{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1,000,000\n",
      "1        1,000\n",
      "2            1\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "s_sep = pd.Series(['1,000,000', '1,000', '1'])\n",
    "print(s_sep)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# print(s_sep.astype(int))\n",
    "# ValueError: invalid literal for int() with base 10: '1,000,000'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1000000\n",
      "1       1000\n",
      "2          1\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(s_sep.str.replace(',', '').astype(int))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1000000.0\n",
      "1       1000.0\n",
      "2          1.0\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(s_sep.str.replace(',', '').astype(float))"
   ]
  }
 ],
 "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}