Bitcoin_Dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6046bdf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "45f51a9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('./data/Bitcoin_dataset_updated.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c67608d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>Date</th>\n",
       "      <th>BTC price [USD]</th>\n",
       "      <th>n-transactions</th>\n",
       "      <th>fee [USD]</th>\n",
       "      <th>btc search trends</th>\n",
       "      <th>Gold price[USD]</th>\n",
       "      <th>SP500 close index</th>\n",
       "      <th>Oil WTI price[USD]</th>\n",
       "      <th>M2(Not seasonally adjusted)[1e+09 USD]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1095</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>964.84</td>\n",
       "      <td>180502.0</td>\n",
       "      <td>0.39</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13275.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1096</th>\n",
       "      <td>2017-01-02</td>\n",
       "      <td>997.36</td>\n",
       "      <td>290951.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>1151.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13275.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1097</th>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>1013.42</td>\n",
       "      <td>301664.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>1232.90</td>\n",
       "      <td>2257.83</td>\n",
       "      <td>52.36</td>\n",
       "      <td>13275.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1098</th>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>1037.83</td>\n",
       "      <td>328642.0</td>\n",
       "      <td>0.42</td>\n",
       "      <td>6</td>\n",
       "      <td>1235.30</td>\n",
       "      <td>2270.75</td>\n",
       "      <td>53.26</td>\n",
       "      <td>13275.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1099</th>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>1109.16</td>\n",
       "      <td>288501.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>1250.30</td>\n",
       "      <td>2269.00</td>\n",
       "      <td>53.77</td>\n",
       "      <td>13275.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2305</th>\n",
       "      <td>2020-04-25</td>\n",
       "      <td>7507.08</td>\n",
       "      <td>280805.0</td>\n",
       "      <td>0.75</td>\n",
       "      <td>16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17269.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2306</th>\n",
       "      <td>2020-04-26</td>\n",
       "      <td>7549.52</td>\n",
       "      <td>252833.0</td>\n",
       "      <td>0.62</td>\n",
       "      <td>16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17269.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2307</th>\n",
       "      <td>2020-04-27</td>\n",
       "      <td>7699.27</td>\n",
       "      <td>311217.0</td>\n",
       "      <td>0.69</td>\n",
       "      <td>16</td>\n",
       "      <td>1723.80</td>\n",
       "      <td>2878.48</td>\n",
       "      <td>12.17</td>\n",
       "      <td>17269.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2308</th>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>7790.66</td>\n",
       "      <td>323475.0</td>\n",
       "      <td>0.66</td>\n",
       "      <td>16</td>\n",
       "      <td>1722.20</td>\n",
       "      <td>2863.39</td>\n",
       "      <td>12.40</td>\n",
       "      <td>17269.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2309</th>\n",
       "      <td>2020-04-29</td>\n",
       "      <td>7765.33</td>\n",
       "      <td>331401.0</td>\n",
       "      <td>1.30</td>\n",
       "      <td>16</td>\n",
       "      <td>1713.40</td>\n",
       "      <td>2939.51</td>\n",
       "      <td>15.04</td>\n",
       "      <td>17269.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1215 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date  BTC price [USD]  n-transactions  fee [USD]  \\\n",
       "1095  2017-01-01           964.84        180502.0       0.39   \n",
       "1096  2017-01-02           997.36        290951.0        NaN   \n",
       "1097  2017-01-03          1013.42        301664.0        NaN   \n",
       "1098  2017-01-04          1037.83        328642.0       0.42   \n",
       "1099  2017-01-05          1109.16        288501.0        NaN   \n",
       "...          ...              ...             ...        ...   \n",
       "2305  2020-04-25          7507.08        280805.0       0.75   \n",
       "2306  2020-04-26          7549.52        252833.0       0.62   \n",
       "2307  2020-04-27          7699.27        311217.0       0.69   \n",
       "2308  2020-04-28          7790.66        323475.0       0.66   \n",
       "2309  2020-04-29          7765.33        331401.0       1.30   \n",
       "\n",
       "      btc search trends  Gold price[USD]  SP500 close index  \\\n",
       "1095                  6              NaN                NaN   \n",
       "1096                  6          1151.05                NaN   \n",
       "1097                  6          1232.90            2257.83   \n",
       "1098                  6          1235.30            2270.75   \n",
       "1099                  6          1250.30            2269.00   \n",
       "...                 ...              ...                ...   \n",
       "2305                 16              NaN                NaN   \n",
       "2306                 16              NaN                NaN   \n",
       "2307                 16          1723.80            2878.48   \n",
       "2308                 16          1722.20            2863.39   \n",
       "2309                 16          1713.40            2939.51   \n",
       "\n",
       "      Oil WTI price[USD]  M2(Not seasonally adjusted)[1e+09 USD]  \n",
       "1095                 NaN                                 13275.7  \n",
       "1096                 NaN                                 13275.7  \n",
       "1097               52.36                                 13275.7  \n",
       "1098               53.26                                 13275.7  \n",
       "1099               53.77                                 13275.7  \n",
       "...                  ...                                     ...  \n",
       "2305                 NaN                                 17269.8  \n",
       "2306                 NaN                                 17269.8  \n",
       "2307               12.17                                 17269.8  \n",
       "2308               12.40                                 17269.8  \n",
       "2309               15.04                                 17269.8  \n",
       "\n",
       "[1215 rows x 9 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[1095:, :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "15b6df9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "ls = df.iloc[1095:, [0,1,5]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "71d8a25a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fade49e3280>]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(ls.iloc[:, 0], ls.iloc[:, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "546a96ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fae07da4430>]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df.iloc[1095:,0], df.iloc[1095:,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "8f9ccfcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fae004bf7c0>]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df.iloc[1095:,0], df.iloc[1095:,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "f421d6ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fade3789220>]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df.iloc[1095:,0], df.iloc[1095:,5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d03cc83c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fadfbfd5e80>]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df.iloc[1095:,0], df.iloc[1095:,7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b70c0c4",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}