Pandas-Join&Merge.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a97fd230",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cc9d449e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  student_id              name  marks\n",
      "0         S1  Danniella Fenton    200\n",
      "1         S2      Ryder Storey    210\n",
      "2         S3      Bryce Jensen    190\n",
      "3         S4         Ed Bernal    222\n",
      "4         S5       Kwame Morin    199\n",
      "  student_id              name  marks\n",
      "0         S4  Scarlette Fisher    201\n",
      "1         S5  Carla Williamson    200\n",
      "2         S6       Dante Morse    198\n",
      "3         S7    Kaiser William    219\n",
      "4         S8   Madeeha Preston    201\n"
     ]
    }
   ],
   "source": [
    "student_data1 = pd.DataFrame({\n",
    "        'student_id': ['S1', 'S2', 'S3', 'S4', 'S5'],\n",
    "         'name': ['Danniella Fenton', 'Ryder Storey', 'Bryce Jensen', 'Ed Bernal', 'Kwame Morin'], \n",
    "        'marks': [200, 210, 190, 222, 199]})\n",
    "print(student_data1)\n",
    "student_data2 = pd.DataFrame({\n",
    "        'student_id': ['S4', 'S5', 'S6', 'S7', 'S8'],\n",
    "        'name': ['Scarlette Fisher', 'Carla Williamson', 'Dante Morse', 'Kaiser William', 'Madeeha Preston'], \n",
    "        'marks': [201, 200, 198, 219, 201]})\n",
    "print(student_data2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "45987f1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name</th>\n",
       "      <th>marks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S1</td>\n",
       "      <td>Danniella Fenton</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2</td>\n",
       "      <td>Ryder Storey</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S3</td>\n",
       "      <td>Bryce Jensen</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S4</td>\n",
       "      <td>Ed Bernal</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S5</td>\n",
       "      <td>Kwame Morin</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S4</td>\n",
       "      <td>Scarlette Fisher</td>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S5</td>\n",
       "      <td>Carla Williamson</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S6</td>\n",
       "      <td>Dante Morse</td>\n",
       "      <td>198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S7</td>\n",
       "      <td>Kaiser William</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S8</td>\n",
       "      <td>Madeeha Preston</td>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  student_id              name  marks\n",
       "0         S1  Danniella Fenton    200\n",
       "1         S2      Ryder Storey    210\n",
       "2         S3      Bryce Jensen    190\n",
       "3         S4         Ed Bernal    222\n",
       "4         S5       Kwame Morin    199\n",
       "0         S4  Scarlette Fisher    201\n",
       "1         S5  Carla Williamson    200\n",
       "2         S6       Dante Morse    198\n",
       "3         S7    Kaiser William    219\n",
       "4         S8   Madeeha Preston    201"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# join along rows\n",
    "merge_data = pd.concat([student_data1, student_data2])\n",
    "merge_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d0f119b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name</th>\n",
       "      <th>marks</th>\n",
       "      <th>student_id</th>\n",
       "      <th>name</th>\n",
       "      <th>marks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S1</td>\n",
       "      <td>Danniella Fenton</td>\n",
       "      <td>200</td>\n",
       "      <td>S4</td>\n",
       "      <td>Scarlette Fisher</td>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2</td>\n",
       "      <td>Ryder Storey</td>\n",
       "      <td>210</td>\n",
       "      <td>S5</td>\n",
       "      <td>Carla Williamson</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S3</td>\n",
       "      <td>Bryce Jensen</td>\n",
       "      <td>190</td>\n",
       "      <td>S6</td>\n",
       "      <td>Dante Morse</td>\n",
       "      <td>198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S4</td>\n",
       "      <td>Ed Bernal</td>\n",
       "      <td>222</td>\n",
       "      <td>S7</td>\n",
       "      <td>Kaiser William</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S5</td>\n",
       "      <td>Kwame Morin</td>\n",
       "      <td>199</td>\n",
       "      <td>S8</td>\n",
       "      <td>Madeeha Preston</td>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  student_id              name  marks student_id              name  marks\n",
       "0         S1  Danniella Fenton    200         S4  Scarlette Fisher    201\n",
       "1         S2      Ryder Storey    210         S5  Carla Williamson    200\n",
       "2         S3      Bryce Jensen    190         S6       Dante Morse    198\n",
       "3         S4         Ed Bernal    222         S7    Kaiser William    219\n",
       "4         S5       Kwame Morin    199         S8   Madeeha Preston    201"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# join along columns\n",
    "result_data = pd.concat([student_data1, student_data2], axis = 1)\n",
    "result_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f726b141",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name</th>\n",
       "      <th>marks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S1</td>\n",
       "      <td>Danniella Fenton</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2</td>\n",
       "      <td>Ryder Storey</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S3</td>\n",
       "      <td>Bryce Jensen</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S4</td>\n",
       "      <td>Ed Bernal</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S5</td>\n",
       "      <td>Kwame Morin</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>S6</td>\n",
       "      <td>Scarlette Fisher</td>\n",
       "      <td>205</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  student_id              name  marks\n",
       "0         S1  Danniella Fenton    200\n",
       "1         S2      Ryder Storey    210\n",
       "2         S3      Bryce Jensen    190\n",
       "3         S4         Ed Bernal    222\n",
       "4         S5       Kwame Morin    199\n",
       "5         S6  Scarlette Fisher    205"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Q3\n",
    "s6 = pd.Series(['S6', 'Scarlette Fisher', 205], index=['student_id', 'name', 'marks'])\n",
    "\n",
    "combine_data = student_data1.append(s6,ignore_index=True)\n",
    "combine_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c185207c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name</th>\n",
       "      <th>marks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S1</td>\n",
       "      <td>Danniella Fenton</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2</td>\n",
       "      <td>Ryder Storey</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S3</td>\n",
       "      <td>Bryce Jensen</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S4</td>\n",
       "      <td>Ed Bernal</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S5</td>\n",
       "      <td>Kwame Morin</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>S6</td>\n",
       "      <td>Scarlette Fisher</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>S7</td>\n",
       "      <td>Bryce Jensen</td>\n",
       "      <td>207</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  student_id              name  marks\n",
       "0         S1  Danniella Fenton    200\n",
       "1         S2      Ryder Storey    210\n",
       "2         S3      Bryce Jensen    190\n",
       "3         S4         Ed Bernal    222\n",
       "4         S5       Kwame Morin    199\n",
       "5         S6  Scarlette Fisher    203\n",
       "6         S7      Bryce Jensen    207"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Q4\n",
    "dicts = [{'student_id': 'S6', 'name': 'Scarlette Fisher', 'marks': 203},\n",
    "         {'student_id': 'S7', 'name': 'Bryce Jensen', 'marks': 207}]\n",
    "combined_data =  student_data1.append(dicts, ignore_index=True, sort=False)\n",
    "combined_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "05cdf22c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name</th>\n",
       "      <th>marks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S1</td>\n",
       "      <td>Danniella Fenton</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2</td>\n",
       "      <td>Ryder Storey</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S3</td>\n",
       "      <td>Bryce Jensen</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S4</td>\n",
       "      <td>Ed Bernal</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S5</td>\n",
       "      <td>Kwame Morin</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S4</td>\n",
       "      <td>Scarlette Fisher</td>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S5</td>\n",
       "      <td>Carla Williamson</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S6</td>\n",
       "      <td>Dante Morse</td>\n",
       "      <td>198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S7</td>\n",
       "      <td>Kaiser William</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S8</td>\n",
       "      <td>Madeeha Preston</td>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  student_id              name  marks\n",
       "0         S1  Danniella Fenton    200\n",
       "1         S2      Ryder Storey    210\n",
       "2         S3      Bryce Jensen    190\n",
       "3         S4         Ed Bernal    222\n",
       "4         S5       Kwame Morin    199\n",
       "0         S4  Scarlette Fisher    201\n",
       "1         S5  Carla Williamson    200\n",
       "2         S6       Dante Morse    198\n",
       "3         S7    Kaiser William    219\n",
       "4         S8   Madeeha Preston    201"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Q5\n",
    "student_data1 = pd.DataFrame({\n",
    "        'student_id': ['S1', 'S2', 'S3', 'S4', 'S5'],\n",
    "         'name': ['Danniella Fenton', 'Ryder Storey', 'Bryce Jensen', 'Ed Bernal', 'Kwame Morin'], \n",
    "        'marks': [200, 210, 190, 222, 199]})\n",
    "\n",
    "student_data2 = pd.DataFrame({\n",
    "        'student_id': ['S4', 'S5', 'S6', 'S7', 'S8'],\n",
    "        'name': ['Scarlette Fisher', 'Carla Williamson', 'Dante Morse', 'Kaiser William', 'Madeeha Preston'], \n",
    "        'marks': [201, 200, 198, 219, 201]})\n",
    "\n",
    "exam_data = pd.DataFrame({\n",
    "        'student_id': ['S1', 'S2', 'S3', 'S4', 'S5', 'S7', 'S8', 'S9', 'S10', 'S11', 'S12', 'S13'],\n",
    "        'exam_id': [23, 45, 12, 67, 21, 55, 33, 14, 56, 83, 88, 12]})\n",
    "\n",
    "merge_data = pd.concat([student_data1, student_data2])\n",
    "merge_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f86528dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name</th>\n",
       "      <th>marks</th>\n",
       "      <th>exam_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S1</td>\n",
       "      <td>Danniella Fenton</td>\n",
       "      <td>200</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2</td>\n",
       "      <td>Ryder Storey</td>\n",
       "      <td>210</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S3</td>\n",
       "      <td>Bryce Jensen</td>\n",
       "      <td>190</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S4</td>\n",
       "      <td>Ed Bernal</td>\n",
       "      <td>222</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S4</td>\n",
       "      <td>Scarlette Fisher</td>\n",
       "      <td>201</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>S5</td>\n",
       "      <td>Kwame Morin</td>\n",
       "      <td>199</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>S5</td>\n",
       "      <td>Carla Williamson</td>\n",
       "      <td>200</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S7</td>\n",
       "      <td>Kaiser William</td>\n",
       "      <td>219</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>S8</td>\n",
       "      <td>Madeeha Preston</td>\n",
       "      <td>201</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  student_id              name  marks  exam_id\n",
       "0         S1  Danniella Fenton    200       23\n",
       "1         S2      Ryder Storey    210       45\n",
       "2         S3      Bryce Jensen    190       12\n",
       "3         S4         Ed Bernal    222       67\n",
       "4         S4  Scarlette Fisher    201       67\n",
       "5         S5       Kwame Morin    199       21\n",
       "6         S5  Carla Williamson    200       21\n",
       "7         S7    Kaiser William    219       55\n",
       "8         S8   Madeeha Preston    201       33"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_merged_data = pd.merge(merge_data, exam_data, on='student_id')\n",
    "final_merged_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3cbbdf80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name_x</th>\n",
       "      <th>marks_x</th>\n",
       "      <th>name_y</th>\n",
       "      <th>marks_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S4</td>\n",
       "      <td>Ed Bernal</td>\n",
       "      <td>222</td>\n",
       "      <td>Scarlette Fisher</td>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S5</td>\n",
       "      <td>Kwame Morin</td>\n",
       "      <td>199</td>\n",
       "      <td>Carla Williamson</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  student_id       name_x  marks_x            name_y  marks_y\n",
       "0         S4    Ed Bernal      222  Scarlette Fisher      201\n",
       "1         S5  Kwame Morin      199  Carla Williamson      200"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Q6\n",
    "common_merge = pd.merge(student_data1, student_data2, on='student_id', how='inner')\n",
    "common_merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "33906386",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name_x</th>\n",
       "      <th>marks_x</th>\n",
       "      <th>name_y</th>\n",
       "      <th>marks_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S1</td>\n",
       "      <td>Danniella Fenton</td>\n",
       "      <td>200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2</td>\n",
       "      <td>Ryder Storey</td>\n",
       "      <td>210.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S3</td>\n",
       "      <td>Bryce Jensen</td>\n",
       "      <td>190.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S4</td>\n",
       "      <td>Ed Bernal</td>\n",
       "      <td>222.0</td>\n",
       "      <td>Scarlette Fisher</td>\n",
       "      <td>201.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S5</td>\n",
       "      <td>Kwame Morin</td>\n",
       "      <td>199.0</td>\n",
       "      <td>Carla Williamson</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>S6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dante Morse</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>S7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kaiser William</td>\n",
       "      <td>219.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Madeeha Preston</td>\n",
       "      <td>201.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  student_id            name_x  marks_x            name_y  marks_y\n",
       "0         S1  Danniella Fenton    200.0               NaN      NaN\n",
       "1         S2      Ryder Storey    210.0               NaN      NaN\n",
       "2         S3      Bryce Jensen    190.0               NaN      NaN\n",
       "3         S4         Ed Bernal    222.0  Scarlette Fisher    201.0\n",
       "4         S5       Kwame Morin    199.0  Carla Williamson    200.0\n",
       "5         S6               NaN      NaN       Dante Morse    198.0\n",
       "6         S7               NaN      NaN    Kaiser William    219.0\n",
       "7         S8               NaN      NaN   Madeeha Preston    201.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Q7\n",
    "outer_merge = pd.merge(student_data1, student_data2, on='student_id', how='outer')\n",
    "outer_merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4f23b3e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  key1 key2   P   Q\n",
      "0   K0   K0  P0  Q0\n",
      "1   K0   K1  P1  Q1\n",
      "2   K1   K0  P2  Q2\n",
      "3   K2   K1  P3  Q3\n",
      "  key1 key2   R   S\n",
      "0   K0   K0  R0  S0\n",
      "1   K1   K0  R1  S1\n",
      "2   K1   K0  R2  S2\n",
      "3   K2   K0  R3  S3\n",
      "\n",
      "Merged Data (keys from data1):\n",
      "  key1 key2   P   Q    R    S\n",
      "0   K0   K0  P0  Q0   R0   S0\n",
      "1   K0   K1  P1  Q1  NaN  NaN\n",
      "2   K1   K0  P2  Q2   R1   S1\n",
      "3   K1   K0  P2  Q2   R2   S2\n",
      "4   K2   K1  P3  Q3  NaN  NaN\n",
      "\n",
      "Merged Data (keys from data2):\n",
      "  key1 key2   R   S    P    Q\n",
      "0   K0   K0  R0  S0   P0   Q0\n",
      "1   K1   K0  R1  S1   P2   Q2\n",
      "2   K1   K0  R2  S2   P2   Q2\n",
      "3   K2   K0  R3  S3  NaN  NaN\n"
     ]
    }
   ],
   "source": [
    "#Q8\n",
    "data1 = pd.DataFrame({'key1': ['K0', 'K0', 'K1', 'K2'],\n",
    "                     'key2': ['K0', 'K1', 'K0', 'K1'],\n",
    "                     'P': ['P0', 'P1', 'P2', 'P3'],\n",
    "                     'Q': ['Q0', 'Q1', 'Q2', 'Q3']}) \n",
    "print(data1)\n",
    "data2 = pd.DataFrame({'key1': ['K0', 'K1', 'K1', 'K2'],\n",
    "                      'key2': ['K0', 'K0', 'K0', 'K0'],\n",
    "                      'R': ['R0', 'R1', 'R2', 'R3'],\n",
    "                      'S': ['S0', 'S1', 'S2', 'S3']})\n",
    "print(data2)\n",
    "print(\"\\nMerged Data (keys from data1):\")\n",
    "merged_data = pd.merge(data1, data2, how='left', on=['key1', 'key2'])\n",
    "print(merged_data)\n",
    "print(\"\\nMerged Data (keys from data2):\")\n",
    "merged_data = pd.merge(data2, data1, how='left', on=['key1', 'key2'])\n",
    "print(merged_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6ffa4d94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>key1</th>\n",
       "      <th>key2</th>\n",
       "      <th>P</th>\n",
       "      <th>Q</th>\n",
       "      <th>R</th>\n",
       "      <th>S</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>K0</td>\n",
       "      <td>K0</td>\n",
       "      <td>P0</td>\n",
       "      <td>Q0</td>\n",
       "      <td>R0</td>\n",
       "      <td>S0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "      <td>P2</td>\n",
       "      <td>Q2</td>\n",
       "      <td>R1</td>\n",
       "      <td>S1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "      <td>P2</td>\n",
       "      <td>Q2</td>\n",
       "      <td>R2</td>\n",
       "      <td>S2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>K2</td>\n",
       "      <td>K0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>R3</td>\n",
       "      <td>S3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  key1 key2    P    Q   R   S\n",
       "0   K0   K0   P0   Q0  R0  S0\n",
       "1   K1   K0   P2   Q2  R1  S1\n",
       "2   K1   K0   P2   Q2  R2  S2\n",
       "3   K2   K0  NaN  NaN  R3  S3"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Q9\n",
    "merged_data = pd.merge(data1, data2, how='right', on=['key1', 'key2'])\n",
    "merged_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9b64ef04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>key1</th>\n",
       "      <th>key2</th>\n",
       "      <th>P</th>\n",
       "      <th>Q</th>\n",
       "      <th>R</th>\n",
       "      <th>S</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>K0</td>\n",
       "      <td>K0</td>\n",
       "      <td>P0</td>\n",
       "      <td>Q0</td>\n",
       "      <td>R0</td>\n",
       "      <td>S0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "      <td>P2</td>\n",
       "      <td>Q2</td>\n",
       "      <td>R1</td>\n",
       "      <td>S1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "      <td>P2</td>\n",
       "      <td>Q2</td>\n",
       "      <td>R2</td>\n",
       "      <td>S2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  key1 key2   P   Q   R   S\n",
       "0   K0   K0  P0  Q0  R0  S0\n",
       "1   K1   K0  P2  Q2  R1  S1\n",
       "2   K1   K0  P2  Q2  R2  S2"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Q10\n",
    "merged_data = pd.merge(data1, data2, on=['key1', 'key2'])\n",
    "merged_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b9f448b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   column1  column2  column3\n",
      "0        0        0        0\n",
      "1        1        1        1\n",
      "2        2        2        4\n",
      "3        3        3        5\n"
     ]
    }
   ],
   "source": [
    "#Q11\n",
    "\n",
    "s1 = pd.Series([0, 1, 2, 3], name='col1')\n",
    "s2 = pd.Series([0, 1, 2, 3])\n",
    "s3 = pd.Series([0, 1, 4, 5], name='col3')\n",
    "df = pd.concat([s1, s2, s3], axis=1, keys=['column1', 'column2', 'column3'])\n",
    "print(df)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "758e2d50",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>key1</th>\n",
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       "      <th>0</th>\n",
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       "      <td>R0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "      <td>P2</td>\n",
       "      <td>Q2</td>\n",
       "      <td>K0</td>\n",
       "      <td>R1</td>\n",
       "      <td>S1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "      <td>P2</td>\n",
       "      <td>Q2</td>\n",
       "      <td>K0</td>\n",
       "      <td>R2</td>\n",
       "      <td>S2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>K2</td>\n",
       "      <td>K1</td>\n",
       "      <td>P3</td>\n",
       "      <td>Q3</td>\n",
       "      <td>K0</td>\n",
       "      <td>R3</td>\n",
       "      <td>S3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  key1 key2_x   P   Q key2_y   R   S\n",
       "0   K0     K0  P0  Q0     K0  R0  S0\n",
       "1   K0     K1  P1  Q1     K0  R0  S0\n",
       "2   K1     K0  P2  Q2     K0  R1  S1\n",
       "3   K1     K0  P2  Q2     K0  R2  S2\n",
       "4   K2     K1  P3  Q3     K0  R3  S3"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Q12\n",
    "merger = pd.merge(data1, data2, on='key1')\n",
    "merger"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "66f65ded",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original DataFrames:\n",
      "     A   B\n",
      "K0  A0  B0\n",
      "K1  A1  B1\n",
      "K2  A2  B2\n",
      "--------------------\n",
      "     C   D\n",
      "K0  C0  D0\n",
      "K2  C2  D2\n",
      "K3  C3  D3\n",
      "\n",
      "Merged Data (Joining on index):\n",
      "     A   B    C    D\n",
      "K0  A0  B0   C0   D0\n",
      "K1  A1  B1  NaN  NaN\n",
      "K2  A2  B2   C2   D2\n"
     ]
    }
   ],
   "source": [
    "#Q13\n",
    "data1 = pd.DataFrame({'A': ['A0', 'A1', 'A2'],\n",
    "                      'B': ['B0', 'B1', 'B2']},\n",
    "                     index=['K0', 'K1', 'K2'])\n",
    "\n",
    "data2 = pd.DataFrame({'C': ['C0', 'C2', 'C3'],\n",
    "                      'D': ['D0', 'D2', 'D3']},\n",
    "                     index=['K0', 'K2', 'K3'])\n",
    " \n",
    "print(\"Original DataFrames:\")\n",
    "print(data1)\n",
    "print(\"--------------------\")\n",
    "print(data2)\n",
    "print(\"\\nMerged Data (Joining on index):\")\n",
    "result = data1.join(data2)\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d7eda03e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original DataFrames:\n",
      "  key1 key2   P   Q\n",
      "0   K0   K0  P0  Q0\n",
      "1   K0   K1  P1  Q1\n",
      "2   K1   K0  P2  Q2\n",
      "3   K2   K1  P3  Q3\n",
      "--------------------\n",
      "  key1 key2   R   S\n",
      "0   K0   K0  R0  S0\n",
      "1   K1   K0  R1  S1\n",
      "2   K1   K0  R2  S2\n",
      "3   K2   K0  R3  S3\n",
      "\n",
      "Merge two dataframes with different columns:\n",
      "  key1 key2    P    Q    R    S\n",
      "0   K0   K0   P0   Q0  NaN  NaN\n",
      "1   K0   K1   P1   Q1  NaN  NaN\n",
      "2   K1   K0   P2   Q2  NaN  NaN\n",
      "3   K2   K1   P3   Q3  NaN  NaN\n",
      "4   K0   K0  NaN  NaN   R0   S0\n",
      "5   K1   K0  NaN  NaN   R1   S1\n",
      "6   K1   K0  NaN  NaN   R2   S2\n",
      "7   K2   K0  NaN  NaN   R3   S3\n"
     ]
    }
   ],
   "source": [
    "#Q14\n",
    "data1 = pd.DataFrame({'key1': ['K0', 'K0', 'K1', 'K2'],\n",
    "                     'key2': ['K0', 'K1', 'K0', 'K1'],\n",
    "                     'P': ['P0', 'P1', 'P2', 'P3'],\n",
    "                     'Q': ['Q0', 'Q1', 'Q2', 'Q3']}) \n",
    "data2 = pd.DataFrame({'key1': ['K0', 'K1', 'K1', 'K2'],\n",
    "                      'key2': ['K0', 'K0', 'K0', 'K0'],\n",
    "                      'R': ['R0', 'R1', 'R2', 'R3'],\n",
    "                      'S': ['S0', 'S1', 'S2', 'S3']})\n",
    "print(\"Original DataFrames:\")\n",
    "print(data1)\n",
    "print(\"--------------------\")\n",
    "print(data2)\n",
    "print(\"\\nMerge two dataframes with different columns:\")\n",
    "result = pd.concat([data1,data2], axis=0, ignore_index=True)\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a26fbb15",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original DataFrames:\n",
      "     A  B\n",
      "0  NaN  3\n",
      "1  0.0  4\n",
      "2  NaN  5\n",
      "--------------------\n",
      "   A    B\n",
      "0  1  3.0\n",
      "1  1  NaN\n",
      "2  3  3.0\n",
      "\n",
      "Merge two dataframes with different columns:\n",
      "     A    B\n",
      "0  1.0  3.0\n",
      "1  0.0  4.0\n",
      "2  3.0  5.0\n"
     ]
    }
   ],
   "source": [
    "#Q15\n",
    "df1 = pd.DataFrame({'A': [None, 0, None], 'B': [3, 4, 5]})\n",
    "df2 = pd.DataFrame({'A': [1, 1, 3], 'B': [3, None, 3]})\n",
    "df1.combine_first(df2)\n",
    "print(\"Original DataFrames:\")\n",
    "print(df1)\n",
    "print(\"--------------------\")\n",
    "print(df2)\n",
    "print(\"\\nMerge two dataframes with different columns:\")\n",
    "result = df1.combine_first(df2)\n",
    "print(result)"
   ]
  }
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