{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "ee7327cd-811d-4c20-a1f0-79eb6f6371d8",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "2bf45cb0-054d-4771-8116-767c86176dd4",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    <tr style=\"text-align: right;\">\n",
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       "      <th>User ID</th>\n",
       "      <th>Username</th>\n",
       "      <th>Age</th>\n",
       "      <th>Joined Date</th>\n",
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       "      <td>2032-01-01</td>\n",
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       "      <td>2032-02-15</td>\n",
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       "      <td>bob56</td>\n",
       "      <td>38.0</td>\n",
       "      <td>2032-06-21</td>\n",
       "      <td>420</td>\n",
       "      <td>940</td>\n",
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       "      <td>500</td>\n",
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      "text/plain": [
       "   User ID     Username   Age Joined Date  Total Posts  Reputation\n",
       "0        1     bogdan_s  18.0  2032-01-01          150         500\n",
       "1        2   jane_smith  35.0  2032-02-15          230         720\n",
       "2        3      alex123  25.0  2032-04-25           80         200\n",
       "3        4        bob56  38.0  2032-06-21          420         940\n",
       "4        5  mark_wilson   NaN  2032-09-15          310         500"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forum_users = {\n",
    "    'User ID': np.array([1, 2, 3, 4, 5]),\n",
    "    'Username': ['bogdan_s', 'jane_smith', 'alex123', 'bob56', 'mark_wilson'],\n",
    "    'Age': [18, 35, 25, 38, None],\n",
    "    'Joined Date': pd.to_datetime(['2032-01-01', '2032-02-15', '2032-04-25', '2032-06-21', '2032-09-15']),\n",
    "    'Total Posts': [150, 230, 80, 420, 310],\n",
    "    'Reputation': [500, 720, 200, 940, 500]\n",
    "}\n",
    "\n",
    "df = pd.DataFrame(forum_users)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "e3320801-21e9-4b27-bb7b-52d265391a9e",
   "metadata": {},
   "outputs": [
    {
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       "      <td>500</td>\n",
       "      <td>English</td>\n",
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      ],
      "text/plain": [
       "   User ID     Username   Age Joined Date  Total Posts  Reputation Language\n",
       "0        1     bogdan_s  18.0  2032-01-01          150         500  English\n",
       "1        2   jane_smith  35.0  2032-02-15          230         720  English\n",
       "2        3      alex123  25.0  2032-04-25           80         200  English\n",
       "3        4        bob56  38.0  2032-06-21          420         940  English\n",
       "4        5  mark_wilson   NaN  2032-09-15          310         500  English"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Language'] = 'English'\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "be48a148-2e8d-4c31-92ee-ae29e37b3a0b",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   User ID     Username   Age Joined Date  Total Posts  Reputation Language  \\\n",
       "0        1     bogdan_s  18.0  2032-01-01          150         500  English   \n",
       "1        2   jane_smith  35.0  2032-02-15          230         720  English   \n",
       "2        3      alex123  25.0  2032-04-25           80         200  English   \n",
       "3        4        bob56  38.0  2032-06-21          420         940  English   \n",
       "4        5  mark_wilson   NaN  2032-09-15          310         500  English   \n",
       "\n",
       "   Active  \n",
       "0    True  \n",
       "1   False  \n",
       "2   False  \n",
       "3    True  \n",
       "4    True  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Active'] = np.array([True, False, False, True, True])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "75baabdd-f82e-4f79-b68c-6a5f6015f877",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "   Total Comments\n",
       "0              70\n",
       "1              30\n",
       "2              45\n",
       "3              55\n",
       "4              80"
      ]
     },
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   "source": [
    "total_comments = {\n",
    "    'Total Comments': [70, 30, 45, 55, 80]\n",
    "}\n",
    "\n",
    "df2 = pd.DataFrame(total_comments)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "10d1123a-6cb3-4f22-9938-566203065923",
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    {
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      ],
      "text/plain": [
       "   User ID     Username   Age Joined Date  Total Posts  Reputation Language  \\\n",
       "0      1.0     bogdan_s  18.0  2032-01-01        150.0       500.0  English   \n",
       "1      2.0   jane_smith  35.0  2032-02-15        230.0       720.0  English   \n",
       "2      3.0      alex123  25.0  2032-04-25         80.0       200.0  English   \n",
       "3      4.0        bob56  38.0  2032-06-21        420.0       940.0  English   \n",
       "4      5.0  mark_wilson   NaN  2032-09-15        310.0       500.0  English   \n",
       "0      NaN          NaN   NaN         NaT          NaN         NaN      NaN   \n",
       "1      NaN          NaN   NaN         NaT          NaN         NaN      NaN   \n",
       "2      NaN          NaN   NaN         NaT          NaN         NaN      NaN   \n",
       "3      NaN          NaN   NaN         NaT          NaN         NaN      NaN   \n",
       "4      NaN          NaN   NaN         NaT          NaN         NaN      NaN   \n",
       "\n",
       "  Active  Total Comments  \n",
       "0   True             NaN  \n",
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       "1    NaN            30.0  \n",
       "2    NaN            45.0  \n",
       "3    NaN            55.0  \n",
       "4    NaN            80.0  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "# By default concat works on the Axis 0!\n",
    "pd.concat([df, df2])"
   ]
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   "cell_type": "code",
   "execution_count": 46,
   "id": "fb7378de-519d-40dc-b3a0-ca634bdfaa88",
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    {
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       "   User ID     Username   Age Joined Date  Total Posts  Reputation Language  \\\n",
       "0        1     bogdan_s  18.0  2032-01-01          150         500  English   \n",
       "1        2   jane_smith  35.0  2032-02-15          230         720  English   \n",
       "2        3      alex123  25.0  2032-04-25           80         200  English   \n",
       "3        4        bob56  38.0  2032-06-21          420         940  English   \n",
       "4        5  mark_wilson   NaN  2032-09-15          310         500  English   \n",
       "\n",
       "   Active  Total Comments  \n",
       "0    True              70  \n",
       "1   False              30  \n",
       "2   False              45  \n",
       "3    True              55  \n",
       "4    True              80  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
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   "source": [
    "df = pd.concat([df, df2], axis=1)\n",
    "df"
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   "execution_count": 47,
   "id": "48497b8e-3370-4b55-87d9-896a11c96bcc",
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    {
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      "text/plain": [
       "   User ID     Username   Age Joined Date  Total Posts  Reputation  Active  \\\n",
       "0        1     bogdan_s  18.0  2032-01-01          150         500    True   \n",
       "1        2   jane_smith  35.0  2032-02-15          230         720   False   \n",
       "2        3      alex123  25.0  2032-04-25           80         200   False   \n",
       "3        4        bob56  38.0  2032-06-21          420         940    True   \n",
       "4        5  mark_wilson   NaN  2032-09-15          310         500    True   \n",
       "\n",
       "   Total Comments  \n",
       "0              70  \n",
       "1              30  \n",
       "2              45  \n",
       "3              55  \n",
       "4              80  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
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   ],
   "source": [
    "# Original df doesn't change\n",
    "df.drop(['Language'], axis=1)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 48,
   "id": "15577e6a-c570-4827-b6ea-28ea25b2244e",
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    {
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       "   User ID     Username   Age Joined Date  Total Posts  Reputation Language  \\\n",
       "0        1     bogdan_s  18.0  2032-01-01          150         500  English   \n",
       "1        2   jane_smith  35.0  2032-02-15          230         720  English   \n",
       "2        3      alex123  25.0  2032-04-25           80         200  English   \n",
       "3        4        bob56  38.0  2032-06-21          420         940  English   \n",
       "4        5  mark_wilson   NaN  2032-09-15          310         500  English   \n",
       "\n",
       "   Active  Total Comments  \n",
       "0    True              70  \n",
       "1   False              30  \n",
       "2   False              45  \n",
       "3    True              55  \n",
       "4    True              80  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
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   "id": "d0b85919-4668-4f91-a768-05cc35a9522f",
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       "   User ID     Username   Age Joined Date  Reputation  Active  Total Comments\n",
       "0        1     bogdan_s  18.0  2032-01-01         500    True              70\n",
       "1        2   jane_smith  35.0  2032-02-15         720   False              30\n",
       "2        3      alex123  25.0  2032-04-25         200   False              45\n",
       "3        4        bob56  38.0  2032-06-21         940    True              55\n",
       "4        5  mark_wilson   NaN  2032-09-15         500    True              80"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# Original df is changed inplace\n",
    "df.drop(['Language', 'Total Posts'], axis=1, inplace=True)\n",
    "df"
   ]
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   "cell_type": "code",
   "execution_count": 50,
   "id": "4e0a992e-55ae-4182-b95b-fd1f70606b4a",
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       "   User ID     Username   Age Joined Date  Reputation  Active  Total Comments\n",
       "0        1     bogdan_s  18.0  2032-01-01         500    True              70\n",
       "1        2   jane_smith  35.0  2032-02-15         720   False              30\n",
       "4        5  mark_wilson   NaN  2032-09-15         500    True              80"
      ]
     },
     "execution_count": 50,
     "metadata": {},
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    "df.drop([2, 3], inplace=True)\n",
    "df"
   ]
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