg/sP08HlzPPPS5MmST16mGaDMOLizB910dHmDkp+v+Oekc2bpVdfTdJvvyXr7NnMfyBVqpQa5G3BvlYtEzhtEhOlTZtSg/rmzfYBt0gRqXXr1LBepUouvjGZwaIOHUoN8pGRpi+1bds2vVN2+fmZO/ppl+Bgs7aF8LSBPKPn/P0zvnNutZoPOvbuTb8cPpz5Bwfe3qafblyc9M8/WRsj4LrrTLioXNn8O1eubFqY+PqaDwG8vbO3DgjI2Yddly7FqF27eP3ySzE1bmz6wOfwdyYKqWPHTH/1WbNMyx/J/D998UXTRSyr0/xm5Xf44sVmsLpz58wHbJ99Zn7mAbnFXf+2LAiOHz+u8+fPq1SpUgoICJAlp03dCpGkpCRdvnxZvr6++XY6OKvVqpiYGJ06dUrFihVT2bJlM9wvqzmU4P4fgnvO/PST1KqVVLKkuUOXT/9/Od1330n33Wfuyh4+XDDuuGfEdl2WLFlLhw8HaPduczfqjz/MYHEnTmT+2vLlTZAPDDTXUVSU/dcbNDB/tN55p/ngIztN03OD1WruyKcN8rYwX7x4+kCeUUB3Vf/zmBjTQubKQL9vX/oPI7y8zPWbNpSnXedm94iciomJ0Zo1f6lr13o6f96i0aOlV15xdVXIL06ckL7+Wpo/X1q7NvXDriJFpOeeMx9YOzoGRlZ/hx86ZFo2bd5sPph79VVzN57frcgN7vq3ZUFgtVp14sQJnc9OX71CLjk5WYmJifLy8pJHPv8DulixYipTpkymH9xkNYfSVB5OcfPNJoicPm2a9zVr5uqK3IOtmfyDDxbc0J7WddeZIHfLLfbPnz0r7dmTGuRtof7o0dTFJiREatvWBPW2bc0Ueu7IYkltpp3frveAAPOBSIMG9s8nJ5sBtvbvN/tUrmy+//k5LJQsmaC33opXr16+GjFCuvdeyc0/n4ULnT5twvoXX5hBV9OOuXDTTWYQuW7dzM+63BQaaj4seO45M0vCqFGmxcjnn5sPyAHkDxaLRWXLllWpUqWUkJDg6nLyldjYWEVGRqpSpUr5uquBt7e301oMENzhFN7eJmjNn2+mhctvQSY3xMZK339vtvPraPLOEhIiNW9ulrTOn08N9GfPSi1amFGV83NQzM88PFKbvBckXbsm6fvvzcwXPXtKGzfSZB6pzpwx/dbnzzetftIOetm0qfn53bmzVLFi3tbl62tm7WjeXOrdW1qxQmrY0HyoUBC7XQEFmaenZ75t7u0qyf99curr6yu//DZFTi4pBPcAkVfuvtusFy50bR3uYulSM11XpUpmuh+kV6yY+ZDniSekF14wfyTzew3OZrFI771nujBs3Sq9+aarK4KrnTsnffyx1K6daTXTq5cJxklJUuPG0vjxphvMxo2mSXxeh/a0Hn5Y+u03M3jk0aNmIM4xY8w4FACAwoPgDqdp187csdu50/TnLuzSNpNnLBLAtcqWlaZMMdsjR0q//+7aepD3Ll6U5swxHzKXLi09/rj5gDUxUYqIMGH4zz9Nv/IXXjDN1d1F7dqmG9pDD5l6X3lFqlFD+uQT+xYCAICCi+AOpylRIrX53qJFrq3F1WJiUlseFPZm8oC76NZN6tDBzBffs6dZo3BYtMhMW/roo2bU9oQEMz3gyJFmYMZt26ShQ6Vq1VxdaeaKFjVzx3/yiRkw8u+/zUwujRqZDyAYahgACjaCO5zqnnvMurAH9x9+MFOJhYaaPtsAXM9ikd5914y5sG2bNHasqytCbjt/3nxIc889ZpT40FAzOvvu3aZ12GuvSeHhLi7SARaLmSpu/37T5SM42LQeaddOuv12acsWV1cIAMgtDgf3AwcO6LHHHlNERISaN2+u8ePHKz4+/pqvGzx4sNq2bauIiAjdcMMNevjhh7V27Vq7fX7//XcNHTpUbdq0UYMGDdS2bVtNnDgxZdJ6mylTpig8PDzdMnfuXEffDpzMFtxXrTLNEgsrmskD7qlMGWnqVLM9alTqnNwoeJYskerUkWbPNj+HBw82A2EOH26anudn/v5mDvnISGnQIDNN5qpV5oPibt1M//zcZLVK8fHc5QeAvOTQqPJRUVHq0aOHQkNDNWXKFJ08eVLjxo1TXFychg0bdtXXJiQkqGfPngoNDdXly5f11VdfqXfv3vrkk090/X+3JJcsWaLDhw/rySefVGhoqP766y+988472rFjhz755BO74/n5+Wn27Nl2z1V05egxkGQGzwkLM39MrFhh5jAvbC5dSm1x8NBDrq0FQHpdukhffmlGEu/Z0/Qd9vFxdVVwlqgoE2Y//NA8rl7dDER35awWBUFIiDRhgvT006b1wGefmeb0X30l9etn5n931tR1tt/rK1ea5cwZ87yHh5mlwdtb8vKyX2f0nG3t5yfddpv0yCOm6T8A4OocCu7z5s3TpUuXNHXqVBUrVkySlJSUpBEjRqhPnz4qXbp0pq/93//+Z/e4RYsWat26tb777ruU4N6rVy+FhISk7NO0aVMFBQVp8ODB2rVrl+rWrZvyNQ8PD0VERDhSPvKAxWLuuv/vf6aPd2EM7osXm6ngqlY1U/cAcC8Wi5kbe80aaccOMyjZ8OGurgrOsGyZmaXin3/Mv/Ozz0pvvCEFBLi6stwVGmoG3hs0SHrpJfN9+N//zAcWL70kDRzo+Pfg9GlzF3/lShPYM7uLn5wsXb5sFkctWya9/LJp5t+jh3T//QX/3woAssuh4L5mzRo1a9YsJbRLUrt27fT6669r3bp16tixY5aP5enpqaJFiyohzehAaUO7Te3/2rOdOnXKkVLhQnffbf5gWLzY/EL3KGQjKdBMHnB/pUtL06aZu+9vvGE+ZOSz4PwrOto0hX//ffM4LMyE1hYtXFtXXouIkH78UVq+3AT2bdvMCPTTppmB+Hr0MHe8M3LpkvTLL6lB/cpuJF5eZvrO22+XWreWatUyI9onJJiR7tOuM9tO+9zp09L8+eacy5ebpWhRqXNnU+fNNxe+vx8A4GocCu6RkZF64IEH7J4LCgpSyZIlFRkZec3XW61WJSUlKTo6Wt98840OHz6skSNHXvU1W/4baSUsLMzu+bi4ON144426cOGCQkND1bNnTz2Yw+G7rVZruv707iY2NtZu7Y6uv14qWtRfJ09atHZtnK6/PtnVJeWZixelxYv9JVl0zz2xiokpHB0A88N1icLnWtfl3XdL993nowULvNS9e7J++SWOJvP50E8/eahfPx8dOWJSXt++CRo5MkGBgWaGD3eSVz8rmzc3LUq++MJTI0d66/BhDz35pDRxYrJGjkxQu3ZJSkqStmzx0E8/eejnnz21caOHEhLsP22uWzdZt92WpNtuS1Lz5skqUsS5dT72mHTwoEWff+6lzz/31KFDHvroI+mjj6TQ0GR165akbt0SVaVK4fhd6ir8Doc7KkzXpdVqlSULd/scCu4XLlxQUFBQuueDg4MVFRV1zdd/9dVXevXVVyVJAQEBmjRpkhpepS3x2bNnNWXKFLVu3VqhaSZUrVSpkgYPHqzatWvr8uXLWrhwoV577TVFR0friSeecOQt2UlISNCePXuy/fq8dOjQIVeXcFVNmoRp5cri+uSTcwoMPObqcvLMjz8WV1xcmCpVipO39x/KJ5eT07j7dYnC6WrXZb9+Xvr559ratctbL7xwXn37Hs+7wtzA5csWnTvnpfPnU5dz57z/W6c+FxfnoWrVYlW79iXVrXtJ1arFZnrnNq/ExHhoypTy+vLLUpKkcuUua9iwQ7r++os6csS1tV1LXv2sbNBAmjvXoi+/LKmPPiqrPXu81Lmzr8LCYnXypI8uXfK0279Mmctq2jRaTZpc0A03RCskJDHla3//nXt1duxoWr1s315EixaV0MqVxXXokKfGjPHQmDHeatgwWu3bn9Htt59TkSKF52ZAXuN3ONxRYbkufbJw58BitWZ9TNA6dero2WefVe/eve2ev/vuu9WwYUONGjXqqq8/e/asjh49qnPnzmnp0qVauHChpk6dqpYtW6bbNyEhQb169dKBAwf09ddfq1SpUlc99oABA7R+/Xpt2LBB3t7eWX1LKXbu3Cmr1apq7jyJq8ynTocOHVJoaKj8/f1dXU6mPvvMU717+6p+/WRt2BDn6nLyTNeuPvr+ey+9+GKCXn+98EwSnV+uSxQuWb0uv/7aU48+6itPT6tWr45Tw4YF5+7e5cvS5597at8+D/37r0Vnzlj077/6b23RpUvZ68/j62tVgwbJatzYLNdfn6yqVa151rT5l1881Levjw4dMifs1StBo0cnOP2OsLO58mfl+fPS2297a9o0L8XFmX/3kBCrWrZM0m23JevWW5MUFmZ1iy5eMTHS99976rPPvPTTTx6yWk1R/v5W3XNPkh5+OFG33ZYsT89rHAhZwu9wuKPCdF3+9ddfslgsqlev3lX3c+jz8qCgIEVHR6d7PioqSsHBwdd8fUhISEo/9hYtWigqKkpvvfVWuuButVr18ssv6/fff9fnn39+zdAumb72P/74o44cOaKqVatm8R3Zs1gsCsgno6L4+/u7da333Sf16SP9/ruHzpwJUGEY8P/CBdO3UJIefthbAQGOf4CU37n7dYnC6VrXZffuZjDNL7+06Kmn/LV5c/4fZd5qNeOMDBwoHThw9X29vKSSJc3o45mtvbxMf+lff5V++006f96iX3/11K+/pianYsVMV6kmTcxyww1SuXLOfV+XLklDh0pTppjHlSqZ0eNvv91bUv75meuKn5UBAWYE+oEDzaBzdetKEREWeXi4uOlEBgICpMcfN8s//0iffmqm9du716IvvvDSF194qXx5M5ZM8+bmeqtQgXFlcorf4XBHheG6zEozecnB4B4WFpauL3t0dLROnz6drg96VtSpU0dr1qxJ9/ybb76pJUuWaObMmapZs6bDx4XrlSxpBrFZv9788di3r6sryn0LF5q7WzVrStf4wAyAm5k2Tfr5Z2nnTjO/+zUakLm1ffuk554z85hLZu76hx+WSpVKDeNpg3lQUNYCj22IG6tV+usvE+JtQX7rVnNHd8UKs9iUL28CfJMmZsA4R6cMS7u9c6cZMd72QUSvXiaIZtCDD1dRoYL06KOuriLrKlSQhgwxg+399psJ8HPnSkePSpMmmUUy13nTpqkfHF1/vfkwCQAKCoeCe4sWLfTuu+/a9XVfunSpPDw81DwbE6Ru2bIl3dzr77//vmbNmqUJEyaoWbNmWT7WDz/8oKCgIFWqVMnhOpA77rnHBPeFCwtHcGc0eSD/KllSmj7djGg9dqzUoYP5wz8/uXDBfOAwebIZvdvbW3r+eTOqeNGizjuPxWLmRq9e3XwgIJlRwnfuNMHKFuj/+MOEq6NHpQULnHf+ChWkDz6Q7rjDeceE+7NYUkP5229LixaZ6eR+/dVceydOSN99Zxab8PDU1zRpYvr8+/q67j0AQE44FNy7dOmiOXPmqH///urTp49Onjyp8ePHq0uXLnZzuPfo0UPHjh3T8uXLJUk///yzFixYoFtvvVVly5ZVVFSUFi1apLVr1+rtt99Oed3ChQs1ceJE3XvvvapQoYK2p5mLpFKlSinN7Dt27Kj77rtPYWFhiouL08KFC7Vs2TK9/PLL2erfjtxx992mSePKlaZ5Y2CgqyvKPVFR0tKlZjuHkxsAcJFOnaSHHjJTVPXsKW3Zkj/+yE9ONnN4v/SSdPKkea59e3Mnsnr1vKnB21tq1MgsffqY5y5eNHfibXflT53K2jRhVz6X+N/4aJ6eZpqwt9+WstA7DwWYr69pAWJrBRITk9qVw7ZERprWJ/v2mf8fkukCExFhH+Zr1ODDdgD5g0PBPTg4WLNnz9aoUaPUv39/BQYGqlOnTnruuefs9ktOTlZSUlLK44oVKyo+Pl4TJ07UuXPnVLx4cYWHh2vOnDlq0qRJyn7r1q2TJH3//ff6/vvv7Y45duzYlHniK1WqpFmzZunff/+VxWJRjRo19NZbb+nee+917N0jV9WpI4WGSocOmfBekP95vv9eio+Xatc27xtA/jR1qvTTT9Lu3Wbe6zfecHVFV/fbb9Izz0ibNpnH1aubO+533eXSsiRJRYqYedRzOpe61WrmC7dazQcEwJUCAkxf97SNP//9174FyKZN0pkzqY9t+vSR3n0372sGAEc5NKp8QbZz505JuuZofq4WExOjPXv2qFatWvlioIZnnjF/CPfqJb3/vquryT333GOa7Q0fLr3+uquryXv57bpE4ZDd6/Kbb8ydPE9PacMG00fb3Zw8aVo0ffyxeVykiDRsmPTss/l/YL2CjJ+VrmO1SgcPpgb3tWtNsC9TRjpeuGaBTIfrEu6oMF2XWc2h7jeUKAqUe+4xwX3RItOcM6+mCspL58+njibfubNLSwHgBB07Sl26SPPmSe3a6ZqzYlytma2Hh1SlilS/vulfW7++VLly9pvmxsebn6kjRpg+7ZIZaGzcOKls2ewdEygMLBYzQGJYmPn/HR1tBjY8ccLciS9RwtUVAsDVEdyRq1q2NHeCjh83/c8aN3Z1Rc63YIHph1m3rmkqDyD/mzpVWr3a/Ow6cyZnx9qyRfrqq9THQUH2Qb5BA/Pz41rjgPz4o5nKa+9e8/j66820aDfemLP6gMKoaFHzIdrhw6ZrTE67dABAbiO4I1f5+kpt25qmpwsXFszgnnY0eQAFQ4kSZmC1HTuuvt+1OpslJJjBsX7/3Sx//GHulK9daxYbi0WqWtU+zNevb8YJiYw0o8Pbhn4pWdLcYe/Zs2C2YgLySp06BHcA+QfBHbnu7rtNcLf1AS9Izp6V/ps8geAOFDBlypglp+65J3U7Pt4E+R07UsP8jh2mue5ff5nl669T9y9aVLp82bzOy8uMGzJsGPNTA85Qp470ww8muAOAuyO4I9fddZe5m7Rli3TsmFSunKsrcp4FC8xURQ0amPliAeBqfHykevXMktapU6lB3hbm//jD9MOVTMulyZOlWrXyvGSgwKpb16x37XJtHQCQFQR35LrSpc1cqZs2SYsXmxHmCwqayQNwhlKlpNtvN4tNQoK0f79ZN2jAXNOAs9mmb+WOO4D8gN5xyBO2pqILF7q2Dmc6c0ZascJsM5o8AGfz9jbBIiKC0A7khlq1zP+tf/81rV4AwJ1xxx154p57pFdfNUE3Nlby93d1RaaOCxekmBjp0iWzti1ZeXz4sJSUJDVsKFWv7up3AwAAHBEQYKZrjIw0d91LlXJ1RQCQOYI78kS9emYu5L//llatktq3z71zxcaaKZyOHzd96o8dy3j7/HnnnO/hh51zHAAAkLfq1jXBfdcu6bbbXF0NAGSO4I48YbGYu+7Tp5vm8jkN7r//Lv38c8ah/Nw5x44VEGDmTw4ISF2ufJzZcyVLmlHzAQBA/lOnjplqkX7uANwdwR155u67TXBftMjMfexon83Tp6XPP5dmzZK2b7/6vn5+ZvT6cuWksmUz3w4Opu8oAACFFQPUAcgvCO7IM7fdZu5SHz1qgnfDhtd+TXy8mWN11iwzIn1ionnex0dq00aqVi3jYE4gBwAA15I2uGfnpgIA5BWCO/KMn58J2999Z+66ZxbcrVYT7GfNMnfY//039Ws33CD17Cl16SKFhORB0QAAoMCqWVPy8DDd7I4fNx/+A4A7Yjo45KmrTQt38qT09ttm6qNGjaR33jGhvWxZ6YUXzMAxv/4q9etHaAcAADnn52da70k0lwfg3rjjjjx1111m/dtv0okTUvHi5u77rFnSkiVmejVJ8vWVOnQwd9fbtJG8uFIBAEAuqFNH2r/fBPc2bVxdDQBkjDiEPFW2rGnu/ttvUteuZnT4s2dTv960qQnrDz1kQj0AAEBuqlNH+vZb7rgDcG8Ed+S5u+82wf3nn83jcuWkRx+VevQwfc0AAADySt26Zr1rl2vrAICrIbgjz/XqJa1cKZUvb+6ut24teXq6uioAAFAY2UaW/+MPRpYH4L4I7shzZctKq1e7ugoAAACpRg0zls6FC9I//0gVK7q6IgBIj1HlAQAAUGj5+EjVq5tt+rkDcFcEdwAAABRqtn7uBHcA7orgDgAAgELN1s+dAeoAuCuCOwAAAAo1W3DnjjsAd0VwBwAAQKGWdmT55GTX1gIAGSG4AwAAoFCrVs0MUnfpknTkiKurAYD0CO4AAAAo1Ly9pfBws00/dwDuiOAOAACAQo9+7gDcGcEdAAAAhR7BHYA7I7gDAACg0CO4A3BnBHcAAAAUenXrmvUff0hJSa6tBQCuRHAHAABAoRcWJvn5SXFx0sGDrq4GAOwR3AEAAFDoeXpKNWuabZrLA3A3BHcAAABA9HMH4L4I7gAAAIBS+7kzlzsAd0NwBwAAAMQddwDui+AOAAAAKDW4790rJSa6thYASIvgDgAAAEgKDZUCAqT4eOnAAVdXAwCpCO4AAACAJA8PqXZts00/dwDuhOAOAAAA/Id+7gDcEcEdAAAA+A/BHYA7IrgDAAAA/yG4A3BHBHcAAADgP7a53PftM4PUAYA7ILgDAAAA/6lYUSpa1EwH9+efrq4GAAyCOwAAAPAfiyV1ZHmaywNwFwR3AAAAIA36uQNwNwR3AAAAIA1bP3eCOwB3QXAHAAAA0rDdcd+1y7V1AIANwR0AAABIwxbc//pLunzZtbUAgERwBwAAAOyUKycFB0tJSWZaOABwNYI7AAAAkIbFQj93AO6F4A4AAABcgX7uANwJwR0AAAC4AlPCAXAnBHcAAADgCgR3AO6E4A4AAABcwdbH/cABKTbWtbUAAMEdAAAAuEKpUlKJEpLVKu3Z4+pqABR2BHcAAADgChYLzeUBuA+COwAAAJABgjsAd0FwBwAAADLAXO4A3AXBHQAAAMgAc7kDcBcEdwAAACADtuB+6JB08aJLSwFQyBHcAQAAgAxcd50ZXV5iZHkArkVwBwAAADLBAHUA3AHBHQAAAMiEbYA6+rkDcCWCOwAAAJAJ7rgDcAcOB/cDBw7oscceU0REhJo3b67x48crPj7+mq8bPHiw2rZtq4iICN1www16+OGHtXbt2nT7RUdH6+WXX1aTJk3UsGFDDRgwQKdOnUq339atW/XQQw+pfv36uu222/T+++/LarU6+nYAAACATBHcAbgDh4J7VFSUevTooYSEBE2ZMkXPPfecvvjiC40bN+6ar01ISFDPnj01ffp0jR8/XsWKFVPv3r21efNmu/0GDhyodevWafjw4ZowYYIOHjyoXr16KTExMWWfw4cP64knnlDJkiX13nvvqUePHnrnnXf00UcfOfJ2AAAAgKuyBfe//5YuXHBtLQAKLy9Hdp43b54uXbqkqVOnqlixYpKkpKQkjRgxQn369FHp0qUzfe3//vc/u8ctWrRQ69at9d133+n666+XJG3btk1r167Vhx9+qJtvvlmSVKVKFd11111atmyZ7rrrLknShx9+qOLFi+vtt9+Wj4+PmjVrprNnz+rdd99V9+7d5ePj48jbAgAAADJUvLhUrpx07Jj0xx/SjTe6uiIAhZFDd9zXrFmjZs2apYR2SWrXrp2Sk5O1bt06h07s6empokWLKiEhwe74QUFBat68ecpzYWFhqlWrltasWWO3X+vWre0C+l133aULFy5o27ZtDtUBAAAAXI3trjsD1AFwFYeCe2RkpMLCwuyeCwoKUsmSJRUZGXnN11utViUmJurcuXP68MMPdfjwYT300EN2x69SpYosFovd68LCwlKOHxMTo+PHj6erIywsTBaLJUt1AAAAAFlFP3cAruZQU/kLFy4oKCgo3fPBwcGKioq65uu/+uorvfrqq5KkgIAATZo0SQ0bNrQ7ftGiRTM8/q7/PuKMjo6WpHR1+Pj4yN/fP0t1ZMZqtSomJibbr88LsbGxdmvAHXBdwh1xXcLdcE3mX9Wre0ry1e+/Jykm5rKry3Eqrku4o8J0XVqt1nQ3rjPiUHDPqdatW6tmzZo6d+6cli5dqoEDB2rq1Klq2bJlXpaRqYSEBO3Zs8fVZWTJoUOHXF0CkA7XJdwR1yXcDddk/hMQECippnbuTMo3fys6iusS7qiwXJdZGaPNoeAeFBSUcsc7raioKAUHB1/z9SEhIQoJCZFkBqeLiorSW2+9lRLcg4KCdOLEiase33ZH/so64uPjFRsbm6U6MuPt7a1q1apl+/V5ITY2VocOHVJoaKj8/f1dXQ4giesS7onrEu6GazL/Kl/erE+f9lGZMrVUvLhr63Emrku4o8J0Xf71119Z2s+h4J62r7lNdHS0Tp8+na7PeVbUqVPHbtC5sLAwbdiwIV1zgYMHD6pGjRqSTBP7smXLpqvj4MGDslqt2arDxmKxKCAgINuvz0v+/v75plYUHlyXcEdcl3A3XJP5T0CAVLGimRLu4MGAlCBfkHBdwh0VhusyK83kJQcHp2vRooXWr1+vC2kmsVy6dKk8PDzsRoLPqi1btqhixYp2x4+KitKGDRtSnjt48KD++OMPtWjRwm6/lStX2o1I/8MPPygoKMiuzzwAAADgDAxQB8CVHAruXbp0UWBgoPr376+1a9fq66+/1vjx49WlSxe7Odx79OihNm3apDz++eefNXDgQC1YsECbNm3SsmXLNGDAAK1du1b9+/dP2a9hw4a6+eab9fLLL2vJkiVatWqVBgwYoPDwcLVt2zZlvyeeeEJnz57VoEGDtGHDBs2ePVsffvih+vbtyxzuAAAAcLq6dc2a4A7AFRxqKh8cHKzZs2dr1KhR6t+/vwIDA9WpUyc999xzdvslJycrKSkp5XHFihUVHx+viRMn6ty5cypevLjCw8M1Z84cNWnSxO61kydP1tixYzVs2DAlJibq5ptv1quvviovr9RSK1eurA8//FDjxo1T7969FRISogEDBujxxx/PzvcAAAAAuCrmcgfgSg6PKl+1alXNmjXrqvvMmTMn3WumT5+epeMXLVpUY8aM0ZgxY666X6NGjfTFF19k6ZgAAABATtBUHoArOdRUHgAAACiMatUy61OnpH//dW0tAAofgjsAAABwDUWKSFWqmG3uugPIawR3AAAAIAvo5w7AVQjuAAAAQBbQzx2AqxDcAQAAgCwguANwFYI7AAAAkAVp53K3Wl1bC4DCheAOAAAAZEHNmpKHh3TmjHTypKurAVCYENwBAACALPD3l8LCzDbN5QHkJYI7AAAAkEX0cwfgCgR3AAAAIIvS9nMHgLxCcAcAAACyiLncAbgCwR0AAADIorRN5RlZHkBeIbgDAAAAWRQeLnl6SlFR0rFjrq4GQGFBcAcAAACyyNdXql7dbNPPHUBeIbgDAAAADmBkeQB5jeAOAAAAOIAB6gDkNYI7AAAA4ADuuAPIawR3AAAAwAG2udz/+IOR5QHkDYI7AAAA4IDq1SVvbyk6Wvr7b1dXA6AwILgDAAAADvD2lmrUMNsrV7q2FgCFA8EdAAAAcFDbtmbdu7f08ceurQVAwUdwBwAAABw0dqz08MNSYqL0+OPS66/T3x1A7iG4AwAAAA7y9ZXmzJFeecU8HjlS6tlTio93aVkACiiCOwAAAJANFos0erQ0c6bk6Sl98onUrp0UFeXqygAUNAR3AAAAIAeefFJatEgqUkRatUq6+WZGmwfgXAR3AAAAIIfuvFNas0YqW1batUu68UZp+3ZXVwWgoCC4AwAAAE7QsKG0caNUp4507Jh0yy3Sjz+6uioABQHBHQAAAHCSSpWktWul226TLl6U2reXPvzQ1VUByO8I7gAAAIATFSsmLV0qde8uJSWZPvCvvcZ0cQCyj+AOAAAAOJmPjzR7tvTqq+bx6NFSjx5MFwcgewjuAAAAQC6wWKRRo6QPPjDTxc2ZYwaxO3/e1ZUByG8I7gAAAEAueuIJafFiM13cTz+Z6eKOHHF1VQDyE4I7AAAAkMvuuEP65RepXDlp924zXdy2ba6uCkB+QXAHAAAA8kBEhJkurm5d6fhxqUULcyceAK6F4A4AAADkkYoVzZ33Vq3MdHF3322a0p875+rKALgzgjsAAACQh4oVk5YskZ55xjz+6COpVi3pq6+YMg5AxgjuAAAAQB7z8ZHeeUdau1aqWVM6eVLq3Fm6/37p6FFXVwfA3RDcAQAAABdp3lzavl167TXJy0v67jupdm3pvfek5GRXV3dtp09LkydLkZGurgQo2AjuAAAAgAv5+kojR0pbt0pNm0oXLkh9+0q33Sbt3+/q6jKWmGhaDFSvLj33nPTii66uCCjYCO4AAACAG6hXT1q3ztzBDgiQ1qyR6teXxo6VEhJcXV2qn34yI+Q/+6wUFWWe27PHpSUBBR7BHQAAAHATnp4mEO/ebeZ+v3xZevll6YYbpM2bXVvbkSPSgw+aEfF375ZKlDBN/CXTVD4/NO0H8iuCOwAAAOBmQkPNyPNz5piAvGOHaUY/eLAUE5O3tcTGmqb8NWtKX34peXhI/fubZvyvvWY+bIiLM3PTA8gdBHcAAADADVks0iOPSH/8IXXrZu5oT5xomtSvWJH757dapW+/NYPlvf66CfAtW0rbtklTp0ohIZK3t1S5stn/r79yvyagsCK4AwAAAG6sVCnps8+kRYukihVNs/Q2baTHH5fOns2dc+7ZY5rqd+woHTokVaggzZtn+rfXr2+/b7VqZn3gQO7UAoDgDgAAAOQL7dubvuVPP23uxn/8sVSrlvTYY2ZAu1WrpH//zdk5oqKk55834Xz5cjPf/CuvSHv3Sg89ZM57papVzZrgDuQeL1cXAAAAACBrihaVpkyRunaVnnzS3BmfNct+n3LlTPCuX19q0MCsw8NNs/bMJCebDwKGDJFOnTLPdehgmubbgnlmCO5A7iO4AwAAAPnMTTeZvuZLl0rbt5vB637/3YTnY8fMsnRp6v4+Pqavui3I20J9YKC0a1eA+vb1TRm1vkYN6X//k+68M2u1ENyB3EdwBwAAAPIhX19zV7xDh9TnoqOlXbtSg7xtiY42AX/7dvtjlCzpr9Ona0mSihQxg9ANGGCCflYR3IHcR3AHAAAACoiiRaVmzcxik5wsHT6cGubT3p0/fdp0Wu/WLVETJnipbFnHzxkWZtbnzpnB8kJCnPBGANghuAMAAAAFmIeHVKWKWe67L/X5ixelzZvjdObMX2rXLkwBAdmLBoGBUpky0okT5sMAgjvgfIwqDwAAABRCRYpITZokKzT0co6PxZRwQO4iuAMAAADIEfq5A7mL4A4AAAAgRwjuQO4iuAMAAADIEYI7kLsI7gAAAAByhOAO5C6COwAAAIAcsQX3o0el2FjX1gIURAR3AAAAADlSooQUFGS2Dx50bS1AQURwBwAAAJAjFkvqlHB//eXaWoCCiOAOAAAAIMfo5w7kHoI7AAAAgBwjuAO5h+AOAAAAIMcI7kDuIbgDAAAAyDGCO5B7CO4AAAAAcswW3A8dkpKSXFoKUOAQ3AEAAADkWPnyko+PlJAg/f23q6sBChYvR19w4MABjR49Wtu2bVNgYKA6dOiggQMHysfHJ9PXnDp1SrNmzdK6det05MgRFS1aVDfccIOef/55lS9fPmW/IUOG6Ntvv83wGIMGDVLv3r2vut/MmTPVokULR98SAAAAgBzy9JTCwqS9e82UcKGhrq4IKDgcCu5RUVHq0aOHQkNDNWXKFJ08eVLjxo1TXFychg0blunrdu/ereXLl+uBBx5QgwYNdO7cOc2YMUOdO3fWokWLFBISIknq16+funTpYvfaH374QbNnz04XyCtWrKgJEybYPVfV1j4HAAAAQJ6rWtUE9wMHpNtvd3U1QMHhUHCfN2+eLl26pKlTp6pYsWKSpKSkJI0YMUJ9+vRR6dKlM3xd48aNtWTJEnl5pZ6uUaNGuvXWW7VgwQI9/vjjkqRKlSqpUqVKdq+dOHGiqlWrppo1a9o97+fnp4iICEfKBwAAAJCLGKAOyB0O9XFfs2aNmjVrlhLaJaldu3ZKTk7WunXrMn1dUFCQXWiXpDJlyigkJESnTp3K9HUnT57U5s2bdc899zhSJgAAAAAXILgDucOh4B4ZGamwsDC754KCglSyZElFRkY6dOKDBw/qzJkzV23evmjRIiUnJ6t9+/bpvnb48GE1btxYdevWVceOHbVixQqHzg8AAADAuQjuQO5wqKn8hQsXFBQUlO754OBgRUVFZfk4VqtVo0ePVqlSpTIM5TaLFi1Sw4YNVbFiRbvna9WqpXr16qlatWqKjo7W3Llz1b9/f/3vf//TnXfemfU3lEFdMTEx2X59XoiNjbVbA+6A6xLuiOsS7oZrEu7I2ddluXIWSf46cMCqS5diZbE45bAoZArTz0ur1SpLFv6jODyqvDNMmTJFGzdu1AcffKCAgIAM9zlw4ID++OMPvfbaa+m+1qNHD7vHrVq1UpcuXfTOO+/kKLgnJCRoz5492X59Xjp06JCrSwDS4bqEO+K6hLvhmoQ7ctZ1GR9vkcXSUBcvWrR+/Z8KCUl0ynFROBWWn5dXm6HNxqHgHhQUpOjo6HTPR0VFKTg4OEvH+OKLLzRt2jS98cYbatasWab7LVy4UF5eXrrrrruueUwPDw+1bdtWb731luLi4uTn55elWq7k7e2tatWqZeu1eSU2NlaHDh1SaGio/P39XV0OIInrEu6J6xLuhmsS7ig3rsvy5a365x+LPD3DVatWslOOicKlMP28/Ouvv7K0n0PBPSwsLF1f9ujoaJ0+fTpd3/eMLF++XMOHD9eAAQPUqVOnq+67ePFiNWvWLGWquLxgsVgybQHgbvz9/fNNrSg8uC7hjrgu4W64JuGOnHldVq8u/fOPdPSon7jUkROF4edlVprJSw4OTteiRQutX79eFy5cSHlu6dKl8vDwUPPmza/62k2bNun5559X586d1b9//6vuu2PHDh05ckR33313lupKTk7W0qVLVb169WzfbQcAAACQcwxQBzifQ3fcu3Tpojlz5qh///7q06ePTp48qfHjx6tLly52c7j36NFDx44d0/LlyyWZ/ur9+/dXaGioOnTooO3bt6fsGxISkm7u9oULF8rPz09t2rRJV8PRo0c1ZMgQtW/fXpUrV1ZUVJTmzp2rXbt2acqUKY68HQAAAABORnAHnM+h4B4cHKzZs2dr1KhR6t+/vwIDA9WpUyc999xzdvslJycrKSkp5fGOHTsUHR2t6Ohode3a1W7f+++/X+PGjUt5nJSUpKVLl+q2225TYGBguhoCAwNVpEgRzZgxQ2fOnJG3t7fq1q2rmTNn6pZbbnHk7QAAAABwMoI74HwOjypftWpVzZo166r7zJkzx+5xx44d1bFjxywd39PTU2vXrs3068WKFdOMGTOydCwAAAAAeYvgDjifQ33cAQAAAOBqbMH91CkpgwmpAGQDwR0AAACA0wQHSyVKmO0rJqQCkE0EdwAAAABOVa2aWWdximoA10BwBwAAAOBU9HMHnIvgDgAAAMCpCO6AcxHcAQAAADgVwR1wLoengwOy5PJl6exZ6cyZjNfnz0ulS0s1aqQuwcGurhoAAABOQHAHnIvgjmuLjZVOnzZzepw6Zbb//Td9GE+7femS4+cpVcoE+PBw+0Bftark6+v89wUAAIBcYQvuR45I8fGSj49r6wHyO4J7YXT5sgnftjB+ZSi/cn3xYvbO4+EhFS8uhYSYOUHSroODpWPHpP37zXLiRGoNa9emP07lyvZhvkYNqU4dqXz5nH8/AAAA4FRlykgBAVJMjHT4sFS9uqsrAvI3gnt+c+aMimzeLM+DB6WEBCk62gTrixezvp2Q4Ph5fXykkiXNXfGSJaXrrjMh3BbEMwvnHlkcRuHCBenPP1ODvG3Zt8/UfPCgWX780f51N9wgdekiPfigVKGC4+8LAAAATmexmLvuO3eaKeEI7kDOENzzk8RE+TdurPDTp3N+LC8vE8DThvFSpey3066DgsxP4NwSFCQ1bmyWtKxWcxf+ykC/f7+0d6/0229mGTRIuvlmE+I7dTL95wEAAOAytuBOP3cg5wju+Ymnp5LatVPCL7/Ip0QJeQYFSUWKSEWLmnVm2xk9Fxycu0HcWSwWE8JLl5ZuucX+aydPSl99Jc2fL/3yi2liv3atNGCA1KqV9NBDUseO5u4/AAAA8hQD1AHOQ3DPTywWxc+YoT179qhWrVoKCAhwdUWuVbq01L+/Wf7+W/rySxPif/1VWrHCLE89Jd1xhwnxHTqYO/sAAADIdQR3wHmYxx0FQ8WK0vPPS5s2md8OY8ZIDRpIiYnS4sXSo4+aZv8PPCB98YUZKQUAAAC5huAOOA/BHQVPWJg0dKi0fbv0xx/S66+bKeYuX5a++cbcfS9VSurWTVq2zPSjBwAAgFPZgntkpJSc7NpagPyO4I6CrVYtafhwac8eE+SHDJGqVDHzzM+da5rRR0RIn36avdH2AQAAkKFKlSRPTykuTjp+3NXVAPkbwR2Fg8Vims6PHWvaa23aJD3zjBQYKP3+u9S9u/lYeNIkM/0cAAAAcsTbW6pc2Wz/9ZdrawHyO4I7Ch+LRWrSRHrnHTOo3RtvmIHu/v7b9JOvVEl6+WXpxAlXVwoAAJCvVatm1vRzB3KG4I7CrXhxE9IPHZLef1+qUUM6f97cma9cWerVS9q3z9VVAgAA5EsMUAc4B8EdkCQ/PxPS9+yRvv1WatZMio+XPvjA9JO/7z5p3TpXVwkAAJCvENwB5yC4A2l5eJiQvn69tHatmfvdapW++066+WapeXNpwQKGRgUAAMgCgjvgHAR3IDO2kL5nj/Tkk5KPjwn0998v1a5t7sbHxbm6SgAAALdFcAecw8vVBQBur2ZNaeZMaeRIacoUafp00++9Vy/p1VelwYOlp54yI9QD+V1SknT5sllbrVdfkpMz/5pkBoL08EhdsvMYAJCvhYWZ9blzZile3LX1APkVwR3IqrJlpTFjpKFDTZCfNEn65x/phRekN980Ab5/f6lIEVdXioImMVG6eNEs0dHp11c+d+mSCd9xcWZ9teXKfZKSXP1u7Xl4mEmAbeu029d4zs9iUe34ePn6+qZ+zWLJeMnsa/7+UsmS0nXXmXVGS0iIeT0AIJ3AQKlMGTNZz4ED0vXXu7oiIH8iuAOOKlrUTBv3zDPSp5+a6eQOHJCGDJHeest87emnpaAgV1cKdxMTI50+Lf37r1mn3U67vnDBPojHxrq68sxlFoQl+zvz2R0XIgev9ZDkn72zOngiD6lEiYxDfalS5nZTrVpmqkkCPoBCqFo1E9z/+ovgDmQXwR3ILm9v6bHHpO7dpc8/l0aPlv78U3rlFWnCBOm550y4L1bM1ZUiN8XGmpYXR46Y5fjxzMN5TgO4l5f54KhoUdOy48pt2zogwMyU4Oubulz5+Mrlyq97emYeyq8M6Fl1ZZC3NbXP6LGtqX5Skllsz2Vl+7913KVLOnL4sCpVrCg/X9+sN/NPu9g+bMlsOX/eHMv2+Gr8/aXwcBPia9Y061q1pOrVzfccAAqoqlXNmL/0cweyj+AO5JSXl/Too1K3btL8+SbA790rDRsmTZwoDRwoPfssnbryo+Rk6eRJE8j//js1nKddrhXWruTjk77ptW37uuvMEhyccTjP7+EubbP0PJAcE6PoPXuUXKuW+TAjNyQk2H9Ic+Vy8qS0f7/5UC82Vtq+3SxpeXik3pW3LbZgHxycO3UDQB5igDog5wjugLN4eUkPPyx16SJ9+aU0apT0xx/SiBGmP/yAASbElyjh6kphY7WaYPXXX2Y5cMA+lP/9twlm1xIYaJpBV6oklSuXcSC3PVekCIOuFSTe3mb8i7Jlr75fYqJ08KCZpWLvXrO2LRcupF6DCxfav65sWalOHalpU+nGG826ZMncez8AkAsI7kDOEdwBZ/P0NOH9wQelr782o9Hv2mXuxE+ebPq/Dxpkwhxyn9VqOtb9+WdqOEq7ffHi1V/v4WHCuC2Yp10qVjTr4sUJ47g6Ly/TJL56denee1Oft12fthCfNtQfO2a6Xhw/Lq1YkfqaqlVNiG/WzKzr1zcfIACAmyK4AzlHcAdyi4eH1Lmz9MADZj74kSOlHTukcePMtHL9+pmR6EuVcnWl+Z/VasKNLZBfuY6Jyfy1FotUubIZOadqVSk01D6clytnQheQGyyW1Dv2rVrZf+3CBRPkt2+XNm40y5495i/fAwekzz4z+/n5mdGe0ob5cuXy/K0AQGZswf3oUdNryD9PRg4FChb+GgVym4eH1LGjdP/9phnsiBHS1q1mBPqpU6WePaX77pNatsz/fZhz2+XLJojv3Zu67Ntn1tHRmb/Ow8OE8+rVTUCvVi11u0oVvu9wT0FBUpMmZund2zx3/rz066/Shg2pYf78eTPq09q1qa+tWNEEeNvSqJEJ+EBBkZxsuqB4eTFbQz5QooT5kXbhguk1VLu2qysC8h+CO5BXLBbTRPaee6QffjAB/rffpBkzzFKkiNS2rXT33VL79oX3TrzVagb7yiicHzyY+dRgHh7mbrktkKddh4aaQeGA/K5YMfNzom1b8zg52bQs2bgxNczv3GnGZ/j7bzPehmSa0jdoYPrIN21qPgyoXp3Ag7yTdiDHU6fM9sWLpkXUpUtmnXb7Ws9d2ZLKy8t0VfP0TN2+cn3lc15e5ndvSIjp8nStdbFi5rVwmMVifiVv3Wo+fye4A44juAN5zWIxwfyuu6SVK6UvvpAWLTJNvb/5xiwWi/nD+u67TdCvX7/g9aFOSDDNfW2h3Lbeu1c6dy7z1wUFmRG3a9Y0U2vZtqtW5c45Ch8PD/P/IDxc6tHDPHfxorR5c+od+Q0bTFDavNks06aZ/YoVMz9nbGG+aVPG3kDWJSbaB3HbTAq27Sufu9rPdWfVk5iYu+eQzEwPacN8+fJmZplWrQre72knq1rVBHf6uQPZQ3AHXMVikW6/3SzJydK2bSbAL1wobdkibdpkltdekypUSA3xt92WvzqHnT2b/s75vn3mN3dmf2TZ+p1fGc5r1pRKl+aPI+BqihSRbr3VLJJpxXL4cOrPlE2bzF/P589Ly5aZxSYszD7IR0TQxL6wSkw0rTYOHkxdIiNTt0+edPyYHh6mzbRtto2gIDNVY2Cg/Tqrz/n4SElJptaM1lf7mi3oR0eb31PnzqVfp922DWQaFWWWQ4dS39cnn0h165qZY7p1y1+/o/MQA9QBOUNwB9yBh4fUuLFZXn/djCa9eLEJ8suXS//8I737rln8/U3Yv+cec+feHQahSkyU75Ej8jh0yPxBl/bu+b//Zv66wMDUYJ42oFevzh8+gLNYLKa7SGio9NBD5rmEBOn33+3D/L59JphFRkpz55r90jaxr19fqlfPBJSiRV31buAsVqu5G542jKcN50eOmIB7NRaL/XSXpUql3077XEhI/m1qHh9vPuy6MuBv2CDNmmVmj3nySemll6S+fc0AtO7w+9mNENyBnLFYrVarq4twBzt37pQk1atXz8WVXF1MTIz27NmjWrVqKSAgwNXlIC/Exko//ZR6N/6ff+y/3rCh6TgWEmLuZJQokbqd9rnixR0bHT0x0fxRd/LkNRfr6dOyZNb3XDIDZaUN57Z1+fLcPUeu4eelg86dM03p04b506cz3rdyZRPibUG+Xj3z/5qxJK7KJddkcrIJ47t2mfEPdu2S/vjDPHe1GTck8+9ZpYr9EhZm1hUqmN8t+TWIO9O5c9KHH5oBZw8fNs95eZkPyp59VrrhBtfWdw15dV3+9JPpUVC9urR/f66dBgVEYfodntUcSnD/D8Ed+YLVau6SLVxogvyvv5rnsio4OONg7+WVPpCfOePQsZN9faXwcHnUqmXfB71GDXNnHchj/LzMIavVNAfetMkEelvoO3Ys4/29vMz/+SsDfeXKDIL3n1y9Jq1W87Pb9u9kW+/enXlAt1hMAM8omFepYqYp5N8u6xITpe++kyZPtp/l4aabTDP6++93y+lF8+pn5ZEj5seBt7e5J8FnPriawvQ7PKs51P1+egDInMVimq02aCC9+qr5I2316tSgffas/dq2ff68eb2tb15kZNbO5+FhmjeWLp35UqaMYooW1Z4zZ1SrTp0C/8MVKDQsltQA16VL6vNnzphAaAuHtoB44YIJibt3S/Pmpe5fpIgJ8bZBJKtWNeEwLMw0s6bVjeOio+3Due3f4cyZjPf38zPDeNs+TKlTx7TUqlSJQT2dyctLeuABs2zZIv3vf+b/wvr1ZqlYUXr6aalXL9MKrpApX9404oiPN8MnhIa6uiIgfyG4A/lZ6dLSgw9ee7/ERBPe04b5tOuEhIxDeVabQcbE5P6IwQDcQ4kSUsuWZrGxWs1f4lcGyT17zKBethHur1S0qAnwacO8bdt2a66wSk42XaP27Uu/HDmS8Ws8PEwgtwV0W8uHatW4vZnXGjc2g9a9+WbqtK9//236wI8YYWaBGDDAfKBVSHh6mv/ae/eaKeEI7oBjCO5AYeDlZe5sMdUTgNxgsZi7t5UqmUEzbRISzDzzO3eadWSkGZkqMtKE0uhoaccOs1zJw8Mczxbmq1Qxt+zKlk1dQkLy/x37CxdMh98rw/n+/aY9cWbKlUsf0GvXZmBPd1O2rDRypPTyy2bQx8mTTZc3W5i/807Tgq55c1dXmieqVjXB/cABM84ugKwjuAMAgNzh7W3CZO3a6b8WF2f60NuCfNpQHxlpQuuhQ2ZZtSrz45cpYx/mM3pcunTe3r1PTjaB3NY96b/F89Qpldq1S94XLpj3um+fdPx45sfx8jJJJzzcfqlVy7R8QP7h5yc99pjUs6f0888mwC9cKC1daqZknDDB9IPP7x9EXQMjywPZR3AHAAB5z88vdSDLK1mt0okT9kE+MtKE3OPHzdds3Xz+/tssV2ObtqxECdOn28fH8bVtiYlJF8jTLdHRGZbhK6liRl8oXTp9OK9Rw7QyKMzdBQoii0W67TazHDggDRsmff659Pzz5k78u+8W6HEHCO5A9hHcAQCAe7FYUu+Y33xzxvtcvmwG5rQF+bSh3rZ9/LjZxza9ZWbT2+UWX18zm0dQkBQcrKQiRRTl7a2ijRrJu27d1IBerFje1gX3ULWq9OmnZrq4QYPMfPD79knffGNaihRABHcg+wjuAAAg//H1Te1XfzXJyebu/PHjZhDN+HizXL6cvbW/vwnjWVmuuHN6OSZGB/+b3sibGTggmQ+pBg403UkeekjasMEE+QULzAB3BUza4G61FvieAYBTEdwBAEDBZZvWsmRJV1cCZK5tW+nXX6V77zWjt918s/Txx/ZTMRYAVaqYsH7xomkAU6qUqysC8g8PVxcAAAAAFHrVq5tpE++6ywze2LWr9MorptVIAeHrK1WoYLZpLg84huAOAAAAuIPgYOn776UXXzSPx4yR7r8/0wEP86Nq1cz6r79cWweQ3xDcAQAAAHfh6Sm9+aY0Z465Rf3991KzZgXmFjUD1AHZQ3AHAAAA3M0jj0hr1pjZFXbvlpo0kVatcnVVOUZwB7KH4A4AAAC4oyZNpN9+MyPNnz1rBrGbNs0MyZ5PEdyB7CG4AwAAAO6qfHlp9Wrp4YelpCTp6aelvn3N9IT5EMEdyB6COwAAAODO/P1Nn/c33zTzqb3/vnT77WZOtXzGFtxPnSpQY+4BuY7gDgAAALg7i8WMNr9woVS0qPTLL6YJ/Y4drq7MIcHBUokSZjsy0rW1APkJwR0AAADIL9q3lzZtMvOqHT4s3XSTtGyZq6tyCFPCAY4juAMAAAD5Sa1a0q+/Sm3aSDExZq73TZtcXVWW0c8dcBzBHQAAAMhviheXFi0yI83HxJg78fv2ubqqLCG4A44juAMAAAD5kY+P9PXXpq/7mTMmxB896uqqrongDjiO4A4AAADkV0WKSIsXS9WrS0eOSHfeKZ0/7+qqrorgDjiO4A4AAADkZyVLmgHqypaVdu2S7r1Xio11dVWZsgX3I0fy7XT0QJ4juAMAAAD5XWiotHSpFBRkporr1k1KTHR1VRkqU0YKCJCSk83A+ACujeAOAAAAFAT160vffy/5+koLFkhPPSVZra6uKh2LhebygKMI7gAAAEBB0bKl9PnnkoeH9MEH0rBhrq4oQ7bgzlzuQNYQ3AEAAICCpGNHafp0sz16tDR1qmvryQB33AHHENwBAACAgqZPH2nECLM9YID0xReurecKBHfAMQR3AAAAoCB67TWpXz/Tz/2RR6SVK11dUQqCO+AYh4P7gQMH9NhjjykiIkLNmzfX+PHjFX+NeRxOnTql8ePHq0OHDmrYsKFatGihQYMG6ejRo3b7bdq0SeHh4emW5557Lt0xV61apXvvvVf16tXTHXfcoa+//trRtwIAAAAUXBaL9M47UqdOUkKCdP/90tatrq5KUmpwj4w0o8sDuDovR3aOiopSjx49FBoaqilTpujkyZMaN26c4uLiNOwqA1/s3r1by5cv1wMPPKAGDRro3LlzmjFjhjp37qxFixYpJCTEbv+xY8cqLCws5XHx4sXtvr5582Y9/fTT6tSpk15++WVt3LhRr7zyigIDA3XnnXc68pYAAACAgsvTU/r0U+nMGemnn6R27aT161OTs4tUqmRKi4uTjh+Xypd3aTmA23MouM+bN0+XLl3S1KlTVaxYMUlSUlKSRowYoT59+qh06dIZvq5x48ZasmSJvLxST9eoUSPdeuutWrBggR5//HG7/atXr6569eplWseMGTNUv359jRw5UpJ044036u+//9Y777xDcAcAAADS8vWVvv1WuvVWaft2qW1bE94z+ds9L3h7S5UrmzvuBw4Q3IFrcaip/Jo1a9SsWbOU0C5J7dq1U3JystatW5fp64KCguxCuySVKVNGISEhOnXqlEMFx8fHa9OmTekC+l133aUDBw7on3/+ceh4AAAAQIEXHCwtWSJVqWLScrt20oULLi2pWjWzZko44NocuuMeGRmpBx54wO65oKAglSxZUpGRkQ6d+ODBgzpz5oyqZtBMp3fv3jp//rxKliyp9u3b69lnn5Wfn58k6ciRI0pISLBrSi8p5TiRkZGqUKGCQ7XYWK1WxcTEZOu1eSU2NtZuDbgDrku4I65LuBuuSbhcUJAs330nv1atZNm2TUn33KPYuXMluea6rFzZW5K39u5NUExMQp6fH+6rMP28tFqtslgs19zPoeB+4cIFBQUFpXs+ODhYUVFRDhU3evRolSpVSu3bt095vmjRonryySd1ww03yNfXVxs3btRHH32kyMhIvffee5KUcp4r67A9dqSOKyUkJGjPnj3Zfn1eOnTokKtLANLhuoQ74rqEu+GahKsFTJqkGn36yHPNGnk8+qg0ZoxLrsvAwFKSKmr79mjt2XMwz88P91dYfl76+Phccx+HgruzTJkyRRs3btQHH3yggICAlOdr166t2rVrpzxu1qyZSpUqpZEjR+r3339X/fr1c7Uub29vVbO12XFTsbGxOnTokEJDQ+Xv7+/qcgBJXJdwT1yXcDdck3AbtWopoVgxeXTsqOIrV6rihAnynD5d/mn+Ls8LN97oKUk6cyZYtWrVytNzw70Vpp+Xf2Wxr4hDwT0oKEjR0dHpno+KilJwcHCWjvHFF19o2rRpeuONN9SsWbNr7t+uXTuNHDlSu3btUv369VPOc2UdF/7ro5PVOjJisVjsPkhwZ/7+/vmmVhQeXJdwR1yXcDdck3ALd98tzZkja9euKvXll4pv1kw+GUzBnJts9+sOHvTk/wQyVBh+Xmalmbzk4OB0YWFh6fqyR0dH6/Tp0+n6nGdk+fLlGj58uAYMGKBOnTo5cuoUlSpVkre3d7o6bI+zUgcAAABQ6D30kBJGjZIkeb/wgpkuLg/Z/mw/d84sADLnUHBv0aKF1q9fn3J3W5KWLl0qDw8PNW/e/Kqv3bRpk55//nl17txZ/fv3z/I5Fy9eLEkp08P5+PioadOm+vHHH+32++GHH1S1atVsD0wHAAAAFDaJAwfqTLt2siQlSZ07Swfzrq95YKBUpozZPnAgz04L5EsONZXv0qWL5syZo/79+6tPnz46efKkxo8fry5dutjN4d6jRw8dO3ZMy5cvlyQdOHBA/fv3V2hoqDp06KDt27en7BsSEqJKlSpJkgYPHqzKlSurdu3aKYPTzZo1S7fffrvdvO5PPfWUHn30UQ0fPlzt2rXTpk2btGjRIk2aNCkn3wsAAACgcLFYdPiVV1TsxAl5btsm3XeftG6dVKRInpy+WjXpxAkzJdz11+fJKYF8yaHgHhwcrNmzZ2vUqFHq37+/AgMD1alTJz13RX+Y5ORkJSUlpTzesWOHoqOjFR0dra5du9rte//992vcuHGSpOrVq2vhwoX66KOPlJCQoPLly6tv377q3bu33Wuuv/56TZkyRZMnT9ZXX32lcuXKafTo0WrXrp1Dbx4AAAAo7Kx+foqfP1/+t9wi/f671LOn9OWXUhb73uZE1arS2rXccQeuxeFR5atWrapZs2ZddZ85c+bYPe7YsaM6dux4zWP36dNHffr0yVIdrVu3VuvWrbO0LwAAAIDMWcuXl77+WrrtNrN+4w3p1Vdz/bxVq5o1wR24Oof6uAMAAAAooJo3l6ZPN9uvvSZ9912un5LgDmQNwR0AAACA8eST0tNPm+1HHpF2787V0xHcgawhuAMAAABI9fbb0q23ShcvSh06SGfP5tqpbMH96FEpNjbXTgPkewR3AAAAAKm8vc3gdJUrm1vhXbpIiYm5cqoSJaSgILOdhzPRAfkOwR0AAACAveuuM33cAwKk5cull17KldNYLFLNmmZ727ZcOQVQIBDcAQAAAKTXoIE0e7bZfvtt6ZNPcuU0LVqY9apVuXJ4oEAguAMAAADIWKdOZoR5SerdW/r1V6efwjbD88qVktXq9MMDBQLBHQAAAEDmhg+X7r1XunxZuv9+6fhxpx7+lltMt/rDh6XISKceGigwCO4AAAAAMufhIc2ZI9WuLR07JnXsKMXFOe3wgYHSjTea7ZUrnXZYoEAhuAMAAAC4uqAgM1hdsWLSxo3SU085tV27rbk8/dyBjBHcAQAAAFxbtWrS/PnmDvysWdKUKU47dKtWZr1qlZSc7LTDAgUGwR0AAABA1rRtK02YYLaff95pbdubNjUzz50+Le3a5ZRDAgUKwR0AAABA1g0cKD36qJSUJD34oFNGlPPxSZ0Wjn7uQHoEdwAAAABZZ7FI770n3XCDdPas1KGDdPFijg9LP3cgcwR3AAAAAI7x85O+/VYqU8a0bX/kEXMHPgds/dxXr5YSE51QI1CAENwBAAAAOK58eRPefX3NiPNDhuTocBERUkiIFB0t/fabc0oECgqCOwAAAIDsufFG6eOPzfaECdLMmdk+lIeHdNttZpt+7oA9gjsAAACA7OvaVRoxwmz36yetWJHtQ9n6uRPcAXsEdwAAAAA589prpp97YqLUqZO0Z0+2DmPr575+vRQb68T6gHyO4A4AAAAgZywW6YMPpJtvlqKipPbtzaTsDqpRw3Sdj4+X1q3LhTqBfIrgDgAAACDnfH3NYHVhYdLBg9J990lxcQ4dwmKhuTyQEYI7AAAAAOe47jpp8WIpONi0d3/iCclqdegQBHcgPYI7AAAAAOepWVP6+mvJy0v6/HNp5EiHXm7r575li3T+vPPLA/IjgjsAAAAA52rdWpoxw2wPH24CfBZVqGD6uicnS6tX5055QH5DcAcAAADgfE8+Kb3wgtl+7DGHRpujuTxgj+AOAAAAIHeMG2cGqYuPN+vIyCy9jOAO2CO4AwAAAMgdHh7Sp59KjRpJ//5rponLQsf1W281I8z/8Yd04kSuVwm4PYI7AAAAgNwTGCgtXGgmaN+7V+rcWUpIuOpLSpSQIiLM9qpVuV8i4O4I7gAAAAByV7ly0qJFJsSvWCH173/NaeJoLg+kIrgDAAAAyH0REdLcuaYN/MyZ0ttvX3X3tMHdwanggQKH4A4AAAAgb9xzT2pgf+EF6bvvMt31llvMVPCHD0sHD+ZRfYCbIrgDAAAAyDvPPis99ZS5jd6tm7R1a4a7BQZKN95otmkuj8KO4A4AAAAg71gs0jvvSG3bSjEx5i780aMZ7ko/d8AguAMAAADIW15e0hdfSLVrS8eOmfB+6VK63WzBfdUqKTk5j2sE3AjBHQAAAEDeCw6WFi+WSpWStm2Tnnsu3S5Nm0oBAdLp09KuXS6oEXATBHcAAAAArhEaaj/S/Fdf2X3Zx8cMUicxnzsKN4I7AAAAANdp1Up66SWz3auXdOSI3Zfp5w4Q3AEAAAC42siRUpMm0vnz0iOPSElJKV+yBffVq6XERNeUB7gawR0AAACAa3l7S59/LhUtKv3yizRmTMqXIiKk4sWl6Gjpt99cVyLgSgR3AAAAAK5Xtao0fbrZHjFCWr9ekuThId12m3mafu4orAjuAAAAANzDI4+kNpXv1s00nRf93AGCOwAAAAD3MW2aFBYmHT4s9e0rWa0pwX39eik21rXlAa5AcAcAAADgPoKCzBRxXl7S/PnSrFmqUUMqX166fFlat87VBQJ5j+AOAAAAwL00aWJGmpekZ56R5c/9atXKPMyNfu7Hjknvvy/Fxzv/2IAzENwBAAAAuJ8XXzSj0l26JHXtqjYtLktyfj/32FipbVupTx9pwgTnHhtwFoI7AAAAAPfj6SnNmSOVKCFt3ar7fntFkrR5c8qYdU7x0kvS7t1m+913mSse7ongDgAAAMA9lS8vffihJKno+xP1WPllSk6WVq92zuF/+EGaMsVsBwZKf/8tLV7snGMDzkRwBwAAAOC+OnSQ+vWTJE06+6hK6pRTmsufPCk99pjZHjhQevpps22bSh5wJwR3AAAAAO5twgSpbl0Fx57Ux3pMq1Zac3Q4q1V6/HHp1CmpXj1p7FjTx91ikZYtk/7800l1A05CcAcAAADg3vz9pblzZfXzU3v9oNZ/vKMTJ7J/uOnTTTN5X1/p888lPz+pShXprrvM19991zllA85CcAcAAADg/urWlWXiREnSeL2orR9tz9Zhdu+WBg8222+9JdWtm/q1/1rk6+OPpZiYHNQKOBnBHQAAAED+8NRT2lX1XvkqXhHju5qp4hxw+bLUrZsUFyfdeWdqv3abO+4wd97PnZPmz3di3UAOEdwBAAAA5A8Wi06M/lBHVU7lovZKzz3n0MuHDpV+/10qWVKaNcv0aU/L01Pq29dsM0gd3AnBHQAAAEC+cePd16mnxxwlyyLNnCl99VWWXrdsmTRpktn++GOpdOmM93v8cdP3ffNm6bffnFQ0kEMEdwAAAAD5RpEiUtxNrfSmXjJP9OplJmC/in//lXr0MNv9+0vt22e+73XXSQ8+aLa56w53QXAHAAAAkK+0bi0N00j9FdJEOn9eeuQRKSkpw32tVunJJ6UTJ6RatcyAdNdiG6Ru3jzpzBnn1Q1kF8EdAAAAQL7SqpWUKG910+eyFi0qrVkjjRmT4b4zZ0rffSf5+Jip3/z9r338pk2lhg3NIHazZjm3diA7CO4AAAAA8pUbb5QCAqTfzlbVP0P/a88+erT01192++3dKw0caLbHjpUiIrJ2fIsl9a77jBlScrJTygayjeAOAAAAIF/x8ZFuucVsf+33sNS2rRQfLz3/fMo+8fHSww9LsbHS7benBvis6tpVCg6WDhyQli93Xu1AdhDcAQAAAOQ7rVub9cpVFmnyZMnLS1q4UFq6VJL02mvS1q1SSIg0e7bk4WDyCQyUevY02wxSB1cjuAMAAADId1q1MuvVq6XE6rWkZ54xTwwcqJ9+jE8ZhO7DD6Vy5bJ3jqeeMutFi6TDh3NWL5ATBHcAAAAA+U5EhFS8uBQdbeZc17BhUsmS0r59WvPgVFmtUu/e0n33Zf8c4eHmzn5ysvTee04qHMgGgjsAAACAfMfTU7rtNrO9cqWkYsVkfcOMLD/wwgg1Czupt9/O+Xlsg9R98IF0+XLOjwdkB8EdAAAAQL6U0s99pVnP9nhMW9RIwbqg7+u9osDAnJ/j3ntNU/vTp6Wvv8758YDscDi4HzhwQI899pgiIiLUvHlzjR8/XvHx8Vd9zalTpzR+/Hh16NBBDRs2VIsWLTRo0CAdPXrUbr/169frueeeU6tWrdSgQQPddddd+uCDD5SQkGC335AhQxQeHp5uWbNmjaNvBwAAAEA+Zevnvn69tHOn9PSznhqgdyRJ133/0X9t6HPGy0vq08dsM0gdXMXLkZ2joqLUo0cPhYaGasqUKTp58qTGjRunuLg4DRs2LNPX7d69W8uXL9cDDzygBg0a6Ny5c5oxY4Y6d+6sRYsWKSQkRJI0b948xcXFacCAASpbtqx27NihKVOm6MCBAxo7dqzdMStWrKgJEybYPVe1alVH3g4AAACAfCw83NwNP3bMTPl26ZLkc2tzJZd7WB6ffyYNGCCtW2cmZs+BJ5+URo0yh9qxQ2rQwElvAMgih4L7vHnzdOnSJU2dOlXFihWTJCUlJWnEiBHq06ePSpcuneHrGjdurCVLlsjLK/V0jRo10q233qoFCxbo8ccflyQNHz48JcRLUtOmTZWcnKzJkyfrhRdesPuan5+fIiIiHCkfAAAAQAFisZjm8nPmSKdOScWKSZ98Inl4vCl9t0DasEH67DPpkUdydJ5y5aT775e+/FKaMUN6912nlA9kmUNN5desWaNmzZqlhHZJateunZKTk7Vu3bpMXxcUFGQX2iWpTJkyCgkJ0alTp1KeSxvMbWrVqiWr1arTp087UioAAACAQsDWz12S3n9fqlhRUvny0ssvmydfekm6eDHH57ENUvfpp1JUVI4PBzjEoeAeGRmpsLAwu+eCgoJUsmRJRUZGOnTigwcP6syZM9ds3r5161b5+PioQoUKds8fPnxYjRs3Vt26ddWxY0etWLHCofMDAAAAyP/uu09q2VJ69VWpc+c0X3j+eSkszLSjHzMmx+dp2VKqVcs0x58zJ8eHAxziUFP5CxcuKCgoKN3zwcHBinLgYyer1arRo0erVKlSat++fab7HTp0SJ988om6dOmiwDRDQtaqVUv16tVTtWrVFB0drblz56p///763//+pzvvvNORt5SurpiYmGy/Pi/ExsbarQF3wHUJd8R1CXfDNQl3VBCuS29v6YcfzPaVf8p7jh0r34ceknXiRMV17SprDsfEevJJLw0a5KNp05L12GNxOe06j0wUhOsyq6xWqyxZuJAcCu7OMmXKFG3cuFEffPCBAgICMtzn4sWLeuaZZ1ShQgU999xzdl/r0aOH3eNWrVqpS5cueuedd3IU3BMSErRnz55svz4vHTp0yNUlAOlwXcIdcV3C3XBNwh0V2OsyLEzVmzZV0KZNuvz00zqQw4ndGzf2kL9/fe3d66lPP/1b11+f8yb4yFyBvS6v4OPjc819HAruQUFBio6OTvd8VFSUgoODs3SML774QtOmTdMbb7yhZs2aZbhPfHy8+vfvr6ioKM2fPz/TcG/j4eGhtm3b6q233lJcXJz8/PyyVMuVvL29Va1atWy9Nq/Exsbq0KFDCg0Nlb+/v6vLASRxXcI9cV3C3XBNwh0VhuvSMn26rE2bqtiaNapz9KiSb789R8fr1i1ZH37oqWXLqqp796tPi43sKQzXpc1ff/2Vpf0cCu5hYWHp+rJHR0fr9OnT6fq+Z2T58uUaPny4BgwYoE6dOmW4T3JysgYPHqzdu3frs88+U9myZR0pMUcsFss1PyRwF/7+/vmmVhQeXJdwR1yXcDdck3BHBfq6bNRIevppafJk+b30kvT776Z9fTY984z04YfS99976fx5L5Ur58RaYadAX5f/yUozecnBwelatGih9evX68KFCynPLV26VB4eHmrevPlVX7tp0yY9//zz6ty5s/r375/pfiNGjNBPP/2k6dOnKzw8PEt1JScna+nSpapevXq277YDAAAAKKBef10qWVLau1eaOjVHh2rQQGreXEpMlD74wEn1AdfgUHC3DRLXv39/rV27Vl9//bXGjx+vLl262M3h3qNHD7Vp0ybl8YEDB9S/f3+FhoaqQ4cO2r59e8py5MiRlP3effddzZs3T927d5ePj4/dfhf/m8Lh6NGj6t69u+bNm6cNGzZo6dKleuyxx7Rr1y49++yzOf1+AAAAAChoihWT3njDbA8fbiZ9zwHb1HDvvSclJOToUECWONRUPjg4WLNnz9aoUaPUv39/BQYGqlOnTukGj0tOTlZSUlLK4x07dig6OlrR0dHq2rWr3b7333+/xo0bJ0kpc8F/+OGH+vDDD+32++STT9S0aVMFBgaqSJEimjFjhs6cOSNvb2/VrVtXM2fO1C233OLI2wEAAABQWDz+uPTuu9LWrdIrr0gzZ2b7UA88IA0caGaaW7hQ6tjReWUCGXF4VPmqVatq1qxZV91nzhUTG3bs2FEds3A1X/m6jBQrVkwzZsy45n4AAAAAkMLTU3rnHenmm00n9b59pcaNs3UoX1/pySelsWOl6dMJ7sh9DjWVBwAAAIB8q3lzqVs3yWqVBgww62zq00eyWKSVK03XeSA3EdwBAAAAFB5vvikFBEjr10uff57tw1SuLN19t9l+910n1QZkguAOAAAAoPCoUMH0cZekF1+U/hsEOztsg9TNmiVdupTz0oDMENwBAAAAFC7PPy+FhZnR5caOzfZh2rY1h4mKkubOdWJ9wBUI7gAAAAAKFz8/aeJEsz1hgnTgQLYO4+EhPfWU2Z42LUdd5oGrIrgDAAAAKHw6dJBuv12Kj5cGDcr2YR57zIwyv327tGmT88oD0iK4AwAAACh8LBbpf/8z08R99520fHm2DlOihNSli9kePlxatkzav1+Ki3NeqYDD87gDAAAAQIFQu7b09NMmwD/7rLRjh+Tt7fBh+vWTZs+WfvzRLDZly0qhoemXKlWkSpXMnXogKwjuAAAAAAqv4cOlzz6T9uwx87o984zDh2jSRJo0yczpfuiQdPCgGWX++HGzbNiQ8evKlbMP9NWrS507S4GB2X87KJgI7gAAAAAKr2LFpFGjzChzI0dKPXpIQUEOH2bgQLNIZpC6s2dNiE+7HDyYun3pkhnU/tgxM6W8zd690rhxOXtLKHgI7gAAAAAKtyeflCZPlvbtk8aPl0aPztHhLBbT971ECalx4/Rft1qlM2fsQ/3ataar/apVOTo1CigGpwMAAABQuHl5pd7mfvtt6ejRXD2dxSJdd510/fVSp07S4MGmqb0kbdsmxcbm6umRDxHcAQAAAKBDB6l5c5Oahw/P89OHhkqlS0uJidKWLXl+erg5gjsAAAAAWCymmbwkffSRtHt3np++WTOzndlgdii8CO4AAAAAIEk33SR17CglJ0tDhuT56QnuyAzBHQAAAABsxo6VPD2lRYuk1avz9NRpg7vVmqenhpsjuAMAAACATY0aUu/eZvuFF/I0QV9/vRkn78QJ6ciRPDst8gGCOwAAAACk9frrUmCg9Ntv0pdf5tlp/f2liAizTXN5pEVwBwAAAIC0SpeWXnzRbA8dKsXH59mp6eeOjBDcAQAAAOBKzz9vAnxkpPTee3l2WoI7MkJwBwAAAIArFSkijRhhtkeOlKKi8uS0tuC+bZuZUh6QCO4AAAAAkLEnnpDCw6V//02d4z2XVa4slSkjJSZKW7bkySkLnJ9/lu64Q/rzT1dX4jwEdwAAAADIiJeX9OabZnvSJOno0Vw/pcVCc/mcGjdOWrZMWrPG1ZU4D8EdAAAAADJz771S8+am3frrr+fJKQnu2ZeUlPp9a9TItbU4E8EdAAAAADJjsUhvvWW2P/5Y2rUr10+ZNrjn4TTyBcKuXdKFC2aIgnr1XF2N8xDcAQAAAOBqmjWTHnhASk6WhgzJ9dM1bmxa6Z84IR0+nOunK1DWrTPrZs3M97CgILgDAAAAwLWMGSN5ekqLF5vRz3KRv7/UsKHZprm8Y9auNevmzV1bh7MR3AEAAADgWmrUkPr0MdsvvGDuvuci+rlnj+2O+803u7YOZyO4AwAAAEBWDBtmOk9v3ix9+WWunorg7rgjR8zi6Sk1berqapyL4A4AAAAAWVG6tLnbLkkvvyzFx+faqW680ay3bzcD2uPabHfbIyLM5ysFCcEdAAAAALLq+eelMmWkyEjp3Xdz7TSVK5vTJCaaG/y4toLaTF4iuAMAAABA1hUpIo0YYbZHjpSionLlNBYLzeUdVVAHppMI7gAAAADgmMcfl2rWlM6ckcaPz7XTENyzLipK2rnTbBPcAQAAAKCw8/KSxo0z22+/Lf3zT66cJm1wt1pz5RQFxsaNZqD/KlWkcuVcXY3zEdwBAAAAwFH33ms6U8fFSa+/niunaNzYfEZw8qR06FCunKLAKMj92yWCOwAAAAA4zmKR3nrLbM+aJe3a5fRT+PtLDRuabZrLX11B7t8uEdwBAAAAIHtuvFF64AHTRnvIkFw5Bf3cry0hQdq0yWxzxx0AAAAAYG/MGNOeffFi6aefnH54gvu1bd8uxcRIxYtLtWq5uprcQXAHAAAAgOyqUUPq08dsv/ii00eRswX3HTtMOEV6tmbyN90keRTQhFtA3xYAAAAA5JFhw8z87ps3S1995dRDV6oklS0rJSZKW7Y49dAFRkEfmE4iuAMAAABAzpQqJQ0aZLZfecV0unYSi4Xm8ldjtRb8gekkgjsAAAAA5NygQVLJktKff0offeTUQxPcMxcZaabL8/GRbrjB1dXkHoI7AAAAAORU0aLSq6+a7REjnNohPW1wd3IX+nzPdre9cWPJz8+1teQmgjsAAAAAOEOfPlJoqHT8uPS//zntsI0bS97e5s7yoUNOO2yBUBj6t0sEdwAAAABwDl9fadQos/3mm9LZs045rJ+f1LCh2aa5vD3bHXeCOwAAAAAga7p1k+rXl6KipHHjnHZY+rmnd+aMtGeP2b7pJtfWktsI7gAAAADgLB4e0tixZnvKFOmff5xyWIJ7euvXm3XNmtJ117m2ltxGcAcAAAAAZ2rXTmrRQoqLk4YPd8ohbcF9xw6njnuXrxWGaeBsCO4AAAAA4EwWS2oz+Y8/Tm3PnQMVK0rlykmJidLmzTk+XIFQWAamkwjuAAAAAOB8zZpJHTpIycnSK6/k+HAWC83l04qLk377zWxzxx0AAAAAkD1jxpg+799+K23cmOPDEdxTbdkixcdLpUpJ1aq5uprcR3AHAAAAgNxQu7bUo4fZHjJEslpzdLi0wT2Hh8r30vZvt1hcW0teILgDAAAAQG4ZMcLM7756tbR0aY4O1aiR5O0tnTolHTzopPryqcLUv10iuAMAAABA7qlYUXr6abM9dKjp855Nfn4mvEuFu7l8cjLBHQAAAADgTEOHSkFBZi63efNydKgbbzTrwhzc9+2Tzp6V/P2lhg1dXU3eILgDAAAAQG4qUUJ66SWz/dprZlS1bGKAutT+7U2bmq4DhQHBHQAAAABy27PPSmXKSJGR0vvvZ/swtuC+Y4d06ZKTastnbM3kC8M0cDYEdwAAAADIbYGB0uuvm+1Ro6SLF7N1mIoVpXLlpKQkafNmJ9aXj9juuBeW/u0SwR0AAAAA8sYTT5hJx0+dkt5+O1uHsFgKd3P5EyekAwfsvw+FAcEdAAAAAPKCt7c0erTZfust6fTpbB2mMAd3WzP5evWk4GDX1pKXCO4AAAAAkFc6dzZzul28KL3xRrYOkTa4W61OrC0fKIzN5CWCOwAAAADkHQ8Padw4sz1jhnTokMOHaNTI3Lw/fVo6eNC55W3dKkVHO/eYzlQYB6aTCO4AAAAAkLfatJFatzbTwg0b5vDL/fxMeJec21z+7belxo2lhx923jGd6dIl88GCxB13AAAAAEBus911//RTaedOh1/u7H7ua9ZIL75othculPbvd85xnenXX81o+hUqSJUqubqavOVwcD9w4IAee+wxRUREqHnz5ho/frzi4+Ov+ppTp05p/Pjx6tChgxo2bKgWLVpo0KBBOnr0aLp9T548qWeeeUYNGzZUkyZN9Morr+hiBlMlrFq1Svfee6/q1aunO+64Q19//bWjbwUAAAAAXOP6601/d6tVevllh1/uzOB+/Lj00EMmFHt7m+fefTfnx3W2wtq/XXIwuEdFRalHjx5KSEjQlClT9Nxzz+mLL77QONunRZnYvXu3li9frnbt2mn69OkaMmSI9u/fr86dO+vs2bMp+yUkJOjJJ5/UoUOHNHHiRA0fPlxr167VoEGD7I63efNmPf3004qIiNDMmTPVrl07vfLKK1q6dKkjbwcAAAAAXGf0aMnTU1q0KDWVZpEtuO/YYZqQZ1dCggntJ05IdepIn332//buPSzKOv//+GtA8IACUuRuHkJRUVdM6+uBLLM8opa/TSraTc0sUVFLszLLA2rpklqKZ81DZlkeqksjWlddNQ9sbmnWWimIim2kWUCKgTC/P+4FG0FlEOa+h3k+rouLz9zzmXve0DvwxX34GNtXrJDOny/7fiuCp17fLklVnJm8du1anTt3TvPmzVNgYKAkKT8/X3FxcYqJiVGdOnVKfN3tt9+ujz/+WFWqXHq72267TZ07d9YHH3ygxx9/XJL0ySef6MiRI0pMTFSjRo0kSf7+/ho8eLC+/PJLtWrVSpK0cOFCtWrVSlOmTJEkdejQQSdPntTcuXPVs2dP574DAAAAAGCGpk2lJ56QFi+Wnn/eCO82W6leWr++VLeudOqUtH+/dPfdZSth/Hhp1y6pVi1pwwapSROpUSMpNVV6+22jPCvIz5f27DHGHHG/hp07dyoiIqIotEtSZGSkCgoKtLvwzx8l8Pf3dwjtkvSHP/xBQUFB+vHHHx32HxYWVhTaJaljx44KDAzUjh07JEm5ublKTk4uFtB79eqllJQUpaenO/MlAQAAAIB5Jk6Uqlc3UummTU699HpPl9+4UZo50xivWCGFhRk3vR82zNg2f751lps7dMi4232tWsYa7p7GqeCemprqEKolI5QHBwcrNTXVqTc+duyYfvrpJ4WGhl51/zabTQ0bNiza/4kTJ5SXl1dsXuF+nK0DAAAAAExz883S008b4/HjjUPLpXQ9wf3bb6XHHjPGY8dK/fpdem7QIOPO9QcOSPv2Ob/vilB4nDgiwri6wNM4dap8VlaW/P39i20PCAhQZmZmqfdjt9s1bdo03XTTTerdu7fD/mvVqnXV/Rd+vryOwsfO1FFSXeetdiHHZXJychw+A1ZAX8KK6EtYDT0JK6IvLWLECFVftEi2r7/Wb0uXKn/AgFK9rE0bL0nVtGePXefO5ZT2LHudOyf9+c/VlJ3tpTvvzNeECb85XM9evboUFeWrt96qojlzLurWW69+M/LyVlJf/vOfvpKqqH37XJ0/f9Gl9VQku90uWyn+wzkV3MtLQkKC9u3bp2XLlqlGjRpmlFCivLw8HT582OwySiUtLc3sEoBi6EtYEX0Jq6EnYUX0pfnqDBigenPmyDZxor5t2VIF1atf8zXVqtnk49NaZ8546R//SFG9etcO2Ha7NGFCiA4frqEbbsjTSy/9R0eOFA/C3bvX0FtvNdfGjV4aPPiIgoJcH5Z/35e7dhnnx998c5oOH852eS0VydfX95pznAru/v7+ys4u/k3KzMxUQEBAqfbx3nvvaf78+Xr55ZcVUXhux+/2X9LSb5mZmfrjH/8oSUXvc3kdWVlZDs+XhY+Pjxo3blzm17tCTk6O0tLSFBISouql+J8ZcAX6ElZEX8Jq6ElYEX1pIRMnquDDD+WblqaWH3+svBdfLNXL2rSx61//ks6caapu3a59mv2SJVWUlOQrb2+73n47X3fe2aTEec2bS3Pn5mv/fm/t2dNczz7ruuB+eV+ePGlTRoZRc79+9eTn57JSKtzRo0dLNc+p4N6oUaNi15BnZ2fr9OnTxa45L8mWLVs0efJkjRo1SlFRUSXu/7vvvnPYZrfbdezYMXX83z3/GzRoIB8fH6Wmpuquu+4qmldYV2nquBKbzWapMwCupnr16m5TKzwHfQkroi9hNfQkrIi+tIAaNaT4eOmhh+Tz2mvyGT7cuG38NXTsKP3rX9Lnn1fV4MFXn5ucLD33nDH+299s6t692lXnjxhhXAf/xhu+euklX5dfW17Yl59/bjxu08am4ODK1aelOU1ecvLmdJ06ddKePXuKjm5LUlJSkry8vIqC9ZUkJydrzJgxevDBBxUbG3vF/X/zzTcOp0Ts3btXv/zyi+7+3/oGvr6+at++vT755BOH1yYmJio0NFT16tVz5ksCAAAAAGuIijKSeE6OcaO6UijtDepOnzZ2n5cnPfCANGbMtff98MPSDTdIJ08aS82bpXCJe09cBq6QU8E9Ojpafn5+io2N1aeffqoNGzYoPj5e0dHRDmu4Dxw4UN26dSt6nJKSotjYWIWEhKhv3746cOBA0ceJEyeK5vXo0UNNmjTRyJEjtX37diUmJmr8+PHq3Llz0RrukjRs2DAdOHBAkydPVnJysubOnavNmzdr5MiR1/O9AAAAAADz2GzSa68Z4zffNBZov4bC4P7ll8ZN50qSny/99a9SerqxTvuKFaVbLr5aNRUdxZ8/vxT1V5DCO8pf41hxpeZUcA8ICNCqVavk7e2t2NhYzZo1S1FRURo3bpzDvIKCAuX/bhmDgwcPKjs7W999950eeeQRPfzww0UfCxYsKJrn4+OjZcuWKSQkRGPGjNGkSZN0xx13aNasWQ77/7//+z8lJCTo3//+twYPHqzNmzdr2rRpioyMLMv3AAAAAACsoW1b6dFHjfGYMddcSL1ePeMjP1/67LOS58TFSVu2GGfjb9wolbBQ2BUNHWqE/C1bpMuuanaJzEzjjxKSZwd3p+8qHxoaqpUrV151zurVqx0eP/DAA3rggQdKtf86deooISHhmvO6dOmiLl26lGqfAAAAAOA2XnlF2rBB2rVLev9949z2q4iIkNatM06X79zZ8bmPPpKmTjXGS5ZILVs6V0rDhlKvXsZ+Fi68dEKAq+zda/ztIjRU+t/9yj2SU0fcAQAAAAAVrH59aexYY/zss9Jvv111+pWucz92TOrf3xgPH26cLl8WhbcoW7HiyqfjVxROkzcQ3AEAAADAap57zjjEnJoqzZt31akdOhifC49OS9KFC8bN6H7+WWrXTpo9u+yl9OhhHPHOzJTefrvs+ykLbkxnILgDAAAAgNXUrCm9/LIxnjrVuC38Fdx2m+TrK505I6WkGNtGjZI+/9y4K/y6dVLVqmUvxctLGjbMGM+ff83L7stNXp6xhJ3EEXeCOwAAAABY0YABUuvWxqHuuLgrTqta1QjvknHUfcUKaelS46Zy77wjNWhw/aUMGmTcZf7gwWsvPVdeDh70Uk6OFBQkNWvmmve0KoI7AAAAAFiRt/elc9wXLZL+858rTi28zn35cuN6dkmaMkX63Srd1yUoSHrkEWPsqqXh9u414uoddxhH/T2Zh3/5AAAAAGBh99wj9e1rrPf27LNXnFYY3P/5T+P69l69pPHjy7eUwpvUrVsnZWSU775LUhjcPf36dongDgAAAADW9uqrUpUqUmKi9Pe/lzilMLhLUkiItHp1+R+lvv12qX1749rzZcvKd9+Xs9ulvXu9JRHcJYI7AAAAAFhbkybSiBHGeMwY6eLFYlPq1TOuc/fzk9avN05trwiFp+EvXlxiGeUmPb2qfvzRJl9f4w8Gno7gDgAAAABWN3Gikca//lp6440Sp+zaJaWlVWzQfegh6cYbpZMnpc2bK+59DhyoKUlq29a4KZ6nI7gDAAAAgNXVri1NmmSMJ0yQsrKKTalRwwjVFalaNWnwYGNckTepO3jQTxLLwBUiuAMAAACAOxg2TGra1FjT/ZVXTCtj6FBjqbl//EP69tuKeY/CI+5c324guAMAAACAO/DxkWbONMavvSYdO2ZKGSEhUu/exnjhwvLf/5kzUlpadUnGUnAguAMAAACA++jTR+rSRcrNlcaNM62MwqXhVq6Uzp0r330nJxt3k2/WrEA33FC++3ZXBHcAAAAAcBc2mzRrlvH5vfekPXtMKaN7d6lxYykzU1qzpnz3Xbh+e4cOBeW7YzdGcAcAAAAAd3LrrZfuEDd6tFTg+oDr5WVcci8ZN6mz28tv34XBPSIiv/x26uYI7gAAAADgbqZOlWrWlP71L2ntWlNKeOwx4y7zX35Zfgf+z56VPv/ciKl33MER90IEdwAAAABwN3/4g/TCC8Z43Djp/HmXlxAUJP3lL8b4epeGu3DBuAKgcWMpN9emOnVy1bBhOR7Gd3MEdwAAAABwR6NHSw0aSCdPGneZN0HhTerWr5cyMpx/fUGB9NZbUrNm0tix0s8/S82bF2jGjFTZbOVbqzsjuAMAAACAO6peXZoxwxhPny79978uL+G226QOHaS8PGnpUudeu2WLdPvtUv/+0vHjUt260htvSMnJFxQeXs63qndzBHcAAAAAcFfR0VL79saabBMmmFLC8OHG58WLpYsXrz3/iy+Mu9J37y4dOCD5+0uvvCJ99530+OOSt3eFluuWCO4AAAAA4K5stkunyS9fbiRhF3vwQenGG6X0dGnTpivPS0uTHn3UOEq/ZYvk4yM9/bSUkmJcrl+jhqsqdj8EdwAAAABwZxER0sMPG2uyjRlTvmuzlUK1atITTxjjkm5S99NP0jPPSGFhl9Z8f+QR6ZtvjL853Hij62p1VwR3AAAAAHB3M2ZIVatK27df/bB3BRk61Dj4v3WrEcglKSdHio+XQkOl2bOl3FypSxdp/37p7belRo1cXqbbIrgDAAAAgLsLCTGOtkvG4e3cXJe+/S23SH36GON586SVK6WmTaXnn5cyM6VWraSkpEs3pINzCO4AAAAAUBm88IJUp4509Oj1L6xeBoVLw82fLw0aZFzzXr++tGqV9PnnUo8eYom3MiK4AwAAAEBlUKuW9PLLxjguTjpzxqVv362bcZRdkgIDpVdfNe4UP2AAd4q/XgR3AAAAAKgsHntMat3aOD990iSXvrWXl/Thh9KCBcad4seONW5ch+tHcAcAAACAysLb+9LycIsXS19/7dK3b9ZMGjZMCgpy6dtWegR3AAAAAKhMOneW/vxnKT/flOXhUP4I7gAAAABQ2bz6quTjI/3979LHH5tdDa4TwR0AAAAAKpvQUOmpp4zxM89IeXnm1oPrQnAHAAAAgMropZek4GDpm2+kRYvMrgbXgeAOAAAAAJVRQIA0daoxnjRJOnvW3HpQZgR3AAAAAKisBg+WWraUfv5ZmjLF7GpQRgR3AAAAAKisqlSRZs82xvPnG6fNw+0Q3AEAAACgMuvWTbrvPuniRWnsWLOrQRkQ3AEAAACgsps50zj6/tFHxhJxcCsEdwAAAACo7Jo2lUaMMMZjxhhH3+E2CO4AAAAA4AkmTpSCgqSvv5aWLjW7GjiB4A4AAAAAnqB2bSkuzhhPnCj98oup5aD0CO4AAAAA4CliYqTmzaUzZ6Rp08yuBqVEcAcAAAAAT+HjI82aZYznzpWOHjW3HpQKwR0AAAAAPElkpNSzp5SXJz37rNnVoBQI7gAAAADgaWbNkry9pQ8+kLZvN7saXAPBHQAAAAA8TYsW0tChxnj0aCk/39x6cFUEdwAAAADwRJMnS4GB0sGD0ooVZleDqyC4AwAAAIAnuvFGadIkY/zii1JWlrn14IoI7gAAAADgqYYPl5o0kX78UZo+3exqcAUEdwAAAADwVL6+l5aHmz1bOnbM3HpQIoI7AAAAAHiyPn2krl2l3FzpuefMrgYlILgDAAAAgCez2Yyj7V5e0vr10q5dZleEyxDcAQAAAMDThYdLTz5pjEeOlC5eNLceOCC4AwAAAACkqVOl2rWN5eESEsyuBr9DcAcAAAAASMHBUny8MZ4wQTp50tx6UITgDgAAAAAwPP64dMcd0rlz0tNPm10N/ofgDgAAAAAweHlJixZJ3t7Sxo3S5s1mVwQR3AEAAAAAvxceLo0ZY4xHjDCOvsNUBHcAAAAAgKNJk6QGDaTjx42b1sFUBHcAAAAAgCM/P2nePGM8a5b01Vfm1uPhCO4AAAAAgOLuu0/6f//PWNN92DCpoMDsijwWwR0AAAAAULI5c4yj759+Kq1caXY1HovgDgAAAAAoWYMGUlycMX72Wen0aXPr8VAEdwAAAADAlY0aJbVqJZ09Kz33nNnVeCSCOwAAAADgynx8pMWLJZvNOF1+xw6zK/I4BHcAAAAAwNV16CANGWKMhw2TcnPNrcfDOB3cU1JSNGjQILVu3VodO3ZUfHy8ckvxH23NmjWKiYlRhw4dFBYWpqSkpGJzxo0bp7CwsBI/lixZcs15O3fudPbLAQAAAACUxvTpUnCwdPiwsUQcXKaKM5MzMzM1cOBAhYSEKCEhQRkZGZoxY4YuXLigiRMnXvW1H374oSTp7rvv1gcffFDinOHDhys6OtphW2JiolatWqVOnTo5bK9fv75mzpzpsC00NNSZLwcAAAAAUFq1a0uzZ0v9+0tTpkgPPyw1amR2VR7BqeC+du1anTt3TvPmzVNgYKAkKT8/X3FxcYqJiVGdOnWu+lovLy+lp6dfMbg3aNBADRo0cNg2a9YsNW7cWM2aNXPYXq1aNbVu3dqZ8gEAAAAA1+Ovf5WWL5e2b5diY6XEROPad1Qop06V37lzpyIiIopCuyRFRkaqoKBAu3fvvvobeTl/OX1GRob279+v++67z+nXAgAAAADKmc0mLVwo+fpKSUnShg1mV+QRnDrinpqaqn79+jls8/f3V3BwsFJTU8u1MEnavHmzCgoK1Lt372LPHT9+XLfffrt+++03NW3aVMOHD1fXrl2v6/3sdrvOnz9/XfuoaDk5OQ6fASugL2FF9CWshp6EFdGXKJP69eXzzDPymT5dBaNG6cKdd0r+/uW2e0/qS7vdLlspzlhwKrhnZWXJv4T/IAEBAcrMzHRmV6WyefNmtWnTRvXr13fY3rx5c4WHh6tx48bKzs7WO++8o9jYWM2ZM0c9e/Ys8/vl5eXp8OHD11u2S6SlpZldAlAMfQkroi9hNfQkrIi+hLNsffqoxerVqpaeruwxY5T+zDPl/h6e0pe+vr7XnONUcHellJQU/ec//9GECROKPTdw4ECHx/fee6+io6M1d+7c6wruPj4+aty4cZlf7wo5OTlKS0tTSEiIqlevbnY5gCT6EtZEX8Jq6ElYEX2J6zJ/vtS3r2569135x8bK3qZNuezWk/ry6NGjpZrnVHD39/dXdnZ2se2ZmZkKCAhwZlfXtGnTJlWpUkW9evW65lwvLy91795dr776qi5cuKBq1aqV6T1tNptq1KhRpte6WvXq1d2mVngO+hJWRF/CauhJWBF9iTK5/34pOlq2tWtV/emnpX37JG/vctu9J/RlaU6Tl5y8OV2jRo2KXcuenZ2t06dPq1E5LwPw0UcfKSIiQkFBQeW6XwAAAABAOZk927i+ff9+adEis6uptJwK7p06ddKePXuUlZVVtC0pKUleXl7q2LFjuRV18OBBnThxQn369CnV/IKCAiUlJalJkyZlPtoOAAAAAHDSH/8ovfKKMR4/Xvrvf82tp5Jy6lT56OhorV69WrGxsYqJiVFGRobi4+MVHR3tsIb7wIED9f3332vLli1F2w4dOqRTp07p7NmzkoxwLklBQUFq166dw/ts2rRJ1apVU7du3YrVcOrUKY0bN069e/fWLbfcoszMTL3zzjv66quvlJCQ4MyXAwAAAAC4XkOHSqtWSZ99Jo0ZI73zjtkVVTpOBfeAgACtWrVKU6dOVWxsrPz8/BQVFaXRo0c7zCsoKFB+fr7DtjVr1uj9998verx8+XJJUrt27bR69eqi7fn5+UpKStI999wjPz+/YjX4+fmpZs2aWrhwoX766Sf5+PioZcuWWrp0qe666y5nvhwAAAAAwPXy9jZOk2/bVlq7Vho0SOre3eyqKhWn7yofGhqqlStXXnXO74N4oRkzZmjGjBnX3L+3t7c+/fTTKz4fGBiohQsXXnM/AAAAAAAXue02aeRIac4cafhw6dAhqZLfEd6VnLrGHQAAAACAEk2ZIt18s5SSIk2aZHY1lQrBHQAAAABw/fz9pcKzo2fNkvbuNbeeSoTgDgAAAAAoH/ffL/XvLxUUSI89JuXkmF1RpUBwBwAAAACUnzlzjGXivvtOmjDB7GoqBYI7AAAAAKD81K4tLVlijGfPlnbvNreeSoDgDgAAAAAoX336SAMHSna7sTzc+fNmV+TWCO4AAAAAgPL3+uvGXeaPHJFeesnsatwawR0AAAAAUP4CA6WlS43x669Lu3aZWY1bI7gDAAAAACpGr17GqfJ2u/T449K5c2ZX5JYI7gAAAACAijN7tlSvnnT0qDR+vNnVuCWCOwAAAACg4gQGSsuWGeO5c6UdO0wtxx0R3AEAAAAAFatHD+mJJ4wxp8w7jeAOAAAAAKh4s2ZJ9etLqanSuHFmV+NWCO4AAAAAgIrn73/plPl586R//tPUctwJwR0AAAAA4Brdu0tDhhjjQYOkX381tx43QXAHAAAAALjOq69KDRpIaWnS88+bXY1bILgDAAAAAFzH31964w1jvGCBtG2bufW4AYI7AAAAAMC1unaVhg41xo8/LmVnm1uPxRHcAQAAAACuFx8vhYRIx49Lzz1ndjWWRnAHAAAAALherVrS8uXGeNEi6R//MLceCyO4AwAAAADMcc890vDhxnjwYCkry9x6LIrgDgAAAAAwz9/+JjVsKJ04IY0da3Y1lkRwBwAAAACYp2bNS6fML10qL06ZL4bgDgAAAAAwV+fO0siRkiTf4cPl9euv5tZjMQR3AAAAAID5pk+XQkPldeqU6s+aZXY1lkJwBwAAAACYz89PWr5cdptNN27aJO81a8yuyDII7gAAAAAAa+jUSXnjx0uSfJ96Sjp0yOSCrIHgDgAAAACwjIvPP6/MDh1ky8mR+vVjiTgR3AEAAAAAVuLtrWPTpqmgXj3pyBHp8cclu93sqkxFcAcAAAAAWEp+YKBy33pL8vGRNmyQ5swxuyRTEdwBAAAAAJZT0LatNHu28eDZZ6Xdu80tyEQEdwAAAACANcXGStHR0sWL0kMPST/+aHZFpiC4AwAAAACsyWaTli6VmjWTvv9e+stfpPx8s6tyOYI7AAAAAMC6atY0rnOvUUPaulWaPNnsilyO4A4AAAAAsLYWLYwj75I0bZqUmGhuPS5GcAcAAAAAWN9f/iINH26MH31UOn7c3HpciOAOAAAAAHAPs2dL7dpJP/8sRUVJv/1mdkUuQXAHAAAAALiHqlWl996TgoKk/fulMWPMrsglCO4AAAAAAPdxyy3SW28Zd5xfsEB6+22zK6pwBHcAAAAAgHuJjJReeskYP/mk9PXX5tZTwQjuAAAAAAD3M2mS1LWrdP681K+flJ1tdkUVhuAOAAAAAHA/3t7GafJ160rffmscebfbza6qQhDcAQAAAADuKThYWrdOqlJFevddad48syuqEAR3AAAAAID7ioiQZs40xs88I+3bZ249FYDgDgAAAABwb6NGSQ8+KOXlSQ89JJ05Y3ZF5YrgDgAAAABwbzabtGyZ1LSpdPKk9Ne/Svn5ZldVbgjuAAAAAAD35+8vbdgg1agh/f3v0vvvm11RuSG4AwAAAAAqh5YtpbVrpc6dpfBws6spN1XMLgAAAAAAgHJz333GRyXCEXcAAAAAACyM4A4AAAAAgIUR3AEAAAAAsDCCOwAAAAAAFkZwBwAAAADAwgjuAAAAAABYGMEdAAAAAAALI7gDAAAAAGBhBHcAAAAAACyM4A4AAAAAgIUR3AEAAAAAsDCCOwAAAAAAFkZwBwAAAADAwgjuAAAAAABYGMEdAAAAAAALczq4p6SkaNCgQWrdurU6duyo+Ph45ebmXvN1a9asUUxMjDp06KCwsDAlJSUVm5OcnKywsLBiH6NHjy42d9u2bbr//vsVHh6uHj16aMOGDc5+KQAAAAAAWF4VZyZnZmZq4MCBCgkJUUJCgjIyMjRjxgxduHBBEydOvOprP/zwQ0nS3XffrQ8++OCqc6dPn65GjRoVPa5du7bD8/v379eIESMUFRWl8ePHa9++fXrxxRfl5+ennj17OvMlAQAAAABgaU4F97Vr1+rcuXOaN2+eAgMDJUn5+fmKi4tTTEyM6tSpc9XXenl5KT09/ZrBvUmTJgoPD7/i8wsXLlSrVq00ZcoUSVKHDh108uRJzZ07l+AOAAAAAKhUnDpVfufOnYqIiCgK7ZIUGRmpgoIC7d69++pv5FU+l9Pn5uYqOTm5WEDv1auXUlJSlJ6eXi7vAwAAAACAFTh1xD01NVX9+vVz2Obv76/g4GClpqaWW1FDhgzRL7/8ouDgYPXu3VtPPfWUqlWrJkk6ceKE8vLyHE6ll6TQ0NCiGuvVq1em97Xb7Tp//vz1FV/BcnJyHD4DVkBfworoS1gNPQkroi9hRZ7Ul3a7XTab7ZrznAruWVlZ8vf3L7Y9ICBAmZmZzuyqRLVq1dITTzyhtm3bqmrVqtq3b5+WL1+u1NRULV68WJKK3ufyOgofX08deXl5Onz4cJlf70ppaWlmlwAUQ1/CiuhLWA09CSuiL2FFntKXvr6+15zjVHCvaC1atFCLFi2KHkdEROimm27SlClT9OWXX6pVq1YV+v4+Pj5q3Lhxhb7H9crJyVFaWppCQkJUvXp1s8sBJNGXsCb6ElZDT8KK6EtYkSf15dGjR0s1z6ng7u/vr+zs7GLbMzMzFRAQ4MyuSi0yMlJTpkzRV199pVatWhW9z+V1ZGVlSdJ11WGz2VSjRo2yF+tC1atXd5ta4TnoS1gRfQmroSdhRfQlrMgT+rI0p8lLTt6crlGjRsWuZc/Oztbp06eLXXNeURo0aCAfH59idRQ+dlUdAAAAAAC4glPBvVOnTtqzZ0/R0W1JSkpKkpeXlzp27FjuxUnSRx99JElFy8P5+vqqffv2+uSTTxzmJSYmKjQ0tMw3pgMAAAAAwIqcOlU+Ojpaq1evVmxsrGJiYpSRkaH4+HhFR0c7rOE+cOBAff/999qyZUvRtkOHDunUqVM6e/asJOngwYOSpKCgILVr106SNHbsWN1yyy1q0aJF0c3pVq5cqa5duzqs6z5s2DANGDBAkydPVmRkpJKTk7V582a99tprZf5G5OXlyW6369ChQ2XehyvY7XZJxrUQpT2tAqho9CWsiL6E1dCTsCL6ElbkSX2Zm5tbqq/RZi/8rpRSSkqKpk6dqi+++EJ+fn7q27evRo8e7XAnvP79++vUqVPatm1b0bZx48bp/fffL7a/du3aafXq1ZKkxYsXa9OmTTp16pTy8vJUt25d3XfffRoyZEixO+1t3bpVr7/+uo4dO6abb75ZQ4YMUVRUlDNfioMvvvhCdrtdPj4+Zd4HAAAAAACllZeXJ5vNpjZt2lx1ntPBHQAAAAAAuI5T17gDAAAAAADXIrgDAAAAAGBhBHcAAAAAACyM4A4AAAAAgIUR3AEAAAAAsDCCOwAAAAAAFkZwBwAAAADAwgjuAAAAAABYGMEdAAAAAAALI7gDAAAAAGBhBHcAAAAAACyM4A4AAAAAgIUR3N1ESkqKBg0apNatW6tjx46Kj49Xbm6u2WXBgxw/flwTJ05U37591aJFC/Xp06fEeevWrVOPHj0UHh6u+++/X9u3b3dxpfAUH3/8sYYNG6ZOnTqpdevW6tu3r9avXy+73e4wj56EK+3YsUOPPvqoOnTooJYtW6pLly6aPn26srOzHeZt27ZN999/v8LDw9WjRw9t2LDBpIrhac6dO6dOnTopLCxMhw4dcniOn5dwlY0bNyosLKzYx8yZMx3m0ZOXVDG7AFxbZmamBg4cqJCQECUkJCgjI0MzZszQhQsXNHHiRLPLg4c4cuSIduzYoVtvvVUFBQXFwpEkffTRR5owYYKGDh2qDh06KDExUSNGjNCaNWvUunVr1xeNSm3lypWqW7euxo0bp9q1a2vPnj2aMGGCfvjhB40YMUISPQnX++WXX9SqVSv1799fgYGBOnLkiBISEnTkyBEtX75ckrR//36NGDFCUVFRGj9+vPbt26cXX3xRfn5+6tmzp8lfASq7BQsWKD8/v9h2fl7CDMuWLVOtWrWKHtepU6doTE86stlL+tc3LGXx4sVatGiRtm/frsDAQEnSu+++q7i4OG3fvt2hwYGKUlBQIC8v4ySdcePG6auvvtLmzZsd5vTo0UMtW7bUrFmzirZFR0erVq1aWrp0qUvrReV39uxZBQUFOWybMGGCEhMT9dlnn8nLy4uehCW89957mjBhgnbu3Kk6depo8ODBOnfunNauXVs055lnntHhw4eVmJhoYqWo7FJSUhQVFaXnn39ekyZN0vr16xUeHi6J3+FwrY0bN+qFF17Q3r17i/0uL0RPOuJUeTewc+dORUREFIV2SYqMjFRBQYF2795tXmHwKIWh/UpOnjyptLQ0RUZGOmzv1auX9u7dy6UdKHcl/aJv3ry5fv31V50/f56ehGUU/v7Oy8tTbm6ukpOTix1Z79Wrl1JSUpSenm5ChfAU06ZNU3R0tBo2bOiwnZ+XsBp6sjiCuxtITU1Vo0aNHLb5+/srODhYqampJlUFOCrsxcv/MRAaGqq8vDydPHnSjLLgYf7973+rTp06qlmzJj0JU+Xn5+u3337T119/rfnz5+vee+9VvXr1dOLECeXl5RX7vR4aGipJ/F5HhUlKStJ3332n2NjYYs/x8xJm6dOnj5o3b64uXbpo8eLFRZdx0JPFcY27G8jKypK/v3+x7QEBAcrMzDShIqC4wl68vFcLH9OrqGj79+9XYmKinn/+eUn0JMx1zz33KCMjQ5J01113FZ3qSV/CDDk5OZoxY4ZGjx6tmjVrFnuevoSrBQcHa+TIkbr11ltls9m0bds2vf7668rIyNDEiRPpyRIQ3AEAbu+HH37Q6NGj1b59ew0YMMDscgAtWbJEOTk5Onr0qBYuXKihQ4dqxYoVZpcFD7Vw4ULdcMMN6tevn9mlAJKMP2jeddddRY/vvPNOVa1aVatWrdLQoUNNrMy6OFXeDfj7+xdbRkYy/tIUEBBgQkVAcYW9eHmvZmVlOTwPlLesrCw9+eSTCgwMVEJCQtH9GOhJmKlZs2Zq06aNHnzwQS1YsEDJycnasmULfQmXO3XqlJYvX65Ro0YpOztbWVlZOn/+vCTp/PnzOnfuHH0JS4iMjFR+fr4OHz5MT5aA4O4GGjVqVOyat+zsbJ0+fbrYNXKAWQp78fJeTU1NlY+Pj+rXr29GWajkLly4oJiYGGVnZxdbUoaehFWEhYXJx8dHJ06cUIMGDeTj41NiX0ri9zrKXXp6uvLy8jRkyBC1bdtWbdu2LTqiOWDAAA0aNIifl7AcerI4grsb6NSpk/bs2VP0FybJuMGIl5eXOnbsaGJlwCX169dXSEiIkpKSHLYnJiYqIiJCvr6+JlWGyurixYt6+umnlZqaqmXLlhVbGpOehFUcPHhQeXl5qlevnnx9fdW+fXt98sknDnMSExMVGhqqevXqmVQlKqvmzZvrzTffdPh44YUXJElxcXGaNGkSPy9hCYmJifL29laLFi3oyRJwjbsbiI6O1urVqxUbG6uYmBhlZGQoPj5e0dHRrOEOl8nJydGOHTskGafd/frrr0U/TNu1a6egoCCNHDlSY8eOVYMGDdS+fXslJibqyy+/1FtvvWVm6aik4uLitH37do0bN06//vqrDhw4UPRcixYt5OvrS0/C5UaMGKGWLVsqLCxM1apV0zfffKM33nhDYWFh6tq1qyRp2LBhGjBggCZPnqzIyEglJydr8+bNeu2110yuHpWRv7+/2rdvX+Jzf/rTn/SnP/1Jkvh5CZcaPHiw2rdvr7CwMEnS1q1b9d5772nAgAEKDg6WRE9ezma32+1mF4FrS0lJ0dSpU/XFF1/Iz89Pffv21ejRoz3yr00wR3p6urp06VLic2+++WbRPwrWrVunpUuX6vvvv1fDhg01ZswY3XPPPa4sFR7i3nvv1alTp0p8buvWrUVHLulJuNKSJUuUmJioEydOyG63q27duurWrZsGDx7scDfvrVu36vXXX9exY8d08803a8iQIYqKijKxcniS5ORkDRgwQOvXr1d4eHjRdn5ewlWmTZumXbt26YcfflBBQYFCQkL04IMPqn///rLZbEXz6MlLCO4AAAAAAFgY17gDAAAAAGBhBHcAAAAAACyM4A4AAAAAgIUR3AEAAAAAsDCCOwAAAAAAFkZwBwAAAADAwgjuAAAAAABYGMEdAAAAAAALI7gDAAAAAGBhBHcAAAAAACyM4A4AAAAAgIX9f9MeEK7fdHMEAAAAAElFTkSuQmCC\n"
},
"metadata": {}
}
],
"source": [
"pred = model.predict(X_test)\n",
"plt.figure(figsize=(12,8))\n",
"plt.plot(y_test, color='blue', label='Real')\n",
"plt.plot(pred, color='red', label='Prediction')\n",
"plt.title('Stellar Price Prediction')\n",
"plt.legend()\n",
"plt.show()"
]
}
],
"metadata": {
"colab": {
"collapsed_sections": [
"W06FRpNCHKCo",
"sQ_p1oakHNPn",
"bGQUmu60NwRD",
"VJIl1DwwN43f"
],
"provenance": []
},
"kernelspec": {
"display_name": "Python 3.10.7 64-bit (microsoft store)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.11"
},
"vscode": {
"interpreter": {
"hash": "94348be3325f1ae160a67cb39ab80a1e458b4a3911d8ece2b1e6db7371f6660e"
}
}
},
"nbformat": 4,
"nbformat_minor": 0
}
Reference in a new issue View git blame Copy permalink