Up-sampling to average for several groups must be done separately per group

Pandas_Upsample_All_Together.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Putting it all together\n",
    "Upsample multiple groups with an average"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import io"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>CAT</th>\n",
       "      <th>VALUE</th>\n",
       "      <th>count</th>\n",
       "      <th>daily_average</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1900-01-02</th>\n",
       "      <td>abc</td>\n",
       "      <td>20</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900-01-03</th>\n",
       "      <td>abc</td>\n",
       "      <td>20</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900-01-04</th>\n",
       "      <td>abc</td>\n",
       "      <td>15</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900-01-05</th>\n",
       "      <td>abc</td>\n",
       "      <td>15</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900-01-06</th>\n",
       "      <td>abc</td>\n",
       "      <td>15</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900-01-02</th>\n",
       "      <td>efg</td>\n",
       "      <td>40</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900-01-03</th>\n",
       "      <td>efg</td>\n",
       "      <td>40</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900-01-04</th>\n",
       "      <td>efg</td>\n",
       "      <td>40</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900-01-05</th>\n",
       "      <td>efg</td>\n",
       "      <td>40</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900-01-06</th>\n",
       "      <td>efg</td>\n",
       "      <td>12</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            CAT  VALUE  count  daily_average\n",
       "DATE                                        \n",
       "1900-01-02  abc     20    2.0           10.0\n",
       "1900-01-03  abc     20    2.0           10.0\n",
       "1900-01-04  abc     15    3.0            5.0\n",
       "1900-01-05  abc     15    3.0            5.0\n",
       "1900-01-06  abc     15    3.0            5.0\n",
       "1900-01-02  efg     40    4.0           10.0\n",
       "1900-01-03  efg     40    4.0           10.0\n",
       "1900-01-04  efg     40    4.0           10.0\n",
       "1900-01-05  efg     40    4.0           10.0\n",
       "1900-01-06  efg     12    1.0           12.0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=\"\"\"\n",
    "CAT|DATE|VALUE\n",
    "abc|0101|10\n",
    "abc|0103|20\n",
    "abc|0106|15\n",
    "efg|0101|10\n",
    "efg|0105|40\n",
    "efg|0106|12\"\"\"\n",
    "df = pd.read_csv(io.StringIO(data), skiprows=1, sep=\"|\", dtype={\"DATE\":\"str\"})\n",
    "df[\"DATE\"] = pd.to_datetime(df[\"DATE\"], format=\"%m%d\")\n",
    "\n",
    "updated_df = []\n",
    "for gr in df[\"CAT\"].unique():\n",
    "    \n",
    "    subdf = df[df[\"CAT\"]==gr].set_index(\"DATE\").resample(\"1D\", label=\"right\")\n",
    "    \n",
    "    # back fill the data\n",
    "    res = subdf.bfill()\n",
    "    \n",
    "    # Calculate the number of hours in each group\n",
    "    resampled_groups = subdf.groups\n",
    "    df_groups = pd.DataFrame(resampled_groups, index=[\"group\"]).T\n",
    "    df_groups\n",
    "    \n",
    "    s = df_groups.groupby(\"group\").size()\n",
    "    s.name = \"count\"\n",
    "    s_counts = df_groups.join(s, on=\"group\")[\"count\"]\n",
    "    \n",
    "    res = res.join(s_counts)\n",
    "    res[\"daily_average\"] = res[\"VALUE\"]/res[\"count\"]\n",
    "    \n",
    "    # add to list\n",
    "    updated_df.append(res)\n",
    "    \n",
    "pd.concat(updated_df).dropna()"
   ]
  }
 ],
 "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}