Pandas/Apply-DataFrame-Output.ipynb

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    "# Daily-Dose-of-Data-Science\n",
    "\n",
    "[Daily Dose of Data Science](https://avichawla.substack.com) is a publication on Substack that brings together intriguing frameworks, libraries, technologies, and tips that make the life cycle of a Data Science project effortless. \n",
    "\n",
    "Author: Avi Chawla\n",
    "\n",
    "[Medium](https://medium.com/@avi_chawla) | [LinkedIn](https://www.linkedin.com/in/avi-chawla/)\n",
    "\n",
    "# A Lesser-Known Feature of Apply Method In Pandas\n",
    "\n",
    "Post Link: [Substack](https://avichawla.substack.com/p/a-lesser-known-feature-of-apply-method)\n",
    "\n",
    "LinkedIn Post: [LinkedIn](https://www.linkedin.com/posts/avi-chawla_python-datascience-pandas-activity-7013454040646709249-svKS?utm_source=share&utm_medium=member_desktop)"
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   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
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       "<div>\n",
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       "   A  B  C\n",
       "0  1  3  2\n",
       "1  4  6  3"
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   "source": [
    "df = pd.DataFrame([[1,3,2], [4,6,3]], columns = list(\"ABC\"))\n",
    "df"
   ]
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   "cell_type": "code",
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   "outputs": [],
   "source": [
    "def my_func(row):\n",
    "    return max(row), min(row)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3966763",
   "metadata": {},
   "source": [
    "## Series of Tuple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "495a30d5",
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     "start_time": "2022-12-27T10:50:37.069322Z"
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    "scrolled": true
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   "outputs": [
    {
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      "text/plain": [
       "0    (3, 1)\n",
       "1    (6, 3)\n",
       "dtype: object"
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   "source": [
    "df.apply(my_func, axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "398a3d33",
   "metadata": {},
   "source": [
    "## Pandas DataFrame"
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
   "id": "9fe696f4",
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       "   0  1\n",
       "0  3  1\n",
       "1  6  3"
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   "source": [
    "df.apply(my_func, axis = 1, result_type=\"expand\")"
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