03_extract_pricedata_coinmetric.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Downloading coinmetrics Pricedata\n",
    "This script can't download the pricedata from the coinmetric website as this is prevented from coinmetric which wants you "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib.request\n",
    "import os.path\n",
    "if not os.path.isfile('./data/coinmetric_btc.csv'):\n",
    "    print(\"./data/coinmetric_btc.csv is not existing!\")\n",
    "    print(\"Download from https://coinmetrics.io/community-network-data/#comm-files (Bitcoin)\")\n",
    "    print(\"rename and place it in the data-folder\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AdrActCnt</th>\n",
       "      <th>BlkCnt</th>\n",
       "      <th>BlkSizeByte</th>\n",
       "      <th>BlkSizeMeanByte</th>\n",
       "      <th>CapMVRVCur</th>\n",
       "      <th>CapMrktCurUSD</th>\n",
       "      <th>CapRealUSD</th>\n",
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       "      <th>FeeMeanNtv</th>\n",
       "      <th>FeeMeanUSD</th>\n",
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       "      <th>TxTfrValMedNtv</th>\n",
       "      <th>TxTfrValMedUSD</th>\n",
       "      <th>TxTfrValNtv</th>\n",
       "      <th>TxTfrValUSD</th>\n",
       "      <th>VtyDayRet180d</th>\n",
       "      <th>VtyDayRet30d</th>\n",
       "      <th>VtyDayRet60d</th>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>2009-01-05</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>2009-01-07</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2020-05-05</th>\n",
       "      <td>970464</td>\n",
       "      <td>158</td>\n",
       "      <td>190305322</td>\n",
       "      <td>1.204464e+06</td>\n",
       "      <td>1.599594</td>\n",
       "      <td>1.650160e+11</td>\n",
       "      <td>1.031612e+11</td>\n",
       "      <td>1.608446e+13</td>\n",
       "      <td>0.000219</td>\n",
       "      <td>1.968212</td>\n",
       "      <td>...</td>\n",
       "      <td>1.852142e+09</td>\n",
       "      <td>0.642400</td>\n",
       "      <td>5772.528246</td>\n",
       "      <td>0.010709</td>\n",
       "      <td>96.232930</td>\n",
       "      <td>512106.435390</td>\n",
       "      <td>4.601727e+09</td>\n",
       "      <td>0.050217</td>\n",
       "      <td>0.035826</td>\n",
       "      <td>0.078059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-06</th>\n",
       "      <td>972369</td>\n",
       "      <td>154</td>\n",
       "      <td>186296384</td>\n",
       "      <td>1.209717e+06</td>\n",
       "      <td>1.645748</td>\n",
       "      <td>1.701928e+11</td>\n",
       "      <td>1.034137e+11</td>\n",
       "      <td>1.610481e+13</td>\n",
       "      <td>0.000205</td>\n",
       "      <td>1.902750</td>\n",
       "      <td>...</td>\n",
       "      <td>2.429543e+09</td>\n",
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       "      <td>0.034085</td>\n",
       "      <td>0.078077</td>\n",
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       "    <tr>\n",
       "      <th>2020-05-07</th>\n",
       "      <td>1020443</td>\n",
       "      <td>147</td>\n",
       "      <td>194007072</td>\n",
       "      <td>1.319776e+06</td>\n",
       "      <td>1.762466</td>\n",
       "      <td>1.835621e+11</td>\n",
       "      <td>1.041507e+11</td>\n",
       "      <td>1.610481e+13</td>\n",
       "      <td>0.000265</td>\n",
       "      <td>2.643640</td>\n",
       "      <td>...</td>\n",
       "      <td>3.741749e+09</td>\n",
       "      <td>1.091965</td>\n",
       "      <td>10912.830187</td>\n",
       "      <td>0.010841</td>\n",
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       "      <td>0.035932</td>\n",
       "      <td>0.077684</td>\n",
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       "    <tr>\n",
       "      <th>2020-05-08</th>\n",
       "      <td>949216</td>\n",
       "      <td>137</td>\n",
       "      <td>174365143</td>\n",
       "      <td>1.272738e+06</td>\n",
       "      <td>1.735049</td>\n",
       "      <td>1.811098e+11</td>\n",
       "      <td>1.043831e+11</td>\n",
       "      <td>1.610481e+13</td>\n",
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       "      <td>3.158286</td>\n",
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       "      <td>3.160808e+09</td>\n",
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       "      <td>8622.557629</td>\n",
       "      <td>0.010344</td>\n",
       "      <td>101.983562</td>\n",
       "      <td>711478.024909</td>\n",
       "      <td>7.014692e+09</td>\n",
       "      <td>0.050436</td>\n",
       "      <td>0.036097</td>\n",
       "      <td>0.077616</td>\n",
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       "    <tr>\n",
       "      <th>2020-05-09</th>\n",
       "      <td>906900</td>\n",
       "      <td>136</td>\n",
       "      <td>175387503</td>\n",
       "      <td>1.289614e+06</td>\n",
       "      <td>1.685279</td>\n",
       "      <td>1.759462e+11</td>\n",
       "      <td>1.044018e+11</td>\n",
       "      <td>1.610481e+13</td>\n",
       "      <td>0.000275</td>\n",
       "      <td>2.631075</td>\n",
       "      <td>...</td>\n",
       "      <td>2.500358e+09</td>\n",
       "      <td>0.858406</td>\n",
       "      <td>8221.244046</td>\n",
       "      <td>0.009786</td>\n",
       "      <td>93.724796</td>\n",
       "      <td>661163.090355</td>\n",
       "      <td>6.332183e+09</td>\n",
       "      <td>0.050405</td>\n",
       "      <td>0.036619</td>\n",
       "      <td>0.077731</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>4145 rows × 40 columns</p>\n",
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      ],
      "text/plain": [
       "            AdrActCnt  BlkCnt  BlkSizeByte  BlkSizeMeanByte  CapMVRVCur  \\\n",
       "date                                                                      \n",
       "2009-01-03          0       0            0              NaN         NaN   \n",
       "2009-01-04          0       0            0              NaN         NaN   \n",
       "2009-01-05          0       0            0              NaN         NaN   \n",
       "2009-01-06          0       0            0              NaN         NaN   \n",
       "2009-01-07          0       0            0              NaN         NaN   \n",
       "...               ...     ...          ...              ...         ...   \n",
       "2020-05-05     970464     158    190305322     1.204464e+06    1.599594   \n",
       "2020-05-06     972369     154    186296384     1.209717e+06    1.645748   \n",
       "2020-05-07    1020443     147    194007072     1.319776e+06    1.762466   \n",
       "2020-05-08     949216     137    174365143     1.272738e+06    1.735049   \n",
       "2020-05-09     906900     136    175387503     1.289614e+06    1.685279   \n",
       "\n",
       "            CapMrktCurUSD    CapRealUSD      DiffMean  FeeMeanNtv  FeeMeanUSD  \\\n",
       "date                                                                            \n",
       "2009-01-03            NaN  0.000000e+00           NaN         NaN         NaN   \n",
       "2009-01-04            NaN  0.000000e+00           NaN         NaN         NaN   \n",
       "2009-01-05            NaN  0.000000e+00           NaN         NaN         NaN   \n",
       "2009-01-06            NaN  0.000000e+00           NaN         NaN         NaN   \n",
       "2009-01-07            NaN  0.000000e+00           NaN         NaN         NaN   \n",
       "...                   ...           ...           ...         ...         ...   \n",
       "2020-05-05   1.650160e+11  1.031612e+11  1.608446e+13    0.000219    1.968212   \n",
       "2020-05-06   1.701928e+11  1.034137e+11  1.610481e+13    0.000205    1.902750   \n",
       "2020-05-07   1.835621e+11  1.041507e+11  1.610481e+13    0.000265    2.643640   \n",
       "2020-05-08   1.811098e+11  1.043831e+11  1.610481e+13    0.000320    3.158286   \n",
       "2020-05-09   1.759462e+11  1.044018e+11  1.610481e+13    0.000275    2.631075   \n",
       "\n",
       "            ...  TxTfrValAdjUSD  TxTfrValMeanNtv  TxTfrValMeanUSD  \\\n",
       "date        ...                                                     \n",
       "2009-01-03  ...             NaN              NaN              NaN   \n",
       "2009-01-04  ...             NaN              NaN              NaN   \n",
       "2009-01-05  ...             NaN              NaN              NaN   \n",
       "2009-01-06  ...             NaN              NaN              NaN   \n",
       "2009-01-07  ...             NaN              NaN              NaN   \n",
       "...         ...             ...              ...              ...   \n",
       "2020-05-05  ...    1.852142e+09         0.642400      5772.528246   \n",
       "2020-05-06  ...    2.429543e+09         0.766611      7104.043524   \n",
       "2020-05-07  ...    3.741749e+09         1.091965     10912.830187   \n",
       "2020-05-08  ...    3.160808e+09         0.874559      8622.557629   \n",
       "2020-05-09  ...    2.500358e+09         0.858406      8221.244046   \n",
       "\n",
       "            TxTfrValMedNtv  TxTfrValMedUSD    TxTfrValNtv   TxTfrValUSD  \\\n",
       "date                                                                      \n",
       "2009-01-03             NaN             NaN       0.000000           NaN   \n",
       "2009-01-04             NaN             NaN       0.000000           NaN   \n",
       "2009-01-05             NaN             NaN       0.000000           NaN   \n",
       "2009-01-06             NaN             NaN       0.000000           NaN   \n",
       "2009-01-07             NaN             NaN       0.000000           NaN   \n",
       "...                    ...             ...            ...           ...   \n",
       "2020-05-05        0.010709       96.232930  512106.435390  4.601727e+09   \n",
       "2020-05-06        0.010707       99.217358  633066.838734  5.866512e+09   \n",
       "2020-05-07        0.010841      108.338081  937529.607782  9.369439e+09   \n",
       "2020-05-08        0.010344      101.983562  711478.024909  7.014692e+09   \n",
       "2020-05-09        0.009786       93.724796  661163.090355  6.332183e+09   \n",
       "\n",
       "            VtyDayRet180d  VtyDayRet30d  VtyDayRet60d  \n",
       "date                                                   \n",
       "2009-01-03            NaN           NaN           NaN  \n",
       "2009-01-04            NaN           NaN           NaN  \n",
       "2009-01-05            NaN           NaN           NaN  \n",
       "2009-01-06            NaN           NaN           NaN  \n",
       "2009-01-07            NaN           NaN           NaN  \n",
       "...                   ...           ...           ...  \n",
       "2020-05-05       0.050217      0.035826      0.078059  \n",
       "2020-05-06       0.050148      0.034085      0.078077  \n",
       "2020-05-07       0.050460      0.035932      0.077684  \n",
       "2020-05-08       0.050436      0.036097      0.077616  \n",
       "2020-05-09       0.050405      0.036619      0.077731  \n",
       "\n",
       "[4145 rows x 40 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "btc = pd.read_csv(\"./data/coinmetric_btc.csv\",\\\n",
    "                  index_col=\"date\",parse_dates=[\"date\"])\n",
    "btc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "So now we have 137 datapoints\n"
     ]
    },
    {
     "data": {
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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>date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2009-01-31</th>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2009-02-28</th>\n",
       "      <td>NaN</td>\n",
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       "      <th>2009-03-31</th>\n",
       "      <td>NaN</td>\n",
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       "      <th>2009-04-30</th>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2009-05-31</th>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2020-01-31</th>\n",
       "      <td>8365.735932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-29</th>\n",
       "      <td>9646.192816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>6885.037265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-30</th>\n",
       "      <td>7224.347704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-31</th>\n",
       "      <td>9254.963920</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>137 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  price\n",
       "date                   \n",
       "2009-01-31          NaN\n",
       "2009-02-28          NaN\n",
       "2009-03-31          NaN\n",
       "2009-04-30          NaN\n",
       "2009-05-31          NaN\n",
       "...                 ...\n",
       "2020-01-31  8365.735932\n",
       "2020-02-29  9646.192816\n",
       "2020-03-31  6885.037265\n",
       "2020-04-30  7224.347704\n",
       "2020-05-31  9254.963920\n",
       "\n",
       "[137 rows x 1 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_prices = pd.DataFrame()\n",
    "daily_prices['price'] = btc.PriceUSD.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",
    "# Do we really need that?!\n",
    "# vielleicht besser btc.notnull()\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": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "btc.to_csv ('data/coinmetric_btc_monthly.csv', index = True, header=True)"
   ]
  }
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