03b_extract_pricedata_bitstamp.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib.request\n",
    "import os.path\n",
    "if not os.path.isfile('./data/bitstampUSD.csv.gz'):\n",
    "    url = 'http://api.bitcoincharts.com/v1/csv/bitstampUSD.csv.gz '\n",
    "    urllib.request.urlretrieve(url, './data/bitstampUSD.csv.gz')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "So now we have 38980638 datapoints and the first price is from 2011-09-13 13:53:36\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import pandas_datareader.data as web\n",
    "import datetime\n",
    "#pd.set_option('display.width', 200) # Displaying more columns in one row\n",
    "btc = pd.read_csv(\"./data/bitstampUSD.csv.gz\",compression='gzip',header=None)\n",
    "btc.columns = ['unixtimestamp', 'price','unknown']\n",
    "# warum?!\n",
    "btc[\"timestamp\"]= pd.to_datetime(btc.unixtimestamp,unit='s')\n",
    "btc.index = btc[\"timestamp\"]\n",
    "print(\"So now we have {} datapoints and the first price is from {}\".format(btc.shape[0],btc.timestamp[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "So now we have 105 datapoints\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>timestamp</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-09-30</th>\n",
       "      <td>5.385970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-31</th>\n",
       "      <td>4.167400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-11-30</th>\n",
       "      <td>3.052370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>3.620108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-31</th>\n",
       "      <td>6.278849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-31</th>\n",
       "      <td>8426.070281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-29</th>\n",
       "      <td>9660.456231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>6484.914834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-30</th>\n",
       "      <td>7324.546852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-31</th>\n",
       "      <td>9230.797367</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>105 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  price\n",
       "timestamp              \n",
       "2011-09-30     5.385970\n",
       "2011-10-31     4.167400\n",
       "2011-11-30     3.052370\n",
       "2011-12-31     3.620108\n",
       "2012-01-31     6.278849\n",
       "...                 ...\n",
       "2020-01-31  8426.070281\n",
       "2020-02-29  9660.456231\n",
       "2020-03-31  6484.914834\n",
       "2020-04-30  7324.546852\n",
       "2020-05-31  9230.797367\n",
       "\n",
       "[105 rows x 1 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_prices = pd.DataFrame()\n",
    "daily_prices['price'] = btc.price.resample('M').mean()\n",
    "btc = daily_prices\n",
    "# the first year is not very reliable, we'll skip it.\n",
    "#btc = btc[btc.index > '2012-1-1']\n",
    "btc.fillna(method='ffill',inplace=True) # replace Null-values with forwardfill\n",
    "print(\"So now we have {} datapoints\".format(btc.shape[0]))\n",
    "btc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "btc.to_csv ('data/bitstampUSD_monthly.csv', index = True, header=True)"
   ]
  }
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