Untitled1.ipynb

Untitled1.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from pandas.core.groupby import DataFrameGroupBy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def group_counts(grouped):\n",
    "    grouper = grouped.grouper\n",
    "    indices = grouper.indices\n",
    "    \n",
    "    group_keys = grouper._get_group_keys()\n",
    "    counts = [len(indices[k]) for k in group_keys]\n",
    "    return grouped._wrap_applied_output(group_keys, counts)\n",
    "DataFrameGroupBy.group_counts = group_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.util.testing.makeMixedDataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped = df.groupby('B')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "B\n",
       "0    3\n",
       "1    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped.group_counts()"
   ]
  }
 ],
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