03b_extract_pricedata_gold.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Downloading coinmetrics Pricedata\n",
    "This script can't download the pricedata from the coinmetric [website](https://coinmetrics.io/community-network-data/#comm-files) as this is prevented from coinmetric which wants you to do that manually via your browser. So with the above script you can only check whether the file is there and load it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import os\n",
    "if not os.path.isfile('./data/gold_raw.csv'):\n",
    "    url = 'https://datahub.io/core/gold-prices/r/monthly.csv'\n",
    "    r = requests.get(url)\n",
    "    with open('./data/gold_raw.csv', 'wb') as outfile:\n",
    "        outfile.write(r.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Yes, this are in fact monthly prices but we have to tidy it up to get an index which we can use with the other data (mainly flow)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<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>1950-01-01</th>\n",
       "      <td>34.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1950-02-01</th>\n",
       "      <td>34.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1950-03-01</th>\n",
       "      <td>34.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1950-04-01</th>\n",
       "      <td>34.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1950-05-01</th>\n",
       "      <td>34.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-01</th>\n",
       "      <td>1471.921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-01</th>\n",
       "      <td>1480.025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>1560.668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-01</th>\n",
       "      <td>1598.818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-01</th>\n",
       "      <td>1593.764</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>843 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Price\n",
       "Date                \n",
       "1950-01-01    34.730\n",
       "1950-02-01    34.730\n",
       "1950-03-01    34.730\n",
       "1950-04-01    34.730\n",
       "1950-05-01    34.730\n",
       "...              ...\n",
       "2019-11-01  1471.921\n",
       "2019-12-01  1480.025\n",
       "2020-01-01  1560.668\n",
       "2020-02-01  1598.818\n",
       "2020-03-01  1593.764\n",
       "\n",
       "[843 rows x 1 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "monthly_raw = pd.read_csv(\"./data/gold_raw.csv\",\\\n",
    "                  index_col=\"Date\",parse_dates=[\"Date\"])\n",
    "monthly_raw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gold_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>857.726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-02-28</th>\n",
       "      <td>939.763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-03-31</th>\n",
       "      <td>925.989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-30</th>\n",
       "      <td>892.663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-05-31</th>\n",
       "      <td>926.855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-30</th>\n",
       "      <td>1471.921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>1480.025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-31</th>\n",
       "      <td>1560.668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-29</th>\n",
       "      <td>1598.818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>1593.764</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>135 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            gold_price\n",
       "Date                  \n",
       "2009-01-31     857.726\n",
       "2009-02-28     939.763\n",
       "2009-03-31     925.989\n",
       "2009-04-30     892.663\n",
       "2009-05-31     926.855\n",
       "...                ...\n",
       "2019-11-30    1471.921\n",
       "2019-12-31    1480.025\n",
       "2020-01-31    1560.668\n",
       "2020-02-29    1598.818\n",
       "2020-03-31    1593.764\n",
       "\n",
       "[135 rows x 1 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly_prices = pd.DataFrame()\n",
    "monthly_prices['gold_price'] = monthly_raw[monthly_raw.index > \"2008-12\"].Price.resample('M').mean()\n",
    "monthly_prices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "monthly_prices.to_csv ('data/gold_monthly.csv', index = True, header=True)"
   ]
  }
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