{
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   "cell_type": "code",
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   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "def get_df():\n",
    "    df = pd.DataFrame({'col': ['00000 UNITED STATES', '01000 ALABAMA', \n",
    "                               '01001 Autauga County, AL', '01003 Baldwin County, AL', \n",
    "                               '01005 Barbour County, AL'],\n",
    "                       'type': ['country', 'state', 'county', 'county', 'county']\n",
    "                      })\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                        col     type\n",
      "0       00000 UNITED STATES  country\n",
      "1             01000 ALABAMA    state\n",
      "2  01001 Autauga County, AL   county\n",
      "3  01003 Baldwin County, AL   county\n",
      "4  01005 Barbour County, AL   county\n",
      "                        col     type      A                   B\n",
      "0       00000 UNITED STATES  country  00000       UNITED STATES\n",
      "1             01000 ALABAMA    state  01000             ALABAMA\n",
      "2  01001 Autauga County, AL   county  01001  Autauga County, AL\n",
      "3  01003 Baldwin County, AL   county  01003  Baldwin County, AL\n",
      "4  01005 Barbour County, AL   county  01005  Barbour County, AL\n"
     ]
    }
   ],
   "source": [
    "df = get_df()\n",
    "print(df)\n",
    "df[['A', 'B']] = df['col'].str.split(n=1, expand=True)\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                        col     type\n",
      "0       00000 UNITED STATES  country\n",
      "1             01000 ALABAMA    state\n",
      "2  01001 Autauga County, AL   county\n",
      "3  01003 Baldwin County, AL   county\n",
      "4  01005 Barbour County, AL   county\n",
      "      type      A                   B\n",
      "0  country  00000       UNITED STATES\n",
      "1    state  01000             ALABAMA\n",
      "2   county  01001  Autauga County, AL\n",
      "3   county  01003  Baldwin County, AL\n",
      "4   county  01005  Barbour County, AL\n"
     ]
    }
   ],
   "source": [
    "# If the original columnis to be removed, there are two approaches\n",
    "\n",
    "# method 1: use pop()\n",
    "df = get_df()\n",
    "print(df)\n",
    "df[['A', 'B']] = df.pop('col').str.split(n=1, expand=True)\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                        col     type\n",
      "0       00000 UNITED STATES  country\n",
      "1             01000 ALABAMA    state\n",
      "2  01001 Autauga County, AL   county\n",
      "3  01003 Baldwin County, AL   county\n",
      "4  01005 Barbour County, AL   county\n",
      "                        col     type      A                   B\n",
      "0       00000 UNITED STATES  country  00000       UNITED STATES\n",
      "1             01000 ALABAMA    state  01000             ALABAMA\n",
      "2  01001 Autauga County, AL   county  01001  Autauga County, AL\n",
      "3  01003 Baldwin County, AL   county  01003  Baldwin County, AL\n",
      "4  01005 Barbour County, AL   county  01005  Barbour County, AL\n"
     ]
    }
   ],
   "source": [
    "# method 2: Include the new columns as such and drop the original next\n",
    "df = get_df()\n",
    "print(df)\n",
    "df[['A', 'B']] = df['col'].str.split(n=1, expand=True)\n",
    "df.drop('col', axis=1)\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See also:\n",
    "* https://stackoverflow.com/questions/14745022/how-to-split-a-column-into-two-columns -> https://stackoverflow.com/a/49955802/6305733"
   ]
  }
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