diff --git a/3+Crypto_Price_Prediction.ipynb b/3+Crypto_Price_Prediction.ipynb
deleted file mode 100644
index d933a18..0000000
--- a/3+Crypto_Price_Prediction.ipynb
+++ /dev/null
@@ -1,2285 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "id": "PLZl5KnqIGQ8"
- },
- "outputs": [],
- "source": [
- "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",
- "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"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "id": "RN88EZ6yJYDd"
- },
- "outputs": [
- {
- "ename": "ModuleNotFoundError",
- "evalue": "No module named 'tensorflow.python'",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32mc:\\Users\\rathi\\OneDrive\\Documents\\-\\Coding\\PYTHON\\CRYPTO PREDICTION\\3+Crypto_Price_Prediction.ipynb Cell 3\u001b[0m in \u001b[0;36m1\n\u001b[1;32m----> 1\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mkeras\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mmodels\u001b[39;00m \u001b[39mimport\u001b[39;00m Sequential\n\u001b[0;32m 2\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mkeras\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mlayers\u001b[39;00m \u001b[39mimport\u001b[39;00m Dense, LSTM, Dropout, GRU\n\u001b[0;32m 3\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mkeras\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mlayers\u001b[39;00m \u001b[39mimport\u001b[39;00m \u001b[39m*\u001b[39m\n",
- "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\keras\\__init__.py:20\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[39m# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[39m#\u001b[39;00m\n\u001b[0;32m 3\u001b[0m \u001b[39m# Licensed under the Apache License, Version 2.0 (the \"License\");\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 13\u001b[0m \u001b[39m# limitations under the License.\u001b[39;00m\n\u001b[0;32m 14\u001b[0m \u001b[39m# ==============================================================================\u001b[39;00m\n\u001b[0;32m 15\u001b[0m \u001b[39m\"\"\"Implementation of the Keras API, the high-level API of TensorFlow.\u001b[39;00m\n\u001b[0;32m 16\u001b[0m \n\u001b[0;32m 17\u001b[0m \u001b[39mDetailed documentation and user guides are available at\u001b[39;00m\n\u001b[0;32m 18\u001b[0m \u001b[39m[keras.io](https://keras.io).\u001b[39;00m\n\u001b[0;32m 19\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m---> 20\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mkeras\u001b[39;00m \u001b[39mimport\u001b[39;00m distribute\n\u001b[0;32m 21\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mkeras\u001b[39;00m \u001b[39mimport\u001b[39;00m models\n\u001b[0;32m 22\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mkeras\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mengine\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39minput_layer\u001b[39;00m \u001b[39mimport\u001b[39;00m Input\n",
- "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\keras\\distribute\\__init__.py:18\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[39m# Copyright 2019 The TensorFlow Authors. All Rights Reserved.\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[39m#\u001b[39;00m\n\u001b[0;32m 3\u001b[0m \u001b[39m# Licensed under the Apache License, Version 2.0 (the \"License\");\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 13\u001b[0m \u001b[39m# limitations under the License.\u001b[39;00m\n\u001b[0;32m 14\u001b[0m \u001b[39m# ==============================================================================\u001b[39;00m\n\u001b[0;32m 15\u001b[0m \u001b[39m\"\"\"Keras' Distribution Strategy library.\"\"\"\u001b[39;00m\n\u001b[1;32m---> 18\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mkeras\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mdistribute\u001b[39;00m \u001b[39mimport\u001b[39;00m sidecar_evaluator\n",
- "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\keras\\distribute\\sidecar_evaluator.py:17\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[39m# Copyright 2020 The TensorFlow Authors. All Rights Reserved.\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[39m#\u001b[39;00m\n\u001b[0;32m 3\u001b[0m \u001b[39m# Licensed under the Apache License, Version 2.0 (the \"License\");\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 13\u001b[0m \u001b[39m# limitations under the License.\u001b[39;00m\n\u001b[0;32m 14\u001b[0m \u001b[39m# ==============================================================================\u001b[39;00m\n\u001b[0;32m 15\u001b[0m \u001b[39m\"\"\"Python module for evaluation loop.\"\"\"\u001b[39;00m\n\u001b[1;32m---> 17\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mtensorflow\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mcompat\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mv2\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mtf\u001b[39;00m\n\u001b[0;32m 19\u001b[0m \u001b[39m# isort: off\u001b[39;00m\n\u001b[0;32m 20\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mtensorflow\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mpython\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mplatform\u001b[39;00m \u001b[39mimport\u001b[39;00m tf_logging \u001b[39mas\u001b[39;00m logging\n",
- "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\tensorflow\\__init__.py:37\u001b[0m\n\u001b[0;32m 34\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39msys\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39m_sys\u001b[39;00m\n\u001b[0;32m 35\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mtyping\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39m_typing\u001b[39;00m\n\u001b[1;32m---> 37\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mtensorflow\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mpython\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mtools\u001b[39;00m \u001b[39mimport\u001b[39;00m module_util \u001b[39mas\u001b[39;00m _module_util\n\u001b[0;32m 38\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mtensorflow\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mpython\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mutil\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mlazy_loader\u001b[39;00m \u001b[39mimport\u001b[39;00m LazyLoader \u001b[39mas\u001b[39;00m _LazyLoader\n\u001b[0;32m 40\u001b[0m \u001b[39m# Make sure code inside the TensorFlow codebase can use tf2.enabled() at import.\u001b[39;00m\n",
- "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'tensorflow.python'"
- ]
- }
- ],
- "source": [
- "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"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "background_save": true,
- "base_uri": "https://localhost:8080/",
- "height": 38,
- "resources": {
- "http://localhost:8080/nbextensions/google.colab/files.js": {
- "data": "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",
- "headers": [
- [
- "content-type",
- "application/javascript"
- ]
- ],
- "ok": true,
- "status": 200,
- "status_text": ""
- }
- }
- },
- "id": "sOGCxI5MIHJ8",
- "outputId": "2a391b7b-7b06-4c09-daaa-dfe79a178c84"
- },
- "outputs": [],
- "source": [
- "# from google.colab import files\n",
- "# uploaded = files.upload()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "PLXtatQdIKkr"
- },
- "outputs": [],
- "source": [
- "# import io\n",
- "# df = pd.read_csv(io.StringIO(uploaded['crypto-markets.csv'].decode('utf-8')))\n",
- "\n",
- "df = pd.read_csv(\"crypto-markets.csv\")\n",
- "\n",
- "data_copy = df"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 206
- },
- "id": "vFFnVybLILE8",
- "outputId": "5bf743d9-a5cb-4184-dd52-0a346bde79f2"
- },
- "outputs": [],
- "source": [
- "df.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "TDuDU-SlIW8s",
- "outputId": "b5dab737-bce6-4822-c2b5-053c6bc68a26"
- },
- "outputs": [],
- "source": [
- "df.shape #total number of rows and columns"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "rSQy0La6Iaez",
- "outputId": "efe86655-27e4-4773-a87a-523435d68318"
- },
- "outputs": [],
- "source": [
- "df.isnull().sum() #total of null values column wise "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 300
- },
- "id": "HzaCeYB_Ia_j",
- "outputId": "90fe7dea-0df1-48e2-eb85-e2417ff927d9"
- },
- "outputs": [],
- "source": [
- "df.describe() #statistical readings of all the columns "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "t2R1q-FAIejT",
- "outputId": "aebb2a25-de90-4d15-cfe2-011325915a20"
- },
- "outputs": [],
- "source": [
- "df.info() #info on all the columns"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 206
- },
- "id": "kEwAdAFzNGfa",
- "outputId": "47586bab-8683-4edf-8f21-475aed383a5a"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 238
- },
- "id": "txJAiKwmNNg7",
- "outputId": "6c2070a1-7b4d-4155-f209-0eda8ff7bc41"
- },
- "outputs": [],
- "source": [
- "data_.set_index('row_id', inplace=True)\n",
- "data_.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "Bynw95JgNUx6",
- "outputId": "5e4c28c2-3a39-4a64-8106-c00c1d643c9b"
- },
- "outputs": [],
- "source": [
- "#counitng unique symbols \n",
- "data[\"name\"].unique() #total number of unique cryptos "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "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": null,
- "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": null,
- "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": null,
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "Zjb4kqCzVXwY",
- "outputId": "66568d7f-6656-4101-913c-11e21f22e7e6"
- },
- "outputs": [],
- "source": [
- "five_crypto.info()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 296
- },
- "id": "TXNuyzFoVevf",
- "outputId": "3c7295fd-0ec6-4a3f-e09b-e81d5cc7adf8"
- },
- "outputs": [],
- "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",
- "sns.countplot(x='symbol',hue='Up/Down',data=five_crypto,palette='rainbow')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 454
- },
- "id": "b-KaRiCFVlF3",
- "outputId": "426f31e8-b3b3-44e6-ea05-641d58318b45"
- },
- "outputs": [],
- "source": [
- "#a comparison the the up/down ratio at the end of the day for the six.\n",
- "sns.set(style=\"whitegrid\")\n",
- "\n",
- "g = sns.factorplot(\"symbol\", \"close_ratio\", \"Up/Down\",\n",
- " data=five_crypto, kind=\"bar\",\n",
- " size=6, palette=\"muted\",\n",
- " legend_out=True)\n",
- "g.despine(left=True)\n",
- "g.set_ylabels(\"Ratio Count\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 338
- },
- "id": "s86ZmNTCWvdf",
- "outputId": "e1b87670-2d40-4b8e-d1c9-378782b9f330"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 301
- },
- "id": "fKfl6z3bWxMP",
- "outputId": "010fb6ee-6ac0-4fa5-a6b8-0ff102902d0a"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 301
- },
- "id": "4MJQipOJXAlD",
- "outputId": "0b8c53b6-4253-47e0-8c2f-d9f92a8ac7c1"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 357
- },
- "id": "qfrzkuc2XbeX",
- "outputId": "a182edbc-70a2-4d4d-9f72-3727d9c538fc"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 301
- },
- "id": "X2vurY0xXmff",
- "outputId": "f08949e0-ec1b-4167-8875-99474ff74d57"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 301
- },
- "id": "0XQYcAf8Xy2o",
- "outputId": "5dc80b97-f28a-40b7-f929-13cb06120176"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 506
- },
- "id": "_Ezp2S7NX9sI",
- "outputId": "7da7fcc0-5908-4dd8-f980-bb7f8fce40da"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 357
- },
- "id": "NbAmRhK-CrQV",
- "outputId": "e8338b77-ce5e-47ba-f17c-1b971f2d4b2b"
- },
- "outputs": [],
- "source": [
- "data_top_6_currencies.head(5)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 661
- },
- "id": "yy3-xD2qJ8lI",
- "outputId": "cf7f6044-f55c-4ee1-c38b-47e99bd705bd"
- },
- "outputs": [],
- "source": [
- "data_top_6_currencies.drop(['ranknow'],axis=1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "O1V5XiRaF1DU",
- "outputId": "d551e810-f579-4252-8c89-99a5b97df7ff"
- },
- "outputs": [],
- "source": [
- "data_top_6_currencies.shape"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "TNJ2Lwm3KDAX"
- },
- "source": [
- "#Bitcoin"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "49_WACQuDBll",
- "outputId": "5f524485-7bfd-4400-ac65-08819492e014"
- },
- "outputs": [],
- "source": [
- "#bitcoin\n",
- "df1 = data_top_6_currencies[data_top_6_currencies['name']=='Bitcoin']\n",
- "\n",
- "df1.shape"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "JjcbrGKDQTQC",
- "outputId": "045951bb-0e3a-499b-ed16-8fcba13e5896"
- },
- "outputs": [],
- "source": [
- "print(df1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 357
- },
- "id": "l6R9yP7G_7C9",
- "outputId": "7ec05f9a-69a0-4b30-9b00-8062d5ab045a"
- },
- "outputs": [],
- "source": [
- "df1.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "X4QbNB76AUtO",
- "outputId": "3853da87-8db7-483b-bd83-0d69a36e18bc"
- },
- "outputs": [],
- "source": [
- "d = df1.iloc[:, 5:10]\n",
- "print(d.head())\n",
- "print(d.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 410
- },
- "id": "zDuTpvheHFQ-",
- "outputId": "9c6fdee9-de24-4f66-d1c6-00c12a69dad4"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "35cpNfDfHFUN",
- "outputId": "23b39114-4fc4-42a3-d7a3-aeab60030a3b"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "ybiiTeB7HFad",
- "outputId": "97d5b512-2429-44d3-bc73-5a94b9325916"
- },
- "outputs": [],
- "source": [
- "print(hist[1][89])\n",
- "print(data[90])\n",
- "print(target[0])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "T_-csG_1HTON",
- "outputId": "5fbb5f68-96e1-4f98-fae9-1dbb1fbf7e47"
- },
- "outputs": [],
- "source": [
- "hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
- "print(hist_scaled.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "metadata": {
- "id": "T5o66_7XHTUm"
- },
- "outputs": [],
- "source": [
- "import tensorflow as tf\n",
- "from tensorflow.keras import layers"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "9C8DS-c7Hgp1",
- "outputId": "e29c0ce0-4ca5-495a-eb3d-3a93be61950b"
- },
- "outputs": [],
- "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": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "P91hyF2GHgzR"
- },
- "outputs": [],
- "source": [
- "model.compile(optimizer='adam', loss='mean_squared_error')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "I5uoPY81Hmy4",
- "outputId": "08ad7eed-2807-415b-cca6-b7f1db79ebf9"
- },
- "outputs": [],
- "source": [
- "history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 502
- },
- "id": "_2skqc4uHoo4",
- "outputId": "9334689b-73a1-48c3-9411-c5eff80540f8"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 501
- },
- "id": "XeNxAYOlHg8b",
- "outputId": "474939e5-3aea-401b-b312-ab3c434ca9b5"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "ZK38bhh6JByj",
- "outputId": "022a7b36-5a24-43b5-bfb1-e14b29dc6af1"
- },
- "outputs": [],
- "source": [
- "#bitcoin\n",
- "df2 = data_top_6_currencies[data_top_6_currencies['name']=='XRP']\n",
- "\n",
- "df2.shape"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "jV8de94uJByj",
- "outputId": "16f68219-e348-47fe-ec42-156427813871"
- },
- "outputs": [],
- "source": [
- "print(df2)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 357
- },
- "id": "vT1hHSzbJByk",
- "outputId": "0c15cfeb-ac61-446b-97ae-91a31b813235"
- },
- "outputs": [],
- "source": [
- "df2.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "bOfzu0IhJByk",
- "outputId": "99041c2b-6683-45d9-fee7-3d9e2ba89101"
- },
- "outputs": [],
- "source": [
- "d2 = df2.iloc[:, 5:10]\n",
- "print(d2.head())\n",
- "print(d2.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 410
- },
- "id": "hSNYPEm7JByk",
- "outputId": "b1bb1d23-7a54-4439-d8fa-f204886cab79"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "pcllm_j2JByk",
- "outputId": "effc2f69-4149-4390-be0e-f260f5ae6ec2"
- },
- "outputs": [],
- "source": [
- "data = d2.iloc[:, 0]\n",
- "\n",
- "print(data)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "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": null,
- "metadata": {
- "id": "FpugPkG9NAtl"
- },
- "outputs": [],
- "source": [
- "hist = hist.reshape(-1,1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 381
- },
- "id": "icGR5bLNJByl",
- "outputId": "2e8b762b-8ce2-4d91-bd44-a006a6fe559e"
- },
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "AXyWLswgJByl",
- "outputId": "27002554-6aff-4173-bfcc-dff86d04a1d2"
- },
- "outputs": [],
- "source": [
- "hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
- "print(hist_scaled.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "metadata": {
- "id": "wMmrZ7hFJByl"
- },
- "outputs": [],
- "source": [
- "import tensorflow as tf\n",
- "from tensorflow.keras import layers"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "Tfb5_8l6JByl",
- "outputId": "c59503b3-e2cf-4ccc-ab5a-3d487da4d767"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "id": "XblbdTVWJByl"
- },
- "outputs": [],
- "source": [
- "model.compile(optimizer='adam', loss='mean_squared_error')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "wCu3FeoiJBym",
- "outputId": "9e95db9e-0329-42e8-a740-f56c4c8f1ce1"
- },
- "outputs": [],
- "source": [
- "history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 501
- },
- "id": "jqnFts9HJBym",
- "outputId": "4d9124d3-4f27-4678-d728-7037c6b723fa"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "6Gf_B5zeP-SI",
- "outputId": "f8b449f2-2861-485b-a856-d34e57c17867"
- },
- "outputs": [],
- "source": [
- "#bitcoin\n",
- "df3 = data_top_6_currencies[data_top_6_currencies['slug']=='ethereum']\n",
- "\n",
- "df3.shape"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "wTrWsHkZP-SI",
- "outputId": "5790481a-51d7-4fcf-c069-acb926892bcb"
- },
- "outputs": [],
- "source": [
- "print(df3)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 357
- },
- "id": "zsvIQYO3P-SI",
- "outputId": "57dc9c1a-5cb2-47d2-9a82-b99842248a94"
- },
- "outputs": [],
- "source": [
- "df3.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "TnheAbnAP-SI",
- "outputId": "f3948958-bb36-4936-8eac-86179eaf36f2"
- },
- "outputs": [],
- "source": [
- "d3 = df3.iloc[:, 5:10]\n",
- "print(d3.head())\n",
- "print(d3.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 410
- },
- "id": "T3xP1Eo8P-SJ",
- "outputId": "e6c83d5e-0291-41a2-94c7-91cc5afb6104"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "kbwR0m7RP-SJ",
- "outputId": "4880a7a3-544e-4a9c-c33d-ca7f1e7d0221"
- },
- "outputs": [],
- "source": [
- "data = d3.iloc[:, 0]\n",
- "\n",
- "print(data)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "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": null,
- "metadata": {
- "id": "rhe9sKH3P-SJ"
- },
- "outputs": [],
- "source": [
- "hist = hist.reshape(-1,1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "FNSDMq0mP-SK",
- "outputId": "e90ec60d-7d53-468e-cc15-43f4f25b1dba"
- },
- "outputs": [],
- "source": [
- "hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
- "print(hist_scaled.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "metadata": {
- "id": "zvGPHlb2P-SK"
- },
- "outputs": [],
- "source": [
- "import tensorflow as tf\n",
- "from tensorflow.keras import layers"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "aWFjURq-P-SK",
- "outputId": "f941254d-4964-4573-85c7-1ff0fe062ca8"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "id": "gcUc1ZBHP-SK"
- },
- "outputs": [],
- "source": [
- "model.compile(optimizer='adam', loss='mean_squared_error')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "ZfAB0JWTP-SK",
- "outputId": "45985017-af61-43c6-cc29-d85d10c38a68"
- },
- "outputs": [],
- "source": [
- "history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 504
- },
- "id": "DT2SuvDdP-SK",
- "outputId": "1aa682fa-9709-457f-845d-a6c5b4b8d126"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 501
- },
- "id": "eArbMF4TP-SL",
- "outputId": "306dcd95-93db-47f1-8c32-c97757c9b584"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "O4H46vFAUJWo",
- "outputId": "515cdde8-18ad-4f16-effa-dd66d0ac6380"
- },
- "outputs": [],
- "source": [
- "\n",
- "df4 = data_top_6_currencies[data_top_6_currencies['symbol']=='BCH']\n",
- "\n",
- "df4.shape"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "5-4itcj_UJWo",
- "outputId": "35e6401a-92fb-4f3d-d845-4246d7e5c05f"
- },
- "outputs": [],
- "source": [
- "print(df4)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 357
- },
- "id": "mn_n52xrUJWo",
- "outputId": "b2088956-9bf1-4b69-ade6-ef1049fd8f15"
- },
- "outputs": [],
- "source": [
- "df4.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "lNOi437hUJWp",
- "outputId": "4acc7d16-f0b8-4458-86b6-8b895f60776b"
- },
- "outputs": [],
- "source": [
- "d4 = df4.iloc[:, 5:10]\n",
- "print(d4.head())\n",
- "print(d4.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 410
- },
- "id": "WHrBesaXUJWp",
- "outputId": "5a43e17c-b851-4460-a112-9e7f950c115f"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "YIlXzSaUUJWp",
- "outputId": "e4214da2-9147-4e4f-ddbf-60224a7ab83e"
- },
- "outputs": [],
- "source": [
- "data = d4.iloc[:, 0]\n",
- "\n",
- "print(data)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "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": null,
- "metadata": {
- "id": "jLGddq22UJWp"
- },
- "outputs": [],
- "source": [
- "hist = hist.reshape(1,-1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "hC4XeVpMUJWq",
- "outputId": "d822ff1e-cb56-4e83-cb99-c7792309c96c"
- },
- "outputs": [],
- "source": [
- "hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
- "print(hist_scaled.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "metadata": {
- "id": "kTzfwpunUJWq"
- },
- "outputs": [],
- "source": [
- "import tensorflow as tf\n",
- "from tensorflow.keras import layers"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "RoZrj801UJWq",
- "outputId": "5bcea4f2-4c03-4c59-d37f-1330e4e8795b"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "id": "bb-ArUEIUJWq"
- },
- "outputs": [],
- "source": [
- "model.compile(optimizer='adam', loss='mean_squared_error')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "bQebGMcsUJWq",
- "outputId": "aa752aaa-dbd6-4aac-cae6-42f18e6f7b1d"
- },
- "outputs": [],
- "source": [
- "history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 501
- },
- "id": "UH77ijSZUJWq",
- "outputId": "9009ae84-499d-4c8d-d18e-dc8fc479ecb7"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "id": "zIyf6qzoX2oL"
- },
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "pBEwefqtX3kW"
- },
- "source": [
- "#EOS"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "TjCsw9DNX3kW",
- "outputId": "c44e67f8-b66c-4c41-c898-73f7821629aa"
- },
- "outputs": [],
- "source": [
- "df5 = data_top_6_currencies[data_top_6_currencies['symbol']=='EOS']\n",
- "\n",
- "df5.shape"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "7VzpsN7TX3kW",
- "outputId": "81f3990c-1939-4fe5-818f-8e597166f8f6"
- },
- "outputs": [],
- "source": [
- "print(df5)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 357
- },
- "id": "e-d8UPiHX3kW",
- "outputId": "253e678c-66a2-4f72-d8b9-5422a9fee9e6"
- },
- "outputs": [],
- "source": [
- "df5.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "stGfWD9YX3kX",
- "outputId": "cbaee387-a35d-483d-d0b4-3c4c6d1293e8"
- },
- "outputs": [],
- "source": [
- "d5 = df5.iloc[:, 5:10]\n",
- "print(d5.head())\n",
- "print(d5.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 410
- },
- "id": "Y8SdLCNNX3kX",
- "outputId": "2e8edc3b-5e7a-4684-8318-4e6229b17166"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "wvdmLlFsX3kX",
- "outputId": "6a0d3dad-bb9c-4325-cae5-959f222c9ac3"
- },
- "outputs": [],
- "source": [
- "data = d5.iloc[:, 0]\n",
- "\n",
- "print(data)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "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": null,
- "metadata": {
- "id": "ylr7fwbAX3kX"
- },
- "outputs": [],
- "source": [
- "hist = hist.reshape(1,-1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "ejlHo8paX3kX",
- "outputId": "49925969-2cfb-42de-9d6e-c1e695866eec"
- },
- "outputs": [],
- "source": [
- "hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
- "print(hist_scaled.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "metadata": {
- "id": "2q1aJEr5X3kY"
- },
- "outputs": [],
- "source": [
- "import tensorflow as tf\n",
- "from tensorflow.keras import layers"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "zAml_KZ4X3kY",
- "outputId": "0c411e7b-36d4-4ac5-9f14-b2bdac508d0b"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "id": "blIv5kwJX3kY"
- },
- "outputs": [],
- "source": [
- "model.compile(optimizer='adam', loss='mean_squared_error')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "PYbQNxSRX3kY",
- "outputId": "9a4cbc6e-4075-47e9-820f-083cdc6c59f5"
- },
- "outputs": [],
- "source": [
- "history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 501
- },
- "id": "TT6qgo_iX3kY",
- "outputId": "cb71873e-b886-4e41-9947-f2b3765d2f6e"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "gSZO1_fBa5Oe",
- "outputId": "e7db4e69-1838-409d-e2fe-1c8c92614a2c"
- },
- "outputs": [],
- "source": [
- "df6 = data_top_6_currencies[data_top_6_currencies['name']=='Stellar']\n",
- "\n",
- "df6.shape"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "mejmybDCa5Of",
- "outputId": "573b4195-a4fd-47c3-a924-2579a992512e"
- },
- "outputs": [],
- "source": [
- "print(df6)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 357
- },
- "id": "6jooY2Gza5Of",
- "outputId": "cb00a2dd-c0ba-4ade-9a3f-5f769a78a2bb"
- },
- "outputs": [],
- "source": [
- "df6.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "u4YVMNKha5Of",
- "outputId": "33a752e7-ee5a-4f3b-be07-032b4400973e"
- },
- "outputs": [],
- "source": [
- "d = df6.iloc[:, 5:10]\n",
- "print(d.head())\n",
- "print(d.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 410
- },
- "id": "Pib0FOL3a5Of",
- "outputId": "64bbcef9-615a-45c8-817c-d607016ab130"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "1FPPamzibSiL",
- "outputId": "05da7d73-8e57-4f94-b52d-da5d4cf97102"
- },
- "outputs": [],
- "source": [
- "print(d)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "O5snSz7Aa5Of",
- "outputId": "83f62e46-1b7f-4825-cc84-2128c9d2c5be"
- },
- "outputs": [],
- "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": null,
- "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": null,
- "metadata": {
- "id": "PxEu7xN0a5Og"
- },
- "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": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "JBgXLlZAa5Og",
- "outputId": "371d59f2-bdfe-4e90-b328-3ba17be8f29f"
- },
- "outputs": [],
- "source": [
- "hist_scaled = hist_scaled.reshape((len(hist_scaled), length, 1))\n",
- "print(hist_scaled.shape)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "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": null,
- "metadata": {
- "id": "hKMNQyGna5Og"
- },
- "outputs": [],
- "source": [
- "import tensorflow as tf\n",
- "from tensorflow.keras import layers"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "wIUvXFUCa5Og",
- "outputId": "7a104795-05f8-411f-94f9-314eb6c46b84"
- },
- "outputs": [],
- "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": null,
- "metadata": {
- "id": "2JVd7TxPa5Og"
- },
- "outputs": [],
- "source": [
- "model.compile(optimizer='adam', loss='mean_squared_error')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/"
- },
- "id": "m5lWh3Yba5Oh",
- "outputId": "2846ed4f-6ace-4a2f-b80c-b580aba9a176"
- },
- "outputs": [],
- "source": [
- "history = model.fit(X_train, y_train, epochs=30, batch_size=32)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 501
- },
- "id": "bCmQ1HDRa5Oh",
- "outputId": "ed8ad8b9-4bb2-4563-f756-26dde67ca6eb"
- },
- "outputs": [],
- "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
-}