MCM_2022_Preprocess.ipynb

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   "cell_type": "code",
   "execution_count": 1,
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   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "bchain_df = pd.read_csv(\"Data/BCHAIN-MKPRU.csv\")\n",
    "gold_df = pd.read_csv(\"Data/LBMA-GOLD.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all = bchain_df.join(gold_df.set_index(\"Date\"), on=\"Date\")\n",
    "df_all[\"USD (PM)\"] = df_all[\"USD (PM)\"].interpolate(method=\"linear\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all[\"Bitcoin % Change\"] = (\n",
    "    df_all[\"Value\"] - df_all[\"Value\"].shift(1)) / df_all[\"Value\"].shift(1)\n",
    "df_all[\"Gold % Change\"] = (\n",
    "    df_all[\"USD (PM)\"] - df_all[\"USD (PM)\"].shift(1)) / df_all[\"USD (PM)\"].shift(1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all[\"Date\"] = pd.to_datetime(df_all[\"Date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all.to_csv(\"Data/preprocessed_data.csv\", index=False)"
   ]
  }
 ],
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