├── pandas day 1
├── pandas day 1.ipynb
├── pandas day 2  (1).ipynb
└── pandas day 3 (1).ipynb


/pandas day 1:
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 1 | data link - https://drive.google.com/drive/folders/1zauEUoewFclurlYCh89FHgDfW9is6Y_r?usp=share_link
 2 | 
 3 | Excel data  - https://docs.google.com/spreadsheets/d/1fzzsmqAiC_yoiB2k1inDYVCYQ-Djo4G1/edit?usp=share_link&ouid=111840944180463951908&rtpof=true&sd=true
 4 | 
 5 | Excel Data Airline 1 - https://docs.google.com/spreadsheets/d/1tGh7f3JkPS2TQXLtzdB-JWGCAwRHCxYE/edit?usp=share_link&ouid=111840944180463951908&rtpof=true&sd=true
 6 | 
 7 | git hub data - https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv
 8 | 
 9 | read from html - https://www.basketball-reference.com/leagues/NBA_2015_totals.html
10 | 


--------------------------------------------------------------------------------
/pandas day 3 (1).ipynb:
--------------------------------------------------------------------------------
   1 | {
   2 |  "cells": [
   3 |   {
   4 |    "cell_type": "code",
   5 |    "execution_count": 2,
   6 |    "id": "2634dd02-5e1b-4bef-9a38-7198b2c1990e",
   7 |    "metadata": {},
   8 |    "outputs": [],
   9 |    "source": [
  10 |     "d1 = {'key1':[1,2,3,4,5,\"sudh\"],\n",
  11 |     "      'key2' : [7,8,9,10,11,12],\n",
  12 |     "      'key3':[13,14,15,16,17,18],\n",
  13 |     "      'key4':[19,20,21,22,23,24]\n",
  14 |     "}"
  15 |    ]
  16 |   },
  17 |   {
  18 |    "cell_type": "code",
  19 |    "execution_count": 3,
  20 |    "id": "098f537b-eeef-4326-8a77-e374e041aac5",
  21 |    "metadata": {},
  22 |    "outputs": [],
  23 |    "source": [
  24 |     "import pandas as pd "
  25 |    ]
  26 |   },
  27 |   {
  28 |    "cell_type": "code",
  29 |    "execution_count": 4,
  30 |    "id": "05e765e2-cfa0-49b7-a457-38a983c06b59",
  31 |    "metadata": {},
  32 |    "outputs": [],
  33 |    "source": [
  34 |     "df1 = pd.DataFrame(d1 )"
  35 |    ]
  36 |   },
  37 |   {
  38 |    "cell_type": "code",
  39 |    "execution_count": 5,
  40 |    "id": "3aaa77ad-bdec-4364-a347-0151d7c0e333",
  41 |    "metadata": {},
  42 |    "outputs": [],
  43 |    "source": [
  44 |     "d2 = {'key1':[1,2,3,4,5,\"sudh\"],\n",
  45 |     "      'key2' : [7,8,\"kumar\",10,11,12],\n",
  46 |     "      'key3':[13,14,15,16,17,18],\n",
  47 |     "      'key4':[19,20,21,\"ineuron\",\"pwskills\",24]\n",
  48 |     "}"
  49 |    ]
  50 |   },
  51 |   {
  52 |    "cell_type": "code",
  53 |    "execution_count": 6,
  54 |    "id": "9cca371e-4e10-466c-8608-438e750d2d05",
  55 |    "metadata": {},
  56 |    "outputs": [],
  57 |    "source": [
  58 |     "df2 = pd.DataFrame(d2)"
  59 |    ]
  60 |   },
  61 |   {
  62 |    "cell_type": "code",
  63 |    "execution_count": 7,
  64 |    "id": "a09f3e4d-1ca2-43ac-86eb-b2a74c135044",
  65 |    "metadata": {},
  66 |    "outputs": [
  67 |     {
  68 |      "data": {
  69 |       "text/html": [
  70 |        "<div>\n",
  71 |        "<style scoped>\n",
  72 |        "    .dataframe tbody tr th:only-of-type {\n",
  73 |        "        vertical-align: middle;\n",
  74 |        "    }\n",
  75 |        "\n",
  76 |        "    .dataframe tbody tr th {\n",
  77 |        "        vertical-align: top;\n",
  78 |        "    }\n",
  79 |        "\n",
  80 |        "    .dataframe thead th {\n",
  81 |        "        text-align: right;\n",
  82 |        "    }\n",
  83 |        "</style>\n",
  84 |        "<table border=\"1\" class=\"dataframe\">\n",
  85 |        "  <thead>\n",
  86 |        "    <tr style=\"text-align: right;\">\n",
  87 |        "      <th></th>\n",
  88 |        "      <th>key1</th>\n",
  89 |        "      <th>key2</th>\n",
  90 |        "      <th>key3</th>\n",
  91 |        "      <th>key4</th>\n",
  92 |        "    </tr>\n",
  93 |        "  </thead>\n",
  94 |        "  <tbody>\n",
  95 |        "    <tr>\n",
  96 |        "      <th>0</th>\n",
  97 |        "      <td>1</td>\n",
  98 |        "      <td>7</td>\n",
  99 |        "      <td>13</td>\n",
 100 |        "      <td>19</td>\n",
 101 |        "    </tr>\n",
 102 |        "    <tr>\n",
 103 |        "      <th>1</th>\n",
 104 |        "      <td>2</td>\n",
 105 |        "      <td>8</td>\n",
 106 |        "      <td>14</td>\n",
 107 |        "      <td>20</td>\n",
 108 |        "    </tr>\n",
 109 |        "    <tr>\n",
 110 |        "      <th>2</th>\n",
 111 |        "      <td>3</td>\n",
 112 |        "      <td>9</td>\n",
 113 |        "      <td>15</td>\n",
 114 |        "      <td>21</td>\n",
 115 |        "    </tr>\n",
 116 |        "    <tr>\n",
 117 |        "      <th>3</th>\n",
 118 |        "      <td>4</td>\n",
 119 |        "      <td>10</td>\n",
 120 |        "      <td>16</td>\n",
 121 |        "      <td>22</td>\n",
 122 |        "    </tr>\n",
 123 |        "    <tr>\n",
 124 |        "      <th>4</th>\n",
 125 |        "      <td>5</td>\n",
 126 |        "      <td>11</td>\n",
 127 |        "      <td>17</td>\n",
 128 |        "      <td>23</td>\n",
 129 |        "    </tr>\n",
 130 |        "    <tr>\n",
 131 |        "      <th>5</th>\n",
 132 |        "      <td>sudh</td>\n",
 133 |        "      <td>12</td>\n",
 134 |        "      <td>18</td>\n",
 135 |        "      <td>24</td>\n",
 136 |        "    </tr>\n",
 137 |        "  </tbody>\n",
 138 |        "</table>\n",
 139 |        "</div>"
 140 |       ],
 141 |       "text/plain": [
 142 |        "   key1  key2  key3  key4\n",
 143 |        "0     1     7    13    19\n",
 144 |        "1     2     8    14    20\n",
 145 |        "2     3     9    15    21\n",
 146 |        "3     4    10    16    22\n",
 147 |        "4     5    11    17    23\n",
 148 |        "5  sudh    12    18    24"
 149 |       ]
 150 |      },
 151 |      "execution_count": 7,
 152 |      "metadata": {},
 153 |      "output_type": "execute_result"
 154 |     }
 155 |    ],
 156 |    "source": [
 157 |     "df1"
 158 |    ]
 159 |   },
 160 |   {
 161 |    "cell_type": "code",
 162 |    "execution_count": 8,
 163 |    "id": "afbc9a05-3ce2-484d-8287-8ce28a21cd4e",
 164 |    "metadata": {},
 165 |    "outputs": [
 166 |     {
 167 |      "data": {
 168 |       "text/html": [
 169 |        "<div>\n",
 170 |        "<style scoped>\n",
 171 |        "    .dataframe tbody tr th:only-of-type {\n",
 172 |        "        vertical-align: middle;\n",
 173 |        "    }\n",
 174 |        "\n",
 175 |        "    .dataframe tbody tr th {\n",
 176 |        "        vertical-align: top;\n",
 177 |        "    }\n",
 178 |        "\n",
 179 |        "    .dataframe thead th {\n",
 180 |        "        text-align: right;\n",
 181 |        "    }\n",
 182 |        "</style>\n",
 183 |        "<table border=\"1\" class=\"dataframe\">\n",
 184 |        "  <thead>\n",
 185 |        "    <tr style=\"text-align: right;\">\n",
 186 |        "      <th></th>\n",
 187 |        "      <th>key1</th>\n",
 188 |        "      <th>key2</th>\n",
 189 |        "      <th>key3</th>\n",
 190 |        "      <th>key4</th>\n",
 191 |        "    </tr>\n",
 192 |        "  </thead>\n",
 193 |        "  <tbody>\n",
 194 |        "    <tr>\n",
 195 |        "      <th>0</th>\n",
 196 |        "      <td>1</td>\n",
 197 |        "      <td>7</td>\n",
 198 |        "      <td>13</td>\n",
 199 |        "      <td>19</td>\n",
 200 |        "    </tr>\n",
 201 |        "    <tr>\n",
 202 |        "      <th>1</th>\n",
 203 |        "      <td>2</td>\n",
 204 |        "      <td>8</td>\n",
 205 |        "      <td>14</td>\n",
 206 |        "      <td>20</td>\n",
 207 |        "    </tr>\n",
 208 |        "    <tr>\n",
 209 |        "      <th>2</th>\n",
 210 |        "      <td>3</td>\n",
 211 |        "      <td>kumar</td>\n",
 212 |        "      <td>15</td>\n",
 213 |        "      <td>21</td>\n",
 214 |        "    </tr>\n",
 215 |        "    <tr>\n",
 216 |        "      <th>3</th>\n",
 217 |        "      <td>4</td>\n",
 218 |        "      <td>10</td>\n",
 219 |        "      <td>16</td>\n",
 220 |        "      <td>ineuron</td>\n",
 221 |        "    </tr>\n",
 222 |        "    <tr>\n",
 223 |        "      <th>4</th>\n",
 224 |        "      <td>5</td>\n",
 225 |        "      <td>11</td>\n",
 226 |        "      <td>17</td>\n",
 227 |        "      <td>pwskills</td>\n",
 228 |        "    </tr>\n",
 229 |        "    <tr>\n",
 230 |        "      <th>5</th>\n",
 231 |        "      <td>sudh</td>\n",
 232 |        "      <td>12</td>\n",
 233 |        "      <td>18</td>\n",
 234 |        "      <td>24</td>\n",
 235 |        "    </tr>\n",
 236 |        "  </tbody>\n",
 237 |        "</table>\n",
 238 |        "</div>"
 239 |       ],
 240 |       "text/plain": [
 241 |        "   key1   key2  key3      key4\n",
 242 |        "0     1      7    13        19\n",
 243 |        "1     2      8    14        20\n",
 244 |        "2     3  kumar    15        21\n",
 245 |        "3     4     10    16   ineuron\n",
 246 |        "4     5     11    17  pwskills\n",
 247 |        "5  sudh     12    18        24"
 248 |       ]
 249 |      },
 250 |      "execution_count": 8,
 251 |      "metadata": {},
 252 |      "output_type": "execute_result"
 253 |     }
 254 |    ],
 255 |    "source": [
 256 |     "df2"
 257 |    ]
 258 |   },
 259 |   {
 260 |    "cell_type": "code",
 261 |    "execution_count": 9,
 262 |    "id": "6bd5d2bc-99ee-4f10-ab60-b4f3e3e35d4d",
 263 |    "metadata": {},
 264 |    "outputs": [
 265 |     {
 266 |      "name": "stderr",
 267 |      "output_type": "stream",
 268 |      "text": [
 269 |       "/tmp/ipykernel_1400/1864705398.py:1: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
 270 |       "  pd.merge(df1,df2,how= 'outer',on= ['key4','key1'])\n"
 271 |      ]
 272 |     },
 273 |     {
 274 |      "data": {
 275 |       "text/html": [
 276 |        "<div>\n",
 277 |        "<style scoped>\n",
 278 |        "    .dataframe tbody tr th:only-of-type {\n",
 279 |        "        vertical-align: middle;\n",
 280 |        "    }\n",
 281 |        "\n",
 282 |        "    .dataframe tbody tr th {\n",
 283 |        "        vertical-align: top;\n",
 284 |        "    }\n",
 285 |        "\n",
 286 |        "    .dataframe thead th {\n",
 287 |        "        text-align: right;\n",
 288 |        "    }\n",
 289 |        "</style>\n",
 290 |        "<table border=\"1\" class=\"dataframe\">\n",
 291 |        "  <thead>\n",
 292 |        "    <tr style=\"text-align: right;\">\n",
 293 |        "      <th></th>\n",
 294 |        "      <th>key1</th>\n",
 295 |        "      <th>key2_x</th>\n",
 296 |        "      <th>key3_x</th>\n",
 297 |        "      <th>key4</th>\n",
 298 |        "      <th>key2_y</th>\n",
 299 |        "      <th>key3_y</th>\n",
 300 |        "    </tr>\n",
 301 |        "  </thead>\n",
 302 |        "  <tbody>\n",
 303 |        "    <tr>\n",
 304 |        "      <th>0</th>\n",
 305 |        "      <td>1</td>\n",
 306 |        "      <td>7.0</td>\n",
 307 |        "      <td>13.0</td>\n",
 308 |        "      <td>19.0</td>\n",
 309 |        "      <td>7</td>\n",
 310 |        "      <td>13.0</td>\n",
 311 |        "    </tr>\n",
 312 |        "    <tr>\n",
 313 |        "      <th>1</th>\n",
 314 |        "      <td>2</td>\n",
 315 |        "      <td>8.0</td>\n",
 316 |        "      <td>14.0</td>\n",
 317 |        "      <td>20.0</td>\n",
 318 |        "      <td>8</td>\n",
 319 |        "      <td>14.0</td>\n",
 320 |        "    </tr>\n",
 321 |        "    <tr>\n",
 322 |        "      <th>2</th>\n",
 323 |        "      <td>3</td>\n",
 324 |        "      <td>9.0</td>\n",
 325 |        "      <td>15.0</td>\n",
 326 |        "      <td>21.0</td>\n",
 327 |        "      <td>kumar</td>\n",
 328 |        "      <td>15.0</td>\n",
 329 |        "    </tr>\n",
 330 |        "    <tr>\n",
 331 |        "      <th>3</th>\n",
 332 |        "      <td>4</td>\n",
 333 |        "      <td>10.0</td>\n",
 334 |        "      <td>16.0</td>\n",
 335 |        "      <td>22.0</td>\n",
 336 |        "      <td>NaN</td>\n",
 337 |        "      <td>NaN</td>\n",
 338 |        "    </tr>\n",
 339 |        "    <tr>\n",
 340 |        "      <th>4</th>\n",
 341 |        "      <td>5</td>\n",
 342 |        "      <td>11.0</td>\n",
 343 |        "      <td>17.0</td>\n",
 344 |        "      <td>23.0</td>\n",
 345 |        "      <td>NaN</td>\n",
 346 |        "      <td>NaN</td>\n",
 347 |        "    </tr>\n",
 348 |        "    <tr>\n",
 349 |        "      <th>5</th>\n",
 350 |        "      <td>sudh</td>\n",
 351 |        "      <td>12.0</td>\n",
 352 |        "      <td>18.0</td>\n",
 353 |        "      <td>24.0</td>\n",
 354 |        "      <td>12</td>\n",
 355 |        "      <td>18.0</td>\n",
 356 |        "    </tr>\n",
 357 |        "    <tr>\n",
 358 |        "      <th>6</th>\n",
 359 |        "      <td>4</td>\n",
 360 |        "      <td>NaN</td>\n",
 361 |        "      <td>NaN</td>\n",
 362 |        "      <td>ineuron</td>\n",
 363 |        "      <td>10</td>\n",
 364 |        "      <td>16.0</td>\n",
 365 |        "    </tr>\n",
 366 |        "    <tr>\n",
 367 |        "      <th>7</th>\n",
 368 |        "      <td>5</td>\n",
 369 |        "      <td>NaN</td>\n",
 370 |        "      <td>NaN</td>\n",
 371 |        "      <td>pwskills</td>\n",
 372 |        "      <td>11</td>\n",
 373 |        "      <td>17.0</td>\n",
 374 |        "    </tr>\n",
 375 |        "  </tbody>\n",
 376 |        "</table>\n",
 377 |        "</div>"
 378 |       ],
 379 |       "text/plain": [
 380 |        "   key1  key2_x  key3_x      key4 key2_y  key3_y\n",
 381 |        "0     1     7.0    13.0      19.0      7    13.0\n",
 382 |        "1     2     8.0    14.0      20.0      8    14.0\n",
 383 |        "2     3     9.0    15.0      21.0  kumar    15.0\n",
 384 |        "3     4    10.0    16.0      22.0    NaN     NaN\n",
 385 |        "4     5    11.0    17.0      23.0    NaN     NaN\n",
 386 |        "5  sudh    12.0    18.0      24.0     12    18.0\n",
 387 |        "6     4     NaN     NaN   ineuron     10    16.0\n",
 388 |        "7     5     NaN     NaN  pwskills     11    17.0"
 389 |       ]
 390 |      },
 391 |      "execution_count": 9,
 392 |      "metadata": {},
 393 |      "output_type": "execute_result"
 394 |     }
 395 |    ],
 396 |    "source": [
 397 |     "pd.merge(df1,df2,how= 'outer',on= ['key4','key1'])"
 398 |    ]
 399 |   },
 400 |   {
 401 |    "cell_type": "code",
 402 |    "execution_count": 10,
 403 |    "id": "1a22191e-8b0c-40f7-97c7-48cefb5d7f60",
 404 |    "metadata": {},
 405 |    "outputs": [
 406 |     {
 407 |      "data": {
 408 |       "text/html": [
 409 |        "<div>\n",
 410 |        "<style scoped>\n",
 411 |        "    .dataframe tbody tr th:only-of-type {\n",
 412 |        "        vertical-align: middle;\n",
 413 |        "    }\n",
 414 |        "\n",
 415 |        "    .dataframe tbody tr th {\n",
 416 |        "        vertical-align: top;\n",
 417 |        "    }\n",
 418 |        "\n",
 419 |        "    .dataframe thead th {\n",
 420 |        "        text-align: right;\n",
 421 |        "    }\n",
 422 |        "</style>\n",
 423 |        "<table border=\"1\" class=\"dataframe\">\n",
 424 |        "  <thead>\n",
 425 |        "    <tr style=\"text-align: right;\">\n",
 426 |        "      <th></th>\n",
 427 |        "      <th>key1_x</th>\n",
 428 |        "      <th>key2_x</th>\n",
 429 |        "      <th>key3_x</th>\n",
 430 |        "      <th>key4</th>\n",
 431 |        "      <th>key1_y</th>\n",
 432 |        "      <th>key2_y</th>\n",
 433 |        "      <th>key3_y</th>\n",
 434 |        "    </tr>\n",
 435 |        "  </thead>\n",
 436 |        "  <tbody>\n",
 437 |        "    <tr>\n",
 438 |        "      <th>0</th>\n",
 439 |        "      <td>1</td>\n",
 440 |        "      <td>7</td>\n",
 441 |        "      <td>13</td>\n",
 442 |        "      <td>19</td>\n",
 443 |        "      <td>1</td>\n",
 444 |        "      <td>7</td>\n",
 445 |        "      <td>13.0</td>\n",
 446 |        "    </tr>\n",
 447 |        "    <tr>\n",
 448 |        "      <th>1</th>\n",
 449 |        "      <td>2</td>\n",
 450 |        "      <td>8</td>\n",
 451 |        "      <td>14</td>\n",
 452 |        "      <td>20</td>\n",
 453 |        "      <td>2</td>\n",
 454 |        "      <td>8</td>\n",
 455 |        "      <td>14.0</td>\n",
 456 |        "    </tr>\n",
 457 |        "    <tr>\n",
 458 |        "      <th>2</th>\n",
 459 |        "      <td>3</td>\n",
 460 |        "      <td>9</td>\n",
 461 |        "      <td>15</td>\n",
 462 |        "      <td>21</td>\n",
 463 |        "      <td>3</td>\n",
 464 |        "      <td>kumar</td>\n",
 465 |        "      <td>15.0</td>\n",
 466 |        "    </tr>\n",
 467 |        "    <tr>\n",
 468 |        "      <th>3</th>\n",
 469 |        "      <td>4</td>\n",
 470 |        "      <td>10</td>\n",
 471 |        "      <td>16</td>\n",
 472 |        "      <td>22</td>\n",
 473 |        "      <td>NaN</td>\n",
 474 |        "      <td>NaN</td>\n",
 475 |        "      <td>NaN</td>\n",
 476 |        "    </tr>\n",
 477 |        "    <tr>\n",
 478 |        "      <th>4</th>\n",
 479 |        "      <td>5</td>\n",
 480 |        "      <td>11</td>\n",
 481 |        "      <td>17</td>\n",
 482 |        "      <td>23</td>\n",
 483 |        "      <td>NaN</td>\n",
 484 |        "      <td>NaN</td>\n",
 485 |        "      <td>NaN</td>\n",
 486 |        "    </tr>\n",
 487 |        "    <tr>\n",
 488 |        "      <th>5</th>\n",
 489 |        "      <td>sudh</td>\n",
 490 |        "      <td>12</td>\n",
 491 |        "      <td>18</td>\n",
 492 |        "      <td>24</td>\n",
 493 |        "      <td>sudh</td>\n",
 494 |        "      <td>12</td>\n",
 495 |        "      <td>18.0</td>\n",
 496 |        "    </tr>\n",
 497 |        "  </tbody>\n",
 498 |        "</table>\n",
 499 |        "</div>"
 500 |       ],
 501 |       "text/plain": [
 502 |        "  key1_x  key2_x  key3_x key4 key1_y key2_y  key3_y\n",
 503 |        "0      1       7      13   19      1      7    13.0\n",
 504 |        "1      2       8      14   20      2      8    14.0\n",
 505 |        "2      3       9      15   21      3  kumar    15.0\n",
 506 |        "3      4      10      16   22    NaN    NaN     NaN\n",
 507 |        "4      5      11      17   23    NaN    NaN     NaN\n",
 508 |        "5   sudh      12      18   24   sudh     12    18.0"
 509 |       ]
 510 |      },
 511 |      "execution_count": 10,
 512 |      "metadata": {},
 513 |      "output_type": "execute_result"
 514 |     }
 515 |    ],
 516 |    "source": [
 517 |     "pd.merge(df1,df2,how= 'left',on= 'key4')"
 518 |    ]
 519 |   },
 520 |   {
 521 |    "cell_type": "code",
 522 |    "execution_count": 11,
 523 |    "id": "f588bc63-cf3d-4b9c-9a85-723a9ae9662d",
 524 |    "metadata": {},
 525 |    "outputs": [
 526 |     {
 527 |      "data": {
 528 |       "text/html": [
 529 |        "<div>\n",
 530 |        "<style scoped>\n",
 531 |        "    .dataframe tbody tr th:only-of-type {\n",
 532 |        "        vertical-align: middle;\n",
 533 |        "    }\n",
 534 |        "\n",
 535 |        "    .dataframe tbody tr th {\n",
 536 |        "        vertical-align: top;\n",
 537 |        "    }\n",
 538 |        "\n",
 539 |        "    .dataframe thead th {\n",
 540 |        "        text-align: right;\n",
 541 |        "    }\n",
 542 |        "</style>\n",
 543 |        "<table border=\"1\" class=\"dataframe\">\n",
 544 |        "  <thead>\n",
 545 |        "    <tr style=\"text-align: right;\">\n",
 546 |        "      <th></th>\n",
 547 |        "      <th>key1_x</th>\n",
 548 |        "      <th>key2_x</th>\n",
 549 |        "      <th>key3_x</th>\n",
 550 |        "      <th>key4</th>\n",
 551 |        "      <th>key1_y</th>\n",
 552 |        "      <th>key2_y</th>\n",
 553 |        "      <th>key3_y</th>\n",
 554 |        "    </tr>\n",
 555 |        "  </thead>\n",
 556 |        "  <tbody>\n",
 557 |        "    <tr>\n",
 558 |        "      <th>0</th>\n",
 559 |        "      <td>1</td>\n",
 560 |        "      <td>7</td>\n",
 561 |        "      <td>13</td>\n",
 562 |        "      <td>19</td>\n",
 563 |        "      <td>1</td>\n",
 564 |        "      <td>7</td>\n",
 565 |        "      <td>13</td>\n",
 566 |        "    </tr>\n",
 567 |        "    <tr>\n",
 568 |        "      <th>1</th>\n",
 569 |        "      <td>2</td>\n",
 570 |        "      <td>8</td>\n",
 571 |        "      <td>14</td>\n",
 572 |        "      <td>20</td>\n",
 573 |        "      <td>2</td>\n",
 574 |        "      <td>8</td>\n",
 575 |        "      <td>14</td>\n",
 576 |        "    </tr>\n",
 577 |        "    <tr>\n",
 578 |        "      <th>2</th>\n",
 579 |        "      <td>3</td>\n",
 580 |        "      <td>9</td>\n",
 581 |        "      <td>15</td>\n",
 582 |        "      <td>21</td>\n",
 583 |        "      <td>3</td>\n",
 584 |        "      <td>kumar</td>\n",
 585 |        "      <td>15</td>\n",
 586 |        "    </tr>\n",
 587 |        "    <tr>\n",
 588 |        "      <th>3</th>\n",
 589 |        "      <td>sudh</td>\n",
 590 |        "      <td>12</td>\n",
 591 |        "      <td>18</td>\n",
 592 |        "      <td>24</td>\n",
 593 |        "      <td>sudh</td>\n",
 594 |        "      <td>12</td>\n",
 595 |        "      <td>18</td>\n",
 596 |        "    </tr>\n",
 597 |        "  </tbody>\n",
 598 |        "</table>\n",
 599 |        "</div>"
 600 |       ],
 601 |       "text/plain": [
 602 |        "  key1_x  key2_x  key3_x key4 key1_y key2_y  key3_y\n",
 603 |        "0      1       7      13   19      1      7      13\n",
 604 |        "1      2       8      14   20      2      8      14\n",
 605 |        "2      3       9      15   21      3  kumar      15\n",
 606 |        "3   sudh      12      18   24   sudh     12      18"
 607 |       ]
 608 |      },
 609 |      "execution_count": 11,
 610 |      "metadata": {},
 611 |      "output_type": "execute_result"
 612 |     }
 613 |    ],
 614 |    "source": [
 615 |     "pd.merge(df1,df2,how= 'inner',on= 'key4')"
 616 |    ]
 617 |   },
 618 |   {
 619 |    "cell_type": "code",
 620 |    "execution_count": 12,
 621 |    "id": "766ab323-a189-4641-a961-514f317cc568",
 622 |    "metadata": {},
 623 |    "outputs": [
 624 |     {
 625 |      "data": {
 626 |       "text/html": [
 627 |        "<div>\n",
 628 |        "<style scoped>\n",
 629 |        "    .dataframe tbody tr th:only-of-type {\n",
 630 |        "        vertical-align: middle;\n",
 631 |        "    }\n",
 632 |        "\n",
 633 |        "    .dataframe tbody tr th {\n",
 634 |        "        vertical-align: top;\n",
 635 |        "    }\n",
 636 |        "\n",
 637 |        "    .dataframe thead th {\n",
 638 |        "        text-align: right;\n",
 639 |        "    }\n",
 640 |        "</style>\n",
 641 |        "<table border=\"1\" class=\"dataframe\">\n",
 642 |        "  <thead>\n",
 643 |        "    <tr style=\"text-align: right;\">\n",
 644 |        "      <th></th>\n",
 645 |        "      <th>key1</th>\n",
 646 |        "      <th>key2_x</th>\n",
 647 |        "      <th>key3_x</th>\n",
 648 |        "      <th>key4_x</th>\n",
 649 |        "      <th>key2_y</th>\n",
 650 |        "      <th>key3_y</th>\n",
 651 |        "      <th>key4_y</th>\n",
 652 |        "    </tr>\n",
 653 |        "  </thead>\n",
 654 |        "  <tbody>\n",
 655 |        "    <tr>\n",
 656 |        "      <th>0</th>\n",
 657 |        "      <td>1</td>\n",
 658 |        "      <td>7</td>\n",
 659 |        "      <td>13</td>\n",
 660 |        "      <td>19</td>\n",
 661 |        "      <td>7</td>\n",
 662 |        "      <td>13</td>\n",
 663 |        "      <td>19</td>\n",
 664 |        "    </tr>\n",
 665 |        "    <tr>\n",
 666 |        "      <th>1</th>\n",
 667 |        "      <td>2</td>\n",
 668 |        "      <td>8</td>\n",
 669 |        "      <td>14</td>\n",
 670 |        "      <td>20</td>\n",
 671 |        "      <td>8</td>\n",
 672 |        "      <td>14</td>\n",
 673 |        "      <td>20</td>\n",
 674 |        "    </tr>\n",
 675 |        "    <tr>\n",
 676 |        "      <th>2</th>\n",
 677 |        "      <td>3</td>\n",
 678 |        "      <td>9</td>\n",
 679 |        "      <td>15</td>\n",
 680 |        "      <td>21</td>\n",
 681 |        "      <td>kumar</td>\n",
 682 |        "      <td>15</td>\n",
 683 |        "      <td>21</td>\n",
 684 |        "    </tr>\n",
 685 |        "    <tr>\n",
 686 |        "      <th>3</th>\n",
 687 |        "      <td>4</td>\n",
 688 |        "      <td>10</td>\n",
 689 |        "      <td>16</td>\n",
 690 |        "      <td>22</td>\n",
 691 |        "      <td>10</td>\n",
 692 |        "      <td>16</td>\n",
 693 |        "      <td>ineuron</td>\n",
 694 |        "    </tr>\n",
 695 |        "    <tr>\n",
 696 |        "      <th>4</th>\n",
 697 |        "      <td>5</td>\n",
 698 |        "      <td>11</td>\n",
 699 |        "      <td>17</td>\n",
 700 |        "      <td>23</td>\n",
 701 |        "      <td>11</td>\n",
 702 |        "      <td>17</td>\n",
 703 |        "      <td>pwskills</td>\n",
 704 |        "    </tr>\n",
 705 |        "    <tr>\n",
 706 |        "      <th>5</th>\n",
 707 |        "      <td>sudh</td>\n",
 708 |        "      <td>12</td>\n",
 709 |        "      <td>18</td>\n",
 710 |        "      <td>24</td>\n",
 711 |        "      <td>12</td>\n",
 712 |        "      <td>18</td>\n",
 713 |        "      <td>24</td>\n",
 714 |        "    </tr>\n",
 715 |        "  </tbody>\n",
 716 |        "</table>\n",
 717 |        "</div>"
 718 |       ],
 719 |       "text/plain": [
 720 |        "   key1  key2_x  key3_x  key4_x key2_y  key3_y    key4_y\n",
 721 |        "0     1       7      13      19      7      13        19\n",
 722 |        "1     2       8      14      20      8      14        20\n",
 723 |        "2     3       9      15      21  kumar      15        21\n",
 724 |        "3     4      10      16      22     10      16   ineuron\n",
 725 |        "4     5      11      17      23     11      17  pwskills\n",
 726 |        "5  sudh      12      18      24     12      18        24"
 727 |       ]
 728 |      },
 729 |      "execution_count": 12,
 730 |      "metadata": {},
 731 |      "output_type": "execute_result"
 732 |     }
 733 |    ],
 734 |    "source": [
 735 |     "pd.merge(df1,df2,how= 'inner',on= 'key1')"
 736 |    ]
 737 |   },
 738 |   {
 739 |    "cell_type": "code",
 740 |    "execution_count": 13,
 741 |    "id": "7c088acf-ff3b-45ee-8ad9-1d4bde39bb8e",
 742 |    "metadata": {},
 743 |    "outputs": [
 744 |     {
 745 |      "data": {
 746 |       "text/html": [
 747 |        "<div>\n",
 748 |        "<style scoped>\n",
 749 |        "    .dataframe tbody tr th:only-of-type {\n",
 750 |        "        vertical-align: middle;\n",
 751 |        "    }\n",
 752 |        "\n",
 753 |        "    .dataframe tbody tr th {\n",
 754 |        "        vertical-align: top;\n",
 755 |        "    }\n",
 756 |        "\n",
 757 |        "    .dataframe thead th {\n",
 758 |        "        text-align: right;\n",
 759 |        "    }\n",
 760 |        "</style>\n",
 761 |        "<table border=\"1\" class=\"dataframe\">\n",
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 767 |        "      <th>key3</th>\n",
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 777 |        "      <td>19</td>\n",
 778 |        "    </tr>\n",
 779 |        "    <tr>\n",
 780 |        "      <th>1</th>\n",
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 785 |        "    </tr>\n",
 786 |        "    <tr>\n",
 787 |        "      <th>2</th>\n",
 788 |        "      <td>sudh</td>\n",
 789 |        "      <td>12</td>\n",
 790 |        "      <td>18</td>\n",
 791 |        "      <td>24</td>\n",
 792 |        "    </tr>\n",
 793 |        "  </tbody>\n",
 794 |        "</table>\n",
 795 |        "</div>"
 796 |       ],
 797 |       "text/plain": [
 798 |        "   key1 key2  key3 key4\n",
 799 |        "0     1    7    13   19\n",
 800 |        "1     2    8    14   20\n",
 801 |        "2  sudh   12    18   24"
 802 |       ]
 803 |      },
 804 |      "execution_count": 13,
 805 |      "metadata": {},
 806 |      "output_type": "execute_result"
 807 |     }
 808 |    ],
 809 |    "source": [
 810 |     "pd.merge(df1,df2)"
 811 |    ]
 812 |   },
 813 |   {
 814 |    "cell_type": "code",
 815 |    "execution_count": 14,
 816 |    "id": "bad995e3-4559-48a0-a173-eac5322e071e",
 817 |    "metadata": {},
 818 |    "outputs": [],
 819 |    "source": [
 820 |     "d11 = {'a':[1,2,3,4,5,\"sudh\"],\n",
 821 |     "      'b' : [7,8,9,10,11,12],\n",
 822 |     "      'c':[13,14,15,16,17,18],\n",
 823 |     "      'd':[19,20,21,22,23,24]\n",
 824 |     "}"
 825 |    ]
 826 |   },
 827 |   {
 828 |    "cell_type": "code",
 829 |    "execution_count": 15,
 830 |    "id": "2b066ac8-f853-454f-b557-bd7f1ab9734e",
 831 |    "metadata": {},
 832 |    "outputs": [],
 833 |    "source": [
 834 |     "d12 = {'key1':[1,2,3,4,5,\"sudh\"],\n",
 835 |     "      'key2' : [7,8,\"kumar\",10,11,12],\n",
 836 |     "      'key3':[13,14,15,16,17,18],\n",
 837 |     "      'key4':[19,20,21,\"ineuron\",\"pwskills\",24]\n",
 838 |     "}"
 839 |    ]
 840 |   },
 841 |   {
 842 |    "cell_type": "code",
 843 |    "execution_count": 16,
 844 |    "id": "81b144a3-8f41-469b-94a6-144a117a42d6",
 845 |    "metadata": {},
 846 |    "outputs": [],
 847 |    "source": [
 848 |     "df11 = pd.DataFrame(d11)"
 849 |    ]
 850 |   },
 851 |   {
 852 |    "cell_type": "code",
 853 |    "execution_count": 17,
 854 |    "id": "9379405d-41cb-4aae-a415-f3c1aab7d4b4",
 855 |    "metadata": {},
 856 |    "outputs": [
 857 |     {
 858 |      "data": {
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 864 |        "    }\n",
 865 |        "\n",
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 900 |        "      <th>2</th>\n",
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 911 |        "      <td>22</td>\n",
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 921 |        "      <th>5</th>\n",
 922 |        "      <td>sudh</td>\n",
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 924 |        "      <td>18</td>\n",
 925 |        "      <td>24</td>\n",
 926 |        "    </tr>\n",
 927 |        "  </tbody>\n",
 928 |        "</table>\n",
 929 |        "</div>"
 930 |       ],
 931 |       "text/plain": [
 932 |        "      a   b   c   d\n",
 933 |        "0     1   7  13  19\n",
 934 |        "1     2   8  14  20\n",
 935 |        "2     3   9  15  21\n",
 936 |        "3     4  10  16  22\n",
 937 |        "4     5  11  17  23\n",
 938 |        "5  sudh  12  18  24"
 939 |       ]
 940 |      },
 941 |      "execution_count": 17,
 942 |      "metadata": {},
 943 |      "output_type": "execute_result"
 944 |     }
 945 |    ],
 946 |    "source": [
 947 |     "df11"
 948 |    ]
 949 |   },
 950 |   {
 951 |    "cell_type": "code",
 952 |    "execution_count": 18,
 953 |    "id": "d7538e48-99f0-4d71-9969-51446ca4df48",
 954 |    "metadata": {},
 955 |    "outputs": [],
 956 |    "source": [
 957 |     "df12 = pd.DataFrame(d12)"
 958 |    ]
 959 |   },
 960 |   {
 961 |    "cell_type": "code",
 962 |    "execution_count": 19,
 963 |    "id": "bb578813-d943-4a8d-a8a1-4f529513f920",
 964 |    "metadata": {},
 965 |    "outputs": [
 966 |     {
 967 |      "data": {
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 978 |        "\n",
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 982 |        "</style>\n",
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1000 |        "    </tr>\n",
1001 |        "    <tr>\n",
1002 |        "      <th>1</th>\n",
1003 |        "      <td>2</td>\n",
1004 |        "      <td>8</td>\n",
1005 |        "      <td>14</td>\n",
1006 |        "      <td>20</td>\n",
1007 |        "    </tr>\n",
1008 |        "    <tr>\n",
1009 |        "      <th>2</th>\n",
1010 |        "      <td>3</td>\n",
1011 |        "      <td>kumar</td>\n",
1012 |        "      <td>15</td>\n",
1013 |        "      <td>21</td>\n",
1014 |        "    </tr>\n",
1015 |        "    <tr>\n",
1016 |        "      <th>3</th>\n",
1017 |        "      <td>4</td>\n",
1018 |        "      <td>10</td>\n",
1019 |        "      <td>16</td>\n",
1020 |        "      <td>ineuron</td>\n",
1021 |        "    </tr>\n",
1022 |        "    <tr>\n",
1023 |        "      <th>4</th>\n",
1024 |        "      <td>5</td>\n",
1025 |        "      <td>11</td>\n",
1026 |        "      <td>17</td>\n",
1027 |        "      <td>pwskills</td>\n",
1028 |        "    </tr>\n",
1029 |        "    <tr>\n",
1030 |        "      <th>5</th>\n",
1031 |        "      <td>sudh</td>\n",
1032 |        "      <td>12</td>\n",
1033 |        "      <td>18</td>\n",
1034 |        "      <td>24</td>\n",
1035 |        "    </tr>\n",
1036 |        "  </tbody>\n",
1037 |        "</table>\n",
1038 |        "</div>"
1039 |       ],
1040 |       "text/plain": [
1041 |        "   key1   key2  key3      key4\n",
1042 |        "0     1      7    13        19\n",
1043 |        "1     2      8    14        20\n",
1044 |        "2     3  kumar    15        21\n",
1045 |        "3     4     10    16   ineuron\n",
1046 |        "4     5     11    17  pwskills\n",
1047 |        "5  sudh     12    18        24"
1048 |       ]
1049 |      },
1050 |      "execution_count": 19,
1051 |      "metadata": {},
1052 |      "output_type": "execute_result"
1053 |     }
1054 |    ],
1055 |    "source": [
1056 |     "df12"
1057 |    ]
1058 |   },
1059 |   {
1060 |    "cell_type": "code",
1061 |    "execution_count": 20,
1062 |    "id": "b19a58c6-ccb4-4cdd-8f3f-f2fcd9131408",
1063 |    "metadata": {},
1064 |    "outputs": [
1065 |     {
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1078 |        "    .dataframe thead th {\n",
1079 |        "        text-align: right;\n",
1080 |        "    }\n",
1081 |        "</style>\n",
1082 |        "<table border=\"1\" class=\"dataframe\">\n",
1083 |        "  <thead>\n",
1084 |        "    <tr style=\"text-align: right;\">\n",
1085 |        "      <th></th>\n",
1086 |        "      <th>a</th>\n",
1087 |        "      <th>b</th>\n",
1088 |        "      <th>c</th>\n",
1089 |        "      <th>d</th>\n",
1090 |        "      <th>key1</th>\n",
1091 |        "      <th>key2</th>\n",
1092 |        "      <th>key3</th>\n",
1093 |        "      <th>key4</th>\n",
1094 |        "    </tr>\n",
1095 |        "  </thead>\n",
1096 |        "  <tbody>\n",
1097 |        "    <tr>\n",
1098 |        "      <th>0</th>\n",
1099 |        "      <td>1</td>\n",
1100 |        "      <td>7</td>\n",
1101 |        "      <td>13</td>\n",
1102 |        "      <td>19</td>\n",
1103 |        "      <td>1</td>\n",
1104 |        "      <td>7</td>\n",
1105 |        "      <td>13</td>\n",
1106 |        "      <td>19</td>\n",
1107 |        "    </tr>\n",
1108 |        "    <tr>\n",
1109 |        "      <th>1</th>\n",
1110 |        "      <td>2</td>\n",
1111 |        "      <td>8</td>\n",
1112 |        "      <td>14</td>\n",
1113 |        "      <td>20</td>\n",
1114 |        "      <td>2</td>\n",
1115 |        "      <td>8</td>\n",
1116 |        "      <td>14</td>\n",
1117 |        "      <td>20</td>\n",
1118 |        "    </tr>\n",
1119 |        "    <tr>\n",
1120 |        "      <th>2</th>\n",
1121 |        "      <td>3</td>\n",
1122 |        "      <td>9</td>\n",
1123 |        "      <td>15</td>\n",
1124 |        "      <td>21</td>\n",
1125 |        "      <td>3</td>\n",
1126 |        "      <td>kumar</td>\n",
1127 |        "      <td>15</td>\n",
1128 |        "      <td>21</td>\n",
1129 |        "    </tr>\n",
1130 |        "    <tr>\n",
1131 |        "      <th>3</th>\n",
1132 |        "      <td>4</td>\n",
1133 |        "      <td>10</td>\n",
1134 |        "      <td>16</td>\n",
1135 |        "      <td>22</td>\n",
1136 |        "      <td>4</td>\n",
1137 |        "      <td>10</td>\n",
1138 |        "      <td>16</td>\n",
1139 |        "      <td>ineuron</td>\n",
1140 |        "    </tr>\n",
1141 |        "    <tr>\n",
1142 |        "      <th>4</th>\n",
1143 |        "      <td>5</td>\n",
1144 |        "      <td>11</td>\n",
1145 |        "      <td>17</td>\n",
1146 |        "      <td>23</td>\n",
1147 |        "      <td>5</td>\n",
1148 |        "      <td>11</td>\n",
1149 |        "      <td>17</td>\n",
1150 |        "      <td>pwskills</td>\n",
1151 |        "    </tr>\n",
1152 |        "    <tr>\n",
1153 |        "      <th>5</th>\n",
1154 |        "      <td>sudh</td>\n",
1155 |        "      <td>12</td>\n",
1156 |        "      <td>18</td>\n",
1157 |        "      <td>24</td>\n",
1158 |        "      <td>sudh</td>\n",
1159 |        "      <td>12</td>\n",
1160 |        "      <td>18</td>\n",
1161 |        "      <td>24</td>\n",
1162 |        "    </tr>\n",
1163 |        "  </tbody>\n",
1164 |        "</table>\n",
1165 |        "</div>"
1166 |       ],
1167 |       "text/plain": [
1168 |        "      a   b   c   d  key1   key2  key3      key4\n",
1169 |        "0     1   7  13  19     1      7    13        19\n",
1170 |        "1     2   8  14  20     2      8    14        20\n",
1171 |        "2     3   9  15  21     3  kumar    15        21\n",
1172 |        "3     4  10  16  22     4     10    16   ineuron\n",
1173 |        "4     5  11  17  23     5     11    17  pwskills\n",
1174 |        "5  sudh  12  18  24  sudh     12    18        24"
1175 |       ]
1176 |      },
1177 |      "execution_count": 20,
1178 |      "metadata": {},
1179 |      "output_type": "execute_result"
1180 |     }
1181 |    ],
1182 |    "source": [
1183 |     "pd.merge(df11, df12 , how = 'left' , left_on = 'a' , right_on='key1')"
1184 |    ]
1185 |   },
1186 |   {
1187 |    "cell_type": "code",
1188 |    "execution_count": 21,
1189 |    "id": "b7749074-e054-450b-ae44-f37f54f4a7a0",
1190 |    "metadata": {},
1191 |    "outputs": [
1192 |     {
1193 |      "data": {
1194 |       "text/html": [
1195 |        "<div>\n",
1196 |        "<style scoped>\n",
1197 |        "    .dataframe tbody tr th:only-of-type {\n",
1198 |        "        vertical-align: middle;\n",
1199 |        "    }\n",
1200 |        "\n",
1201 |        "    .dataframe tbody tr th {\n",
1202 |        "        vertical-align: top;\n",
1203 |        "    }\n",
1204 |        "\n",
1205 |        "    .dataframe thead th {\n",
1206 |        "        text-align: right;\n",
1207 |        "    }\n",
1208 |        "</style>\n",
1209 |        "<table border=\"1\" class=\"dataframe\">\n",
1210 |        "  <thead>\n",
1211 |        "    <tr style=\"text-align: right;\">\n",
1212 |        "      <th></th>\n",
1213 |        "      <th>key1</th>\n",
1214 |        "      <th>key2</th>\n",
1215 |        "      <th>key3</th>\n",
1216 |        "      <th>key4</th>\n",
1217 |        "    </tr>\n",
1218 |        "  </thead>\n",
1219 |        "  <tbody>\n",
1220 |        "    <tr>\n",
1221 |        "      <th>0</th>\n",
1222 |        "      <td>1</td>\n",
1223 |        "      <td>7</td>\n",
1224 |        "      <td>13</td>\n",
1225 |        "      <td>19</td>\n",
1226 |        "    </tr>\n",
1227 |        "    <tr>\n",
1228 |        "      <th>1</th>\n",
1229 |        "      <td>2</td>\n",
1230 |        "      <td>8</td>\n",
1231 |        "      <td>14</td>\n",
1232 |        "      <td>20</td>\n",
1233 |        "    </tr>\n",
1234 |        "    <tr>\n",
1235 |        "      <th>2</th>\n",
1236 |        "      <td>3</td>\n",
1237 |        "      <td>9</td>\n",
1238 |        "      <td>15</td>\n",
1239 |        "      <td>21</td>\n",
1240 |        "    </tr>\n",
1241 |        "    <tr>\n",
1242 |        "      <th>3</th>\n",
1243 |        "      <td>4</td>\n",
1244 |        "      <td>10</td>\n",
1245 |        "      <td>16</td>\n",
1246 |        "      <td>22</td>\n",
1247 |        "    </tr>\n",
1248 |        "    <tr>\n",
1249 |        "      <th>4</th>\n",
1250 |        "      <td>5</td>\n",
1251 |        "      <td>11</td>\n",
1252 |        "      <td>17</td>\n",
1253 |        "      <td>23</td>\n",
1254 |        "    </tr>\n",
1255 |        "    <tr>\n",
1256 |        "      <th>5</th>\n",
1257 |        "      <td>sudh</td>\n",
1258 |        "      <td>12</td>\n",
1259 |        "      <td>18</td>\n",
1260 |        "      <td>24</td>\n",
1261 |        "    </tr>\n",
1262 |        "  </tbody>\n",
1263 |        "</table>\n",
1264 |        "</div>"
1265 |       ],
1266 |       "text/plain": [
1267 |        "   key1  key2  key3  key4\n",
1268 |        "0     1     7    13    19\n",
1269 |        "1     2     8    14    20\n",
1270 |        "2     3     9    15    21\n",
1271 |        "3     4    10    16    22\n",
1272 |        "4     5    11    17    23\n",
1273 |        "5  sudh    12    18    24"
1274 |       ]
1275 |      },
1276 |      "execution_count": 21,
1277 |      "metadata": {},
1278 |      "output_type": "execute_result"
1279 |     }
1280 |    ],
1281 |    "source": [
1282 |     "df1"
1283 |    ]
1284 |   },
1285 |   {
1286 |    "cell_type": "code",
1287 |    "execution_count": 22,
1288 |    "id": "4233fb06-db78-4dc7-8899-a6d2fa19e0ec",
1289 |    "metadata": {},
1290 |    "outputs": [
1291 |     {
1292 |      "data": {
1293 |       "text/html": [
1294 |        "<div>\n",
1295 |        "<style scoped>\n",
1296 |        "    .dataframe tbody tr th:only-of-type {\n",
1297 |        "        vertical-align: middle;\n",
1298 |        "    }\n",
1299 |        "\n",
1300 |        "    .dataframe tbody tr th {\n",
1301 |        "        vertical-align: top;\n",
1302 |        "    }\n",
1303 |        "\n",
1304 |        "    .dataframe thead th {\n",
1305 |        "        text-align: right;\n",
1306 |        "    }\n",
1307 |        "</style>\n",
1308 |        "<table border=\"1\" class=\"dataframe\">\n",
1309 |        "  <thead>\n",
1310 |        "    <tr style=\"text-align: right;\">\n",
1311 |        "      <th></th>\n",
1312 |        "      <th>key1</th>\n",
1313 |        "      <th>key2</th>\n",
1314 |        "      <th>key3</th>\n",
1315 |        "      <th>key4</th>\n",
1316 |        "    </tr>\n",
1317 |        "  </thead>\n",
1318 |        "  <tbody>\n",
1319 |        "    <tr>\n",
1320 |        "      <th>0</th>\n",
1321 |        "      <td>1</td>\n",
1322 |        "      <td>7</td>\n",
1323 |        "      <td>13</td>\n",
1324 |        "      <td>19</td>\n",
1325 |        "    </tr>\n",
1326 |        "    <tr>\n",
1327 |        "      <th>1</th>\n",
1328 |        "      <td>2</td>\n",
1329 |        "      <td>8</td>\n",
1330 |        "      <td>14</td>\n",
1331 |        "      <td>20</td>\n",
1332 |        "    </tr>\n",
1333 |        "    <tr>\n",
1334 |        "      <th>2</th>\n",
1335 |        "      <td>3</td>\n",
1336 |        "      <td>kumar</td>\n",
1337 |        "      <td>15</td>\n",
1338 |        "      <td>21</td>\n",
1339 |        "    </tr>\n",
1340 |        "    <tr>\n",
1341 |        "      <th>3</th>\n",
1342 |        "      <td>4</td>\n",
1343 |        "      <td>10</td>\n",
1344 |        "      <td>16</td>\n",
1345 |        "      <td>ineuron</td>\n",
1346 |        "    </tr>\n",
1347 |        "    <tr>\n",
1348 |        "      <th>4</th>\n",
1349 |        "      <td>5</td>\n",
1350 |        "      <td>11</td>\n",
1351 |        "      <td>17</td>\n",
1352 |        "      <td>pwskills</td>\n",
1353 |        "    </tr>\n",
1354 |        "    <tr>\n",
1355 |        "      <th>5</th>\n",
1356 |        "      <td>sudh</td>\n",
1357 |        "      <td>12</td>\n",
1358 |        "      <td>18</td>\n",
1359 |        "      <td>24</td>\n",
1360 |        "    </tr>\n",
1361 |        "  </tbody>\n",
1362 |        "</table>\n",
1363 |        "</div>"
1364 |       ],
1365 |       "text/plain": [
1366 |        "   key1   key2  key3      key4\n",
1367 |        "0     1      7    13        19\n",
1368 |        "1     2      8    14        20\n",
1369 |        "2     3  kumar    15        21\n",
1370 |        "3     4     10    16   ineuron\n",
1371 |        "4     5     11    17  pwskills\n",
1372 |        "5  sudh     12    18        24"
1373 |       ]
1374 |      },
1375 |      "execution_count": 22,
1376 |      "metadata": {},
1377 |      "output_type": "execute_result"
1378 |     }
1379 |    ],
1380 |    "source": [
1381 |     "df2"
1382 |    ]
1383 |   },
1384 |   {
1385 |    "cell_type": "code",
1386 |    "execution_count": 35,
1387 |    "id": "095467bf-0bd4-4a2b-a170-6f8052d05ebb",
1388 |    "metadata": {},
1389 |    "outputs": [],
1390 |    "source": [
1391 |     "d10 = {'key11':[1,2,3,4,5,\"sudh\"],\n",
1392 |     "      'key21' : [7,8,9,10,11,12],\n",
1393 |     "      'key31':[13,14,15,16,17,18],\n",
1394 |     "      'key41':[19,20,21,22,23,24]\n",
1395 |     "}"
1396 |    ]
1397 |   },
1398 |   {
1399 |    "cell_type": "code",
1400 |    "execution_count": 36,
1401 |    "id": "e7f0f269-7009-4827-be0a-909c1dc8e8a7",
1402 |    "metadata": {},
1403 |    "outputs": [],
1404 |    "source": [
1405 |     "d20 = {'key1':[1,2,3,4,5,\"sudh\"],\n",
1406 |     "      'key2' : [7,8,\"kumar\",10,11,12],\n",
1407 |     "      'key3':[13,14,15,16,17,18],\n",
1408 |     "      'key4':[19,20,21,\"ineuron\",\"pwskills\",24]\n",
1409 |     "}"
1410 |    ]
1411 |   },
1412 |   {
1413 |    "cell_type": "code",
1414 |    "execution_count": 46,
1415 |    "id": "d175fbed-f677-4356-82bf-8e29be81ee05",
1416 |    "metadata": {},
1417 |    "outputs": [],
1418 |    "source": [
1419 |     "df10 = pd.DataFrame(d10 , index = [1,2,3,4,5,6])"
1420 |    ]
1421 |   },
1422 |   {
1423 |    "cell_type": "code",
1424 |    "execution_count": 47,
1425 |    "id": "bc675706-4ee9-486c-b92c-b362798595d2",
1426 |    "metadata": {},
1427 |    "outputs": [],
1428 |    "source": [
1429 |     "df20 = pd.DataFrame(d20, index=[1,2,3,4,5,'sudh'])"
1430 |    ]
1431 |   },
1432 |   {
1433 |    "cell_type": "code",
1434 |    "execution_count": 48,
1435 |    "id": "0992f4f1-09b2-488c-9620-7fdca3edc071",
1436 |    "metadata": {},
1437 |    "outputs": [
1438 |     {
1439 |      "data": {
1440 |       "text/html": [
1441 |        "<div>\n",
1442 |        "<style scoped>\n",
1443 |        "    .dataframe tbody tr th:only-of-type {\n",
1444 |        "        vertical-align: middle;\n",
1445 |        "    }\n",
1446 |        "\n",
1447 |        "    .dataframe tbody tr th {\n",
1448 |        "        vertical-align: top;\n",
1449 |        "    }\n",
1450 |        "\n",
1451 |        "    .dataframe thead th {\n",
1452 |        "        text-align: right;\n",
1453 |        "    }\n",
1454 |        "</style>\n",
1455 |        "<table border=\"1\" class=\"dataframe\">\n",
1456 |        "  <thead>\n",
1457 |        "    <tr style=\"text-align: right;\">\n",
1458 |        "      <th></th>\n",
1459 |        "      <th>key11</th>\n",
1460 |        "      <th>key21</th>\n",
1461 |        "      <th>key31</th>\n",
1462 |        "      <th>key41</th>\n",
1463 |        "    </tr>\n",
1464 |        "  </thead>\n",
1465 |        "  <tbody>\n",
1466 |        "    <tr>\n",
1467 |        "      <th>1</th>\n",
1468 |        "      <td>1</td>\n",
1469 |        "      <td>7</td>\n",
1470 |        "      <td>13</td>\n",
1471 |        "      <td>19</td>\n",
1472 |        "    </tr>\n",
1473 |        "    <tr>\n",
1474 |        "      <th>2</th>\n",
1475 |        "      <td>2</td>\n",
1476 |        "      <td>8</td>\n",
1477 |        "      <td>14</td>\n",
1478 |        "      <td>20</td>\n",
1479 |        "    </tr>\n",
1480 |        "    <tr>\n",
1481 |        "      <th>3</th>\n",
1482 |        "      <td>3</td>\n",
1483 |        "      <td>9</td>\n",
1484 |        "      <td>15</td>\n",
1485 |        "      <td>21</td>\n",
1486 |        "    </tr>\n",
1487 |        "    <tr>\n",
1488 |        "      <th>4</th>\n",
1489 |        "      <td>4</td>\n",
1490 |        "      <td>10</td>\n",
1491 |        "      <td>16</td>\n",
1492 |        "      <td>22</td>\n",
1493 |        "    </tr>\n",
1494 |        "    <tr>\n",
1495 |        "      <th>5</th>\n",
1496 |        "      <td>5</td>\n",
1497 |        "      <td>11</td>\n",
1498 |        "      <td>17</td>\n",
1499 |        "      <td>23</td>\n",
1500 |        "    </tr>\n",
1501 |        "    <tr>\n",
1502 |        "      <th>6</th>\n",
1503 |        "      <td>sudh</td>\n",
1504 |        "      <td>12</td>\n",
1505 |        "      <td>18</td>\n",
1506 |        "      <td>24</td>\n",
1507 |        "    </tr>\n",
1508 |        "  </tbody>\n",
1509 |        "</table>\n",
1510 |        "</div>"
1511 |       ],
1512 |       "text/plain": [
1513 |        "  key11  key21  key31  key41\n",
1514 |        "1     1      7     13     19\n",
1515 |        "2     2      8     14     20\n",
1516 |        "3     3      9     15     21\n",
1517 |        "4     4     10     16     22\n",
1518 |        "5     5     11     17     23\n",
1519 |        "6  sudh     12     18     24"
1520 |       ]
1521 |      },
1522 |      "execution_count": 48,
1523 |      "metadata": {},
1524 |      "output_type": "execute_result"
1525 |     }
1526 |    ],
1527 |    "source": [
1528 |     "df10"
1529 |    ]
1530 |   },
1531 |   {
1532 |    "cell_type": "code",
1533 |    "execution_count": 49,
1534 |    "id": "5b61d81a-cdd1-4562-ab68-62bf2b722349",
1535 |    "metadata": {},
1536 |    "outputs": [
1537 |     {
1538 |      "data": {
1539 |       "text/html": [
1540 |        "<div>\n",
1541 |        "<style scoped>\n",
1542 |        "    .dataframe tbody tr th:only-of-type {\n",
1543 |        "        vertical-align: middle;\n",
1544 |        "    }\n",
1545 |        "\n",
1546 |        "    .dataframe tbody tr th {\n",
1547 |        "        vertical-align: top;\n",
1548 |        "    }\n",
1549 |        "\n",
1550 |        "    .dataframe thead th {\n",
1551 |        "        text-align: right;\n",
1552 |        "    }\n",
1553 |        "</style>\n",
1554 |        "<table border=\"1\" class=\"dataframe\">\n",
1555 |        "  <thead>\n",
1556 |        "    <tr style=\"text-align: right;\">\n",
1557 |        "      <th></th>\n",
1558 |        "      <th>key1</th>\n",
1559 |        "      <th>key2</th>\n",
1560 |        "      <th>key3</th>\n",
1561 |        "      <th>key4</th>\n",
1562 |        "    </tr>\n",
1563 |        "  </thead>\n",
1564 |        "  <tbody>\n",
1565 |        "    <tr>\n",
1566 |        "      <th>1</th>\n",
1567 |        "      <td>1</td>\n",
1568 |        "      <td>7</td>\n",
1569 |        "      <td>13</td>\n",
1570 |        "      <td>19</td>\n",
1571 |        "    </tr>\n",
1572 |        "    <tr>\n",
1573 |        "      <th>2</th>\n",
1574 |        "      <td>2</td>\n",
1575 |        "      <td>8</td>\n",
1576 |        "      <td>14</td>\n",
1577 |        "      <td>20</td>\n",
1578 |        "    </tr>\n",
1579 |        "    <tr>\n",
1580 |        "      <th>3</th>\n",
1581 |        "      <td>3</td>\n",
1582 |        "      <td>kumar</td>\n",
1583 |        "      <td>15</td>\n",
1584 |        "      <td>21</td>\n",
1585 |        "    </tr>\n",
1586 |        "    <tr>\n",
1587 |        "      <th>4</th>\n",
1588 |        "      <td>4</td>\n",
1589 |        "      <td>10</td>\n",
1590 |        "      <td>16</td>\n",
1591 |        "      <td>ineuron</td>\n",
1592 |        "    </tr>\n",
1593 |        "    <tr>\n",
1594 |        "      <th>5</th>\n",
1595 |        "      <td>5</td>\n",
1596 |        "      <td>11</td>\n",
1597 |        "      <td>17</td>\n",
1598 |        "      <td>pwskills</td>\n",
1599 |        "    </tr>\n",
1600 |        "    <tr>\n",
1601 |        "      <th>sudh</th>\n",
1602 |        "      <td>sudh</td>\n",
1603 |        "      <td>12</td>\n",
1604 |        "      <td>18</td>\n",
1605 |        "      <td>24</td>\n",
1606 |        "    </tr>\n",
1607 |        "  </tbody>\n",
1608 |        "</table>\n",
1609 |        "</div>"
1610 |       ],
1611 |       "text/plain": [
1612 |        "      key1   key2  key3      key4\n",
1613 |        "1        1      7    13        19\n",
1614 |        "2        2      8    14        20\n",
1615 |        "3        3  kumar    15        21\n",
1616 |        "4        4     10    16   ineuron\n",
1617 |        "5        5     11    17  pwskills\n",
1618 |        "sudh  sudh     12    18        24"
1619 |       ]
1620 |      },
1621 |      "execution_count": 49,
1622 |      "metadata": {},
1623 |      "output_type": "execute_result"
1624 |     }
1625 |    ],
1626 |    "source": [
1627 |     "df20"
1628 |    ]
1629 |   },
1630 |   {
1631 |    "cell_type": "code",
1632 |    "execution_count": 50,
1633 |    "id": "9bdca038-b30a-479f-a68e-e0f0b04480f2",
1634 |    "metadata": {},
1635 |    "outputs": [
1636 |     {
1637 |      "data": {
1638 |       "text/html": [
1639 |        "<div>\n",
1640 |        "<style scoped>\n",
1641 |        "    .dataframe tbody tr th:only-of-type {\n",
1642 |        "        vertical-align: middle;\n",
1643 |        "    }\n",
1644 |        "\n",
1645 |        "    .dataframe tbody tr th {\n",
1646 |        "        vertical-align: top;\n",
1647 |        "    }\n",
1648 |        "\n",
1649 |        "    .dataframe thead th {\n",
1650 |        "        text-align: right;\n",
1651 |        "    }\n",
1652 |        "</style>\n",
1653 |        "<table border=\"1\" class=\"dataframe\">\n",
1654 |        "  <thead>\n",
1655 |        "    <tr style=\"text-align: right;\">\n",
1656 |        "      <th></th>\n",
1657 |        "      <th>key11</th>\n",
1658 |        "      <th>key21</th>\n",
1659 |        "      <th>key31</th>\n",
1660 |        "      <th>key41</th>\n",
1661 |        "      <th>key1</th>\n",
1662 |        "      <th>key2</th>\n",
1663 |        "      <th>key3</th>\n",
1664 |        "      <th>key4</th>\n",
1665 |        "    </tr>\n",
1666 |        "  </thead>\n",
1667 |        "  <tbody>\n",
1668 |        "    <tr>\n",
1669 |        "      <th>1</th>\n",
1670 |        "      <td>1</td>\n",
1671 |        "      <td>7.0</td>\n",
1672 |        "      <td>13.0</td>\n",
1673 |        "      <td>19.0</td>\n",
1674 |        "      <td>1</td>\n",
1675 |        "      <td>7</td>\n",
1676 |        "      <td>13</td>\n",
1677 |        "      <td>19</td>\n",
1678 |        "    </tr>\n",
1679 |        "    <tr>\n",
1680 |        "      <th>2</th>\n",
1681 |        "      <td>2</td>\n",
1682 |        "      <td>8.0</td>\n",
1683 |        "      <td>14.0</td>\n",
1684 |        "      <td>20.0</td>\n",
1685 |        "      <td>2</td>\n",
1686 |        "      <td>8</td>\n",
1687 |        "      <td>14</td>\n",
1688 |        "      <td>20</td>\n",
1689 |        "    </tr>\n",
1690 |        "    <tr>\n",
1691 |        "      <th>3</th>\n",
1692 |        "      <td>3</td>\n",
1693 |        "      <td>9.0</td>\n",
1694 |        "      <td>15.0</td>\n",
1695 |        "      <td>21.0</td>\n",
1696 |        "      <td>3</td>\n",
1697 |        "      <td>kumar</td>\n",
1698 |        "      <td>15</td>\n",
1699 |        "      <td>21</td>\n",
1700 |        "    </tr>\n",
1701 |        "    <tr>\n",
1702 |        "      <th>4</th>\n",
1703 |        "      <td>4</td>\n",
1704 |        "      <td>10.0</td>\n",
1705 |        "      <td>16.0</td>\n",
1706 |        "      <td>22.0</td>\n",
1707 |        "      <td>4</td>\n",
1708 |        "      <td>10</td>\n",
1709 |        "      <td>16</td>\n",
1710 |        "      <td>ineuron</td>\n",
1711 |        "    </tr>\n",
1712 |        "    <tr>\n",
1713 |        "      <th>5</th>\n",
1714 |        "      <td>5</td>\n",
1715 |        "      <td>11.0</td>\n",
1716 |        "      <td>17.0</td>\n",
1717 |        "      <td>23.0</td>\n",
1718 |        "      <td>5</td>\n",
1719 |        "      <td>11</td>\n",
1720 |        "      <td>17</td>\n",
1721 |        "      <td>pwskills</td>\n",
1722 |        "    </tr>\n",
1723 |        "    <tr>\n",
1724 |        "      <th>sudh</th>\n",
1725 |        "      <td>NaN</td>\n",
1726 |        "      <td>NaN</td>\n",
1727 |        "      <td>NaN</td>\n",
1728 |        "      <td>NaN</td>\n",
1729 |        "      <td>sudh</td>\n",
1730 |        "      <td>12</td>\n",
1731 |        "      <td>18</td>\n",
1732 |        "      <td>24</td>\n",
1733 |        "    </tr>\n",
1734 |        "  </tbody>\n",
1735 |        "</table>\n",
1736 |        "</div>"
1737 |       ],
1738 |       "text/plain": [
1739 |        "     key11  key21  key31  key41  key1   key2  key3      key4\n",
1740 |        "1        1    7.0   13.0   19.0     1      7    13        19\n",
1741 |        "2        2    8.0   14.0   20.0     2      8    14        20\n",
1742 |        "3        3    9.0   15.0   21.0     3  kumar    15        21\n",
1743 |        "4        4   10.0   16.0   22.0     4     10    16   ineuron\n",
1744 |        "5        5   11.0   17.0   23.0     5     11    17  pwskills\n",
1745 |        "sudh   NaN    NaN    NaN    NaN  sudh     12    18        24"
1746 |       ]
1747 |      },
1748 |      "execution_count": 50,
1749 |      "metadata": {},
1750 |      "output_type": "execute_result"
1751 |     }
1752 |    ],
1753 |    "source": [
1754 |     "df10.join(df20,how = 'right')"
1755 |    ]
1756 |   },
1757 |   {
1758 |    "cell_type": "code",
1759 |    "execution_count": 51,
1760 |    "id": "d95eab7a-2a8a-45f8-a355-2d8ec6f01d5d",
1761 |    "metadata": {},
1762 |    "outputs": [
1763 |     {
1764 |      "data": {
1765 |       "text/html": [
1766 |        "<div>\n",
1767 |        "<style scoped>\n",
1768 |        "    .dataframe tbody tr th:only-of-type {\n",
1769 |        "        vertical-align: middle;\n",
1770 |        "    }\n",
1771 |        "\n",
1772 |        "    .dataframe tbody tr th {\n",
1773 |        "        vertical-align: top;\n",
1774 |        "    }\n",
1775 |        "\n",
1776 |        "    .dataframe thead th {\n",
1777 |        "        text-align: right;\n",
1778 |        "    }\n",
1779 |        "</style>\n",
1780 |        "<table border=\"1\" class=\"dataframe\">\n",
1781 |        "  <thead>\n",
1782 |        "    <tr style=\"text-align: right;\">\n",
1783 |        "      <th></th>\n",
1784 |        "      <th>key11</th>\n",
1785 |        "      <th>key21</th>\n",
1786 |        "      <th>key31</th>\n",
1787 |        "      <th>key41</th>\n",
1788 |        "      <th>key1</th>\n",
1789 |        "      <th>key2</th>\n",
1790 |        "      <th>key3</th>\n",
1791 |        "      <th>key4</th>\n",
1792 |        "    </tr>\n",
1793 |        "  </thead>\n",
1794 |        "  <tbody>\n",
1795 |        "    <tr>\n",
1796 |        "      <th>1</th>\n",
1797 |        "      <td>1</td>\n",
1798 |        "      <td>7</td>\n",
1799 |        "      <td>13</td>\n",
1800 |        "      <td>19</td>\n",
1801 |        "      <td>1</td>\n",
1802 |        "      <td>7</td>\n",
1803 |        "      <td>13.0</td>\n",
1804 |        "      <td>19</td>\n",
1805 |        "    </tr>\n",
1806 |        "    <tr>\n",
1807 |        "      <th>2</th>\n",
1808 |        "      <td>2</td>\n",
1809 |        "      <td>8</td>\n",
1810 |        "      <td>14</td>\n",
1811 |        "      <td>20</td>\n",
1812 |        "      <td>2</td>\n",
1813 |        "      <td>8</td>\n",
1814 |        "      <td>14.0</td>\n",
1815 |        "      <td>20</td>\n",
1816 |        "    </tr>\n",
1817 |        "    <tr>\n",
1818 |        "      <th>3</th>\n",
1819 |        "      <td>3</td>\n",
1820 |        "      <td>9</td>\n",
1821 |        "      <td>15</td>\n",
1822 |        "      <td>21</td>\n",
1823 |        "      <td>3</td>\n",
1824 |        "      <td>kumar</td>\n",
1825 |        "      <td>15.0</td>\n",
1826 |        "      <td>21</td>\n",
1827 |        "    </tr>\n",
1828 |        "    <tr>\n",
1829 |        "      <th>4</th>\n",
1830 |        "      <td>4</td>\n",
1831 |        "      <td>10</td>\n",
1832 |        "      <td>16</td>\n",
1833 |        "      <td>22</td>\n",
1834 |        "      <td>4</td>\n",
1835 |        "      <td>10</td>\n",
1836 |        "      <td>16.0</td>\n",
1837 |        "      <td>ineuron</td>\n",
1838 |        "    </tr>\n",
1839 |        "    <tr>\n",
1840 |        "      <th>5</th>\n",
1841 |        "      <td>5</td>\n",
1842 |        "      <td>11</td>\n",
1843 |        "      <td>17</td>\n",
1844 |        "      <td>23</td>\n",
1845 |        "      <td>5</td>\n",
1846 |        "      <td>11</td>\n",
1847 |        "      <td>17.0</td>\n",
1848 |        "      <td>pwskills</td>\n",
1849 |        "    </tr>\n",
1850 |        "    <tr>\n",
1851 |        "      <th>6</th>\n",
1852 |        "      <td>sudh</td>\n",
1853 |        "      <td>12</td>\n",
1854 |        "      <td>18</td>\n",
1855 |        "      <td>24</td>\n",
1856 |        "      <td>NaN</td>\n",
1857 |        "      <td>NaN</td>\n",
1858 |        "      <td>NaN</td>\n",
1859 |        "      <td>NaN</td>\n",
1860 |        "    </tr>\n",
1861 |        "  </tbody>\n",
1862 |        "</table>\n",
1863 |        "</div>"
1864 |       ],
1865 |       "text/plain": [
1866 |        "  key11  key21  key31  key41 key1   key2  key3      key4\n",
1867 |        "1     1      7     13     19    1      7  13.0        19\n",
1868 |        "2     2      8     14     20    2      8  14.0        20\n",
1869 |        "3     3      9     15     21    3  kumar  15.0        21\n",
1870 |        "4     4     10     16     22    4     10  16.0   ineuron\n",
1871 |        "5     5     11     17     23    5     11  17.0  pwskills\n",
1872 |        "6  sudh     12     18     24  NaN    NaN   NaN       NaN"
1873 |       ]
1874 |      },
1875 |      "execution_count": 51,
1876 |      "metadata": {},
1877 |      "output_type": "execute_result"
1878 |     }
1879 |    ],
1880 |    "source": [
1881 |     "df10.join(df20)"
1882 |    ]
1883 |   },
1884 |   {
1885 |    "cell_type": "code",
1886 |    "execution_count": 52,
1887 |    "id": "203ef879-efd1-48f7-a82b-1b603f7cc43d",
1888 |    "metadata": {},
1889 |    "outputs": [
1890 |     {
1891 |      "data": {
1892 |       "text/html": [
1893 |        "<div>\n",
1894 |        "<style scoped>\n",
1895 |        "    .dataframe tbody tr th:only-of-type {\n",
1896 |        "        vertical-align: middle;\n",
1897 |        "    }\n",
1898 |        "\n",
1899 |        "    .dataframe tbody tr th {\n",
1900 |        "        vertical-align: top;\n",
1901 |        "    }\n",
1902 |        "\n",
1903 |        "    .dataframe thead th {\n",
1904 |        "        text-align: right;\n",
1905 |        "    }\n",
1906 |        "</style>\n",
1907 |        "<table border=\"1\" class=\"dataframe\">\n",
1908 |        "  <thead>\n",
1909 |        "    <tr style=\"text-align: right;\">\n",
1910 |        "      <th></th>\n",
1911 |        "      <th>key11</th>\n",
1912 |        "      <th>key21</th>\n",
1913 |        "      <th>key31</th>\n",
1914 |        "      <th>key41</th>\n",
1915 |        "      <th>key1</th>\n",
1916 |        "      <th>key2</th>\n",
1917 |        "      <th>key3</th>\n",
1918 |        "      <th>key4</th>\n",
1919 |        "    </tr>\n",
1920 |        "  </thead>\n",
1921 |        "  <tbody>\n",
1922 |        "    <tr>\n",
1923 |        "      <th>1</th>\n",
1924 |        "      <td>1</td>\n",
1925 |        "      <td>7.0</td>\n",
1926 |        "      <td>13.0</td>\n",
1927 |        "      <td>19.0</td>\n",
1928 |        "      <td>1</td>\n",
1929 |        "      <td>7</td>\n",
1930 |        "      <td>13.0</td>\n",
1931 |        "      <td>19</td>\n",
1932 |        "    </tr>\n",
1933 |        "    <tr>\n",
1934 |        "      <th>2</th>\n",
1935 |        "      <td>2</td>\n",
1936 |        "      <td>8.0</td>\n",
1937 |        "      <td>14.0</td>\n",
1938 |        "      <td>20.0</td>\n",
1939 |        "      <td>2</td>\n",
1940 |        "      <td>8</td>\n",
1941 |        "      <td>14.0</td>\n",
1942 |        "      <td>20</td>\n",
1943 |        "    </tr>\n",
1944 |        "    <tr>\n",
1945 |        "      <th>3</th>\n",
1946 |        "      <td>3</td>\n",
1947 |        "      <td>9.0</td>\n",
1948 |        "      <td>15.0</td>\n",
1949 |        "      <td>21.0</td>\n",
1950 |        "      <td>3</td>\n",
1951 |        "      <td>kumar</td>\n",
1952 |        "      <td>15.0</td>\n",
1953 |        "      <td>21</td>\n",
1954 |        "    </tr>\n",
1955 |        "    <tr>\n",
1956 |        "      <th>4</th>\n",
1957 |        "      <td>4</td>\n",
1958 |        "      <td>10.0</td>\n",
1959 |        "      <td>16.0</td>\n",
1960 |        "      <td>22.0</td>\n",
1961 |        "      <td>4</td>\n",
1962 |        "      <td>10</td>\n",
1963 |        "      <td>16.0</td>\n",
1964 |        "      <td>ineuron</td>\n",
1965 |        "    </tr>\n",
1966 |        "    <tr>\n",
1967 |        "      <th>5</th>\n",
1968 |        "      <td>5</td>\n",
1969 |        "      <td>11.0</td>\n",
1970 |        "      <td>17.0</td>\n",
1971 |        "      <td>23.0</td>\n",
1972 |        "      <td>5</td>\n",
1973 |        "      <td>11</td>\n",
1974 |        "      <td>17.0</td>\n",
1975 |        "      <td>pwskills</td>\n",
1976 |        "    </tr>\n",
1977 |        "    <tr>\n",
1978 |        "      <th>6</th>\n",
1979 |        "      <td>sudh</td>\n",
1980 |        "      <td>12.0</td>\n",
1981 |        "      <td>18.0</td>\n",
1982 |        "      <td>24.0</td>\n",
1983 |        "      <td>NaN</td>\n",
1984 |        "      <td>NaN</td>\n",
1985 |        "      <td>NaN</td>\n",
1986 |        "      <td>NaN</td>\n",
1987 |        "    </tr>\n",
1988 |        "    <tr>\n",
1989 |        "      <th>sudh</th>\n",
1990 |        "      <td>NaN</td>\n",
1991 |        "      <td>NaN</td>\n",
1992 |        "      <td>NaN</td>\n",
1993 |        "      <td>NaN</td>\n",
1994 |        "      <td>sudh</td>\n",
1995 |        "      <td>12</td>\n",
1996 |        "      <td>18.0</td>\n",
1997 |        "      <td>24</td>\n",
1998 |        "    </tr>\n",
1999 |        "  </tbody>\n",
2000 |        "</table>\n",
2001 |        "</div>"
2002 |       ],
2003 |       "text/plain": [
2004 |        "     key11  key21  key31  key41  key1   key2  key3      key4\n",
2005 |        "1        1    7.0   13.0   19.0     1      7  13.0        19\n",
2006 |        "2        2    8.0   14.0   20.0     2      8  14.0        20\n",
2007 |        "3        3    9.0   15.0   21.0     3  kumar  15.0        21\n",
2008 |        "4        4   10.0   16.0   22.0     4     10  16.0   ineuron\n",
2009 |        "5        5   11.0   17.0   23.0     5     11  17.0  pwskills\n",
2010 |        "6     sudh   12.0   18.0   24.0   NaN    NaN   NaN       NaN\n",
2011 |        "sudh   NaN    NaN    NaN    NaN  sudh     12  18.0        24"
2012 |       ]
2013 |      },
2014 |      "execution_count": 52,
2015 |      "metadata": {},
2016 |      "output_type": "execute_result"
2017 |     }
2018 |    ],
2019 |    "source": [
2020 |     "df10.join(df20 , how = 'outer')"
2021 |    ]
2022 |   },
2023 |   {
2024 |    "cell_type": "code",
2025 |    "execution_count": 53,
2026 |    "id": "f64b7105-48f5-47b2-9362-1e4b231207ed",
2027 |    "metadata": {},
2028 |    "outputs": [
2029 |     {
2030 |      "data": {
2031 |       "text/html": [
2032 |        "<div>\n",
2033 |        "<style scoped>\n",
2034 |        "    .dataframe tbody tr th:only-of-type {\n",
2035 |        "        vertical-align: middle;\n",
2036 |        "    }\n",
2037 |        "\n",
2038 |        "    .dataframe tbody tr th {\n",
2039 |        "        vertical-align: top;\n",
2040 |        "    }\n",
2041 |        "\n",
2042 |        "    .dataframe thead th {\n",
2043 |        "        text-align: right;\n",
2044 |        "    }\n",
2045 |        "</style>\n",
2046 |        "<table border=\"1\" class=\"dataframe\">\n",
2047 |        "  <thead>\n",
2048 |        "    <tr style=\"text-align: right;\">\n",
2049 |        "      <th></th>\n",
2050 |        "      <th>key11</th>\n",
2051 |        "      <th>key21</th>\n",
2052 |        "      <th>key31</th>\n",
2053 |        "      <th>key41</th>\n",
2054 |        "      <th>key1</th>\n",
2055 |        "      <th>key2</th>\n",
2056 |        "      <th>key3</th>\n",
2057 |        "      <th>key4</th>\n",
2058 |        "    </tr>\n",
2059 |        "  </thead>\n",
2060 |        "  <tbody>\n",
2061 |        "    <tr>\n",
2062 |        "      <th>1</th>\n",
2063 |        "      <td>1</td>\n",
2064 |        "      <td>7</td>\n",
2065 |        "      <td>13</td>\n",
2066 |        "      <td>19</td>\n",
2067 |        "      <td>1</td>\n",
2068 |        "      <td>7</td>\n",
2069 |        "      <td>13</td>\n",
2070 |        "      <td>19</td>\n",
2071 |        "    </tr>\n",
2072 |        "    <tr>\n",
2073 |        "      <th>2</th>\n",
2074 |        "      <td>2</td>\n",
2075 |        "      <td>8</td>\n",
2076 |        "      <td>14</td>\n",
2077 |        "      <td>20</td>\n",
2078 |        "      <td>2</td>\n",
2079 |        "      <td>8</td>\n",
2080 |        "      <td>14</td>\n",
2081 |        "      <td>20</td>\n",
2082 |        "    </tr>\n",
2083 |        "    <tr>\n",
2084 |        "      <th>3</th>\n",
2085 |        "      <td>3</td>\n",
2086 |        "      <td>9</td>\n",
2087 |        "      <td>15</td>\n",
2088 |        "      <td>21</td>\n",
2089 |        "      <td>3</td>\n",
2090 |        "      <td>kumar</td>\n",
2091 |        "      <td>15</td>\n",
2092 |        "      <td>21</td>\n",
2093 |        "    </tr>\n",
2094 |        "    <tr>\n",
2095 |        "      <th>4</th>\n",
2096 |        "      <td>4</td>\n",
2097 |        "      <td>10</td>\n",
2098 |        "      <td>16</td>\n",
2099 |        "      <td>22</td>\n",
2100 |        "      <td>4</td>\n",
2101 |        "      <td>10</td>\n",
2102 |        "      <td>16</td>\n",
2103 |        "      <td>ineuron</td>\n",
2104 |        "    </tr>\n",
2105 |        "    <tr>\n",
2106 |        "      <th>5</th>\n",
2107 |        "      <td>5</td>\n",
2108 |        "      <td>11</td>\n",
2109 |        "      <td>17</td>\n",
2110 |        "      <td>23</td>\n",
2111 |        "      <td>5</td>\n",
2112 |        "      <td>11</td>\n",
2113 |        "      <td>17</td>\n",
2114 |        "      <td>pwskills</td>\n",
2115 |        "    </tr>\n",
2116 |        "  </tbody>\n",
2117 |        "</table>\n",
2118 |        "</div>"
2119 |       ],
2120 |       "text/plain": [
2121 |        "  key11  key21  key31  key41 key1   key2  key3      key4\n",
2122 |        "1     1      7     13     19    1      7    13        19\n",
2123 |        "2     2      8     14     20    2      8    14        20\n",
2124 |        "3     3      9     15     21    3  kumar    15        21\n",
2125 |        "4     4     10     16     22    4     10    16   ineuron\n",
2126 |        "5     5     11     17     23    5     11    17  pwskills"
2127 |       ]
2128 |      },
2129 |      "execution_count": 53,
2130 |      "metadata": {},
2131 |      "output_type": "execute_result"
2132 |     }
2133 |    ],
2134 |    "source": [
2135 |     "df10.join(df20 , how = 'inner')"
2136 |    ]
2137 |   },
2138 |   {
2139 |    "cell_type": "code",
2140 |    "execution_count": 54,
2141 |    "id": "58e349ec-edfa-4fab-aae3-cd4751620a56",
2142 |    "metadata": {},
2143 |    "outputs": [
2144 |     {
2145 |      "data": {
2146 |       "text/html": [
2147 |        "<div>\n",
2148 |        "<style scoped>\n",
2149 |        "    .dataframe tbody tr th:only-of-type {\n",
2150 |        "        vertical-align: middle;\n",
2151 |        "    }\n",
2152 |        "\n",
2153 |        "    .dataframe tbody tr th {\n",
2154 |        "        vertical-align: top;\n",
2155 |        "    }\n",
2156 |        "\n",
2157 |        "    .dataframe thead th {\n",
2158 |        "        text-align: right;\n",
2159 |        "    }\n",
2160 |        "</style>\n",
2161 |        "<table border=\"1\" class=\"dataframe\">\n",
2162 |        "  <thead>\n",
2163 |        "    <tr style=\"text-align: right;\">\n",
2164 |        "      <th></th>\n",
2165 |        "      <th>key11</th>\n",
2166 |        "      <th>key21</th>\n",
2167 |        "      <th>key31</th>\n",
2168 |        "      <th>key41</th>\n",
2169 |        "    </tr>\n",
2170 |        "  </thead>\n",
2171 |        "  <tbody>\n",
2172 |        "    <tr>\n",
2173 |        "      <th>1</th>\n",
2174 |        "      <td>1</td>\n",
2175 |        "      <td>7</td>\n",
2176 |        "      <td>13</td>\n",
2177 |        "      <td>19</td>\n",
2178 |        "    </tr>\n",
2179 |        "    <tr>\n",
2180 |        "      <th>2</th>\n",
2181 |        "      <td>2</td>\n",
2182 |        "      <td>8</td>\n",
2183 |        "      <td>14</td>\n",
2184 |        "      <td>20</td>\n",
2185 |        "    </tr>\n",
2186 |        "    <tr>\n",
2187 |        "      <th>3</th>\n",
2188 |        "      <td>3</td>\n",
2189 |        "      <td>9</td>\n",
2190 |        "      <td>15</td>\n",
2191 |        "      <td>21</td>\n",
2192 |        "    </tr>\n",
2193 |        "    <tr>\n",
2194 |        "      <th>4</th>\n",
2195 |        "      <td>4</td>\n",
2196 |        "      <td>10</td>\n",
2197 |        "      <td>16</td>\n",
2198 |        "      <td>22</td>\n",
2199 |        "    </tr>\n",
2200 |        "    <tr>\n",
2201 |        "      <th>5</th>\n",
2202 |        "      <td>5</td>\n",
2203 |        "      <td>11</td>\n",
2204 |        "      <td>17</td>\n",
2205 |        "      <td>23</td>\n",
2206 |        "    </tr>\n",
2207 |        "    <tr>\n",
2208 |        "      <th>6</th>\n",
2209 |        "      <td>sudh</td>\n",
2210 |        "      <td>12</td>\n",
2211 |        "      <td>18</td>\n",
2212 |        "      <td>24</td>\n",
2213 |        "    </tr>\n",
2214 |        "  </tbody>\n",
2215 |        "</table>\n",
2216 |        "</div>"
2217 |       ],
2218 |       "text/plain": [
2219 |        "  key11  key21  key31  key41\n",
2220 |        "1     1      7     13     19\n",
2221 |        "2     2      8     14     20\n",
2222 |        "3     3      9     15     21\n",
2223 |        "4     4     10     16     22\n",
2224 |        "5     5     11     17     23\n",
2225 |        "6  sudh     12     18     24"
2226 |       ]
2227 |      },
2228 |      "execution_count": 54,
2229 |      "metadata": {},
2230 |      "output_type": "execute_result"
2231 |     }
2232 |    ],
2233 |    "source": [
2234 |     "df10"
2235 |    ]
2236 |   },
2237 |   {
2238 |    "cell_type": "code",
2239 |    "execution_count": 55,
2240 |    "id": "4a2fa551-0e0a-4c15-ac25-c3c14a93f202",
2241 |    "metadata": {},
2242 |    "outputs": [
2243 |     {
2244 |      "data": {
2245 |       "text/html": [
2246 |        "<div>\n",
2247 |        "<style scoped>\n",
2248 |        "    .dataframe tbody tr th:only-of-type {\n",
2249 |        "        vertical-align: middle;\n",
2250 |        "    }\n",
2251 |        "\n",
2252 |        "    .dataframe tbody tr th {\n",
2253 |        "        vertical-align: top;\n",
2254 |        "    }\n",
2255 |        "\n",
2256 |        "    .dataframe thead th {\n",
2257 |        "        text-align: right;\n",
2258 |        "    }\n",
2259 |        "</style>\n",
2260 |        "<table border=\"1\" class=\"dataframe\">\n",
2261 |        "  <thead>\n",
2262 |        "    <tr style=\"text-align: right;\">\n",
2263 |        "      <th></th>\n",
2264 |        "      <th>key1</th>\n",
2265 |        "      <th>key2</th>\n",
2266 |        "      <th>key3</th>\n",
2267 |        "      <th>key4</th>\n",
2268 |        "    </tr>\n",
2269 |        "  </thead>\n",
2270 |        "  <tbody>\n",
2271 |        "    <tr>\n",
2272 |        "      <th>1</th>\n",
2273 |        "      <td>1</td>\n",
2274 |        "      <td>7</td>\n",
2275 |        "      <td>13</td>\n",
2276 |        "      <td>19</td>\n",
2277 |        "    </tr>\n",
2278 |        "    <tr>\n",
2279 |        "      <th>2</th>\n",
2280 |        "      <td>2</td>\n",
2281 |        "      <td>8</td>\n",
2282 |        "      <td>14</td>\n",
2283 |        "      <td>20</td>\n",
2284 |        "    </tr>\n",
2285 |        "    <tr>\n",
2286 |        "      <th>3</th>\n",
2287 |        "      <td>3</td>\n",
2288 |        "      <td>kumar</td>\n",
2289 |        "      <td>15</td>\n",
2290 |        "      <td>21</td>\n",
2291 |        "    </tr>\n",
2292 |        "    <tr>\n",
2293 |        "      <th>4</th>\n",
2294 |        "      <td>4</td>\n",
2295 |        "      <td>10</td>\n",
2296 |        "      <td>16</td>\n",
2297 |        "      <td>ineuron</td>\n",
2298 |        "    </tr>\n",
2299 |        "    <tr>\n",
2300 |        "      <th>5</th>\n",
2301 |        "      <td>5</td>\n",
2302 |        "      <td>11</td>\n",
2303 |        "      <td>17</td>\n",
2304 |        "      <td>pwskills</td>\n",
2305 |        "    </tr>\n",
2306 |        "    <tr>\n",
2307 |        "      <th>sudh</th>\n",
2308 |        "      <td>sudh</td>\n",
2309 |        "      <td>12</td>\n",
2310 |        "      <td>18</td>\n",
2311 |        "      <td>24</td>\n",
2312 |        "    </tr>\n",
2313 |        "  </tbody>\n",
2314 |        "</table>\n",
2315 |        "</div>"
2316 |       ],
2317 |       "text/plain": [
2318 |        "      key1   key2  key3      key4\n",
2319 |        "1        1      7    13        19\n",
2320 |        "2        2      8    14        20\n",
2321 |        "3        3  kumar    15        21\n",
2322 |        "4        4     10    16   ineuron\n",
2323 |        "5        5     11    17  pwskills\n",
2324 |        "sudh  sudh     12    18        24"
2325 |       ]
2326 |      },
2327 |      "execution_count": 55,
2328 |      "metadata": {},
2329 |      "output_type": "execute_result"
2330 |     }
2331 |    ],
2332 |    "source": [
2333 |     "df20"
2334 |    ]
2335 |   },
2336 |   {
2337 |    "cell_type": "code",
2338 |    "execution_count": 57,
2339 |    "id": "b9954f1a-378b-431e-9f47-47a97db85ab0",
2340 |    "metadata": {},
2341 |    "outputs": [
2342 |     {
2343 |      "data": {
2344 |       "text/html": [
2345 |        "<div>\n",
2346 |        "<style scoped>\n",
2347 |        "    .dataframe tbody tr th:only-of-type {\n",
2348 |        "        vertical-align: middle;\n",
2349 |        "    }\n",
2350 |        "\n",
2351 |        "    .dataframe tbody tr th {\n",
2352 |        "        vertical-align: top;\n",
2353 |        "    }\n",
2354 |        "\n",
2355 |        "    .dataframe thead th {\n",
2356 |        "        text-align: right;\n",
2357 |        "    }\n",
2358 |        "</style>\n",
2359 |        "<table border=\"1\" class=\"dataframe\">\n",
2360 |        "  <thead>\n",
2361 |        "    <tr style=\"text-align: right;\">\n",
2362 |        "      <th></th>\n",
2363 |        "      <th>key1</th>\n",
2364 |        "      <th>key2</th>\n",
2365 |        "      <th>key3</th>\n",
2366 |        "      <th>key4</th>\n",
2367 |        "    </tr>\n",
2368 |        "  </thead>\n",
2369 |        "  <tbody>\n",
2370 |        "    <tr>\n",
2371 |        "      <th>0</th>\n",
2372 |        "      <td>1</td>\n",
2373 |        "      <td>7</td>\n",
2374 |        "      <td>13</td>\n",
2375 |        "      <td>19</td>\n",
2376 |        "    </tr>\n",
2377 |        "    <tr>\n",
2378 |        "      <th>1</th>\n",
2379 |        "      <td>2</td>\n",
2380 |        "      <td>8</td>\n",
2381 |        "      <td>14</td>\n",
2382 |        "      <td>20</td>\n",
2383 |        "    </tr>\n",
2384 |        "    <tr>\n",
2385 |        "      <th>2</th>\n",
2386 |        "      <td>3</td>\n",
2387 |        "      <td>9</td>\n",
2388 |        "      <td>15</td>\n",
2389 |        "      <td>21</td>\n",
2390 |        "    </tr>\n",
2391 |        "    <tr>\n",
2392 |        "      <th>3</th>\n",
2393 |        "      <td>4</td>\n",
2394 |        "      <td>10</td>\n",
2395 |        "      <td>16</td>\n",
2396 |        "      <td>22</td>\n",
2397 |        "    </tr>\n",
2398 |        "    <tr>\n",
2399 |        "      <th>4</th>\n",
2400 |        "      <td>5</td>\n",
2401 |        "      <td>11</td>\n",
2402 |        "      <td>17</td>\n",
2403 |        "      <td>23</td>\n",
2404 |        "    </tr>\n",
2405 |        "    <tr>\n",
2406 |        "      <th>5</th>\n",
2407 |        "      <td>sudh</td>\n",
2408 |        "      <td>12</td>\n",
2409 |        "      <td>18</td>\n",
2410 |        "      <td>24</td>\n",
2411 |        "    </tr>\n",
2412 |        "    <tr>\n",
2413 |        "      <th>0</th>\n",
2414 |        "      <td>1</td>\n",
2415 |        "      <td>7</td>\n",
2416 |        "      <td>13</td>\n",
2417 |        "      <td>19</td>\n",
2418 |        "    </tr>\n",
2419 |        "    <tr>\n",
2420 |        "      <th>1</th>\n",
2421 |        "      <td>2</td>\n",
2422 |        "      <td>8</td>\n",
2423 |        "      <td>14</td>\n",
2424 |        "      <td>20</td>\n",
2425 |        "    </tr>\n",
2426 |        "    <tr>\n",
2427 |        "      <th>2</th>\n",
2428 |        "      <td>3</td>\n",
2429 |        "      <td>kumar</td>\n",
2430 |        "      <td>15</td>\n",
2431 |        "      <td>21</td>\n",
2432 |        "    </tr>\n",
2433 |        "    <tr>\n",
2434 |        "      <th>3</th>\n",
2435 |        "      <td>4</td>\n",
2436 |        "      <td>10</td>\n",
2437 |        "      <td>16</td>\n",
2438 |        "      <td>ineuron</td>\n",
2439 |        "    </tr>\n",
2440 |        "    <tr>\n",
2441 |        "      <th>4</th>\n",
2442 |        "      <td>5</td>\n",
2443 |        "      <td>11</td>\n",
2444 |        "      <td>17</td>\n",
2445 |        "      <td>pwskills</td>\n",
2446 |        "    </tr>\n",
2447 |        "    <tr>\n",
2448 |        "      <th>5</th>\n",
2449 |        "      <td>sudh</td>\n",
2450 |        "      <td>12</td>\n",
2451 |        "      <td>18</td>\n",
2452 |        "      <td>24</td>\n",
2453 |        "    </tr>\n",
2454 |        "  </tbody>\n",
2455 |        "</table>\n",
2456 |        "</div>"
2457 |       ],
2458 |       "text/plain": [
2459 |        "   key1   key2  key3      key4\n",
2460 |        "0     1      7    13        19\n",
2461 |        "1     2      8    14        20\n",
2462 |        "2     3      9    15        21\n",
2463 |        "3     4     10    16        22\n",
2464 |        "4     5     11    17        23\n",
2465 |        "5  sudh     12    18        24\n",
2466 |        "0     1      7    13        19\n",
2467 |        "1     2      8    14        20\n",
2468 |        "2     3  kumar    15        21\n",
2469 |        "3     4     10    16   ineuron\n",
2470 |        "4     5     11    17  pwskills\n",
2471 |        "5  sudh     12    18        24"
2472 |       ]
2473 |      },
2474 |      "execution_count": 57,
2475 |      "metadata": {},
2476 |      "output_type": "execute_result"
2477 |     }
2478 |    ],
2479 |    "source": [
2480 |     "pd.concat([df1,df2] , axis=0)"
2481 |    ]
2482 |   },
2483 |   {
2484 |    "cell_type": "code",
2485 |    "execution_count": 60,
2486 |    "id": "2bab2522-d095-468c-ae5a-fb985bad6db7",
2487 |    "metadata": {},
2488 |    "outputs": [
2489 |     {
2490 |      "data": {
2491 |       "text/html": [
2492 |        "<div>\n",
2493 |        "<style scoped>\n",
2494 |        "    .dataframe tbody tr th:only-of-type {\n",
2495 |        "        vertical-align: middle;\n",
2496 |        "    }\n",
2497 |        "\n",
2498 |        "    .dataframe tbody tr th {\n",
2499 |        "        vertical-align: top;\n",
2500 |        "    }\n",
2501 |        "\n",
2502 |        "    .dataframe thead th {\n",
2503 |        "        text-align: right;\n",
2504 |        "    }\n",
2505 |        "</style>\n",
2506 |        "<table border=\"1\" class=\"dataframe\">\n",
2507 |        "  <thead>\n",
2508 |        "    <tr style=\"text-align: right;\">\n",
2509 |        "      <th></th>\n",
2510 |        "      <th>key1</th>\n",
2511 |        "      <th>key2</th>\n",
2512 |        "      <th>key3</th>\n",
2513 |        "      <th>key4</th>\n",
2514 |        "      <th>key1</th>\n",
2515 |        "      <th>key2</th>\n",
2516 |        "      <th>key3</th>\n",
2517 |        "      <th>key4</th>\n",
2518 |        "    </tr>\n",
2519 |        "  </thead>\n",
2520 |        "  <tbody>\n",
2521 |        "    <tr>\n",
2522 |        "      <th>0</th>\n",
2523 |        "      <td>1</td>\n",
2524 |        "      <td>7</td>\n",
2525 |        "      <td>13</td>\n",
2526 |        "      <td>19</td>\n",
2527 |        "      <td>1</td>\n",
2528 |        "      <td>7</td>\n",
2529 |        "      <td>13</td>\n",
2530 |        "      <td>19</td>\n",
2531 |        "    </tr>\n",
2532 |        "    <tr>\n",
2533 |        "      <th>1</th>\n",
2534 |        "      <td>2</td>\n",
2535 |        "      <td>8</td>\n",
2536 |        "      <td>14</td>\n",
2537 |        "      <td>20</td>\n",
2538 |        "      <td>2</td>\n",
2539 |        "      <td>8</td>\n",
2540 |        "      <td>14</td>\n",
2541 |        "      <td>20</td>\n",
2542 |        "    </tr>\n",
2543 |        "    <tr>\n",
2544 |        "      <th>2</th>\n",
2545 |        "      <td>3</td>\n",
2546 |        "      <td>9</td>\n",
2547 |        "      <td>15</td>\n",
2548 |        "      <td>21</td>\n",
2549 |        "      <td>3</td>\n",
2550 |        "      <td>kumar</td>\n",
2551 |        "      <td>15</td>\n",
2552 |        "      <td>21</td>\n",
2553 |        "    </tr>\n",
2554 |        "    <tr>\n",
2555 |        "      <th>3</th>\n",
2556 |        "      <td>4</td>\n",
2557 |        "      <td>10</td>\n",
2558 |        "      <td>16</td>\n",
2559 |        "      <td>22</td>\n",
2560 |        "      <td>4</td>\n",
2561 |        "      <td>10</td>\n",
2562 |        "      <td>16</td>\n",
2563 |        "      <td>ineuron</td>\n",
2564 |        "    </tr>\n",
2565 |        "    <tr>\n",
2566 |        "      <th>4</th>\n",
2567 |        "      <td>5</td>\n",
2568 |        "      <td>11</td>\n",
2569 |        "      <td>17</td>\n",
2570 |        "      <td>23</td>\n",
2571 |        "      <td>5</td>\n",
2572 |        "      <td>11</td>\n",
2573 |        "      <td>17</td>\n",
2574 |        "      <td>pwskills</td>\n",
2575 |        "    </tr>\n",
2576 |        "    <tr>\n",
2577 |        "      <th>5</th>\n",
2578 |        "      <td>sudh</td>\n",
2579 |        "      <td>12</td>\n",
2580 |        "      <td>18</td>\n",
2581 |        "      <td>24</td>\n",
2582 |        "      <td>sudh</td>\n",
2583 |        "      <td>12</td>\n",
2584 |        "      <td>18</td>\n",
2585 |        "      <td>24</td>\n",
2586 |        "    </tr>\n",
2587 |        "  </tbody>\n",
2588 |        "</table>\n",
2589 |        "</div>"
2590 |       ],
2591 |       "text/plain": [
2592 |        "   key1 key2  key3 key4  key1   key2  key3      key4\n",
2593 |        "0     1    7    13   19     1      7    13        19\n",
2594 |        "1     2    8    14   20     2      8    14        20\n",
2595 |        "2     3    9    15   21     3  kumar    15        21\n",
2596 |        "3     4   10    16   22     4     10    16   ineuron\n",
2597 |        "4     5   11    17   23     5     11    17  pwskills\n",
2598 |        "5  sudh   12    18   24  sudh     12    18        24"
2599 |       ]
2600 |      },
2601 |      "execution_count": 60,
2602 |      "metadata": {},
2603 |      "output_type": "execute_result"
2604 |     }
2605 |    ],
2606 |    "source": [
2607 |     "pd.concat([df1,df2] , axis=1)"
2608 |    ]
2609 |   },
2610 |   {
2611 |    "cell_type": "code",
2612 |    "execution_count": 61,
2613 |    "id": "2f1459e2-3b7e-4820-a836-b81aaef0a9b5",
2614 |    "metadata": {},
2615 |    "outputs": [],
2616 |    "source": [
2617 |     "import numpy as np "
2618 |    ]
2619 |   },
2620 |   {
2621 |    "cell_type": "code",
2622 |    "execution_count": 62,
2623 |    "id": "b3a340e3-d856-4f37-9021-aa892653dc5e",
2624 |    "metadata": {},
2625 |    "outputs": [],
2626 |    "source": [
2627 |     "l = [1,2,3,4,4]"
2628 |    ]
2629 |   },
2630 |   {
2631 |    "cell_type": "code",
2632 |    "execution_count": 64,
2633 |    "id": "de1f4257-a2a7-4ee4-a4bc-389eb07678e5",
2634 |    "metadata": {},
2635 |    "outputs": [
2636 |     {
2637 |      "data": {
2638 |       "text/plain": [
2639 |        "list"
2640 |       ]
2641 |      },
2642 |      "execution_count": 64,
2643 |      "metadata": {},
2644 |      "output_type": "execute_result"
2645 |     }
2646 |    ],
2647 |    "source": [
2648 |     "type(l)"
2649 |    ]
2650 |   },
2651 |   {
2652 |    "cell_type": "code",
2653 |    "execution_count": 66,
2654 |    "id": "297d9ac3-3769-4947-b3cf-b06d84046fdd",
2655 |    "metadata": {},
2656 |    "outputs": [],
2657 |    "source": [
2658 |     "a = np.array(l)"
2659 |    ]
2660 |   },
2661 |   {
2662 |    "cell_type": "code",
2663 |    "execution_count": 67,
2664 |    "id": "f91841fd-f18d-4f2a-b479-715f495dddf6",
2665 |    "metadata": {},
2666 |    "outputs": [
2667 |     {
2668 |      "data": {
2669 |       "text/plain": [
2670 |        "numpy.ndarray"
2671 |       ]
2672 |      },
2673 |      "execution_count": 67,
2674 |      "metadata": {},
2675 |      "output_type": "execute_result"
2676 |     }
2677 |    ],
2678 |    "source": [
2679 |     "type(a)"
2680 |    ]
2681 |   },
2682 |   {
2683 |    "cell_type": "code",
2684 |    "execution_count": 68,
2685 |    "id": "f216ea2d-8ae5-4c3f-b62b-26746d1e9f7a",
2686 |    "metadata": {},
2687 |    "outputs": [
2688 |     {
2689 |      "data": {
2690 |       "text/plain": [
2691 |        "array([1, 2, 3, 4, 4])"
2692 |       ]
2693 |      },
2694 |      "execution_count": 68,
2695 |      "metadata": {},
2696 |      "output_type": "execute_result"
2697 |     }
2698 |    ],
2699 |    "source": [
2700 |     "a"
2701 |    ]
2702 |   },
2703 |   {
2704 |    "cell_type": "code",
2705 |    "execution_count": 73,
2706 |    "id": "6af1eefc-7afd-4dc3-a1ee-9d326c7fcfef",
2707 |    "metadata": {},
2708 |    "outputs": [],
2709 |    "source": [
2710 |     "a1 = np.array([[1,2,3] , [3,4,5]])"
2711 |    ]
2712 |   },
2713 |   {
2714 |    "cell_type": "code",
2715 |    "execution_count": 74,
2716 |    "id": "45c4a3a5-d104-4901-819f-24936093ef36",
2717 |    "metadata": {},
2718 |    "outputs": [
2719 |     {
2720 |      "data": {
2721 |       "text/plain": [
2722 |        "array([[1, 2, 3],\n",
2723 |        "       [3, 4, 5]])"
2724 |       ]
2725 |      },
2726 |      "execution_count": 74,
2727 |      "metadata": {},
2728 |      "output_type": "execute_result"
2729 |     }
2730 |    ],
2731 |    "source": [
2732 |     "a1\n"
2733 |    ]
2734 |   },
2735 |   {
2736 |    "cell_type": "code",
2737 |    "execution_count": 75,
2738 |    "id": "15fa41fa-f81d-42ac-a118-b8bcf0666e56",
2739 |    "metadata": {},
2740 |    "outputs": [],
2741 |    "source": [
2742 |     "a2 = np.array([[[1,2,3] , [4,.5,6]]])"
2743 |    ]
2744 |   },
2745 |   {
2746 |    "cell_type": "code",
2747 |    "execution_count": 76,
2748 |    "id": "74ae2bb7-e7aa-43d5-9179-5f5b5948caf8",
2749 |    "metadata": {},
2750 |    "outputs": [
2751 |     {
2752 |      "data": {
2753 |       "text/plain": [
2754 |        "array([[[1. , 2. , 3. ],\n",
2755 |        "        [4. , 0.5, 6. ]]])"
2756 |       ]
2757 |      },
2758 |      "execution_count": 76,
2759 |      "metadata": {},
2760 |      "output_type": "execute_result"
2761 |     }
2762 |    ],
2763 |    "source": [
2764 |     "a2"
2765 |    ]
2766 |   },
2767 |   {
2768 |    "cell_type": "code",
2769 |    "execution_count": 77,
2770 |    "id": "4464a24e-0e19-43fa-b730-1993d2a1cfde",
2771 |    "metadata": {},
2772 |    "outputs": [
2773 |     {
2774 |      "data": {
2775 |       "text/plain": [
2776 |        "array([1, 2, 3, 4, 4])"
2777 |       ]
2778 |      },
2779 |      "execution_count": 77,
2780 |      "metadata": {},
2781 |      "output_type": "execute_result"
2782 |     }
2783 |    ],
2784 |    "source": [
2785 |     "a"
2786 |    ]
2787 |   },
2788 |   {
2789 |    "cell_type": "code",
2790 |    "execution_count": 78,
2791 |    "id": "793d947e-5b3f-4ee5-b352-f70f4bf76ded",
2792 |    "metadata": {},
2793 |    "outputs": [
2794 |     {
2795 |      "data": {
2796 |       "text/plain": [
2797 |        "array([[1, 2, 3],\n",
2798 |        "       [3, 4, 5]])"
2799 |       ]
2800 |      },
2801 |      "execution_count": 78,
2802 |      "metadata": {},
2803 |      "output_type": "execute_result"
2804 |     }
2805 |    ],
2806 |    "source": [
2807 |     "a1"
2808 |    ]
2809 |   },
2810 |   {
2811 |    "cell_type": "code",
2812 |    "execution_count": 79,
2813 |    "id": "2f8c9477-257b-458b-bb46-d5348fa84e41",
2814 |    "metadata": {},
2815 |    "outputs": [
2816 |     {
2817 |      "data": {
2818 |       "text/plain": [
2819 |        "array([[[1. , 2. , 3. ],\n",
2820 |        "        [4. , 0.5, 6. ]]])"
2821 |       ]
2822 |      },
2823 |      "execution_count": 79,
2824 |      "metadata": {},
2825 |      "output_type": "execute_result"
2826 |     }
2827 |    ],
2828 |    "source": [
2829 |     "a2"
2830 |    ]
2831 |   },
2832 |   {
2833 |    "cell_type": "code",
2834 |    "execution_count": 80,
2835 |    "id": "e3b68bb7-d3e4-44c3-ba3f-8419b7d91d28",
2836 |    "metadata": {},
2837 |    "outputs": [
2838 |     {
2839 |      "data": {
2840 |       "text/plain": [
2841 |        "1"
2842 |       ]
2843 |      },
2844 |      "execution_count": 80,
2845 |      "metadata": {},
2846 |      "output_type": "execute_result"
2847 |     }
2848 |    ],
2849 |    "source": [
2850 |     "a.ndim"
2851 |    ]
2852 |   },
2853 |   {
2854 |    "cell_type": "code",
2855 |    "execution_count": 81,
2856 |    "id": "0879e33b-5b1a-4f95-b7bf-b286fe4dd453",
2857 |    "metadata": {},
2858 |    "outputs": [
2859 |     {
2860 |      "data": {
2861 |       "text/plain": [
2862 |        "2"
2863 |       ]
2864 |      },
2865 |      "execution_count": 81,
2866 |      "metadata": {},
2867 |      "output_type": "execute_result"
2868 |     }
2869 |    ],
2870 |    "source": [
2871 |     "a1.ndim\n"
2872 |    ]
2873 |   },
2874 |   {
2875 |    "cell_type": "code",
2876 |    "execution_count": 82,
2877 |    "id": "984ac883-a6e3-487f-bad9-3de78a4170a3",
2878 |    "metadata": {},
2879 |    "outputs": [
2880 |     {
2881 |      "data": {
2882 |       "text/plain": [
2883 |        "3"
2884 |       ]
2885 |      },
2886 |      "execution_count": 82,
2887 |      "metadata": {},
2888 |      "output_type": "execute_result"
2889 |     }
2890 |    ],
2891 |    "source": [
2892 |     "a2.ndim"
2893 |    ]
2894 |   },
2895 |   {
2896 |    "cell_type": "code",
2897 |    "execution_count": 83,
2898 |    "id": "3a024126-8be3-4bad-b26c-7e4fa51b5fab",
2899 |    "metadata": {},
2900 |    "outputs": [],
2901 |    "source": [
2902 |     "a3 = np.array([[[1,2,3] , [4,.5,6]],[[1,2,3] , [4,.5,6]],[[1,2,3] , [4,.5,6]]])"
2903 |    ]
2904 |   },
2905 |   {
2906 |    "cell_type": "code",
2907 |    "execution_count": 84,
2908 |    "id": "83ac298d-c474-4c57-94bf-97befda66e9f",
2909 |    "metadata": {},
2910 |    "outputs": [
2911 |     {
2912 |      "data": {
2913 |       "text/plain": [
2914 |        "array([[[1. , 2. , 3. ],\n",
2915 |        "        [4. , 0.5, 6. ]],\n",
2916 |        "\n",
2917 |        "       [[1. , 2. , 3. ],\n",
2918 |        "        [4. , 0.5, 6. ]],\n",
2919 |        "\n",
2920 |        "       [[1. , 2. , 3. ],\n",
2921 |        "        [4. , 0.5, 6. ]]])"
2922 |       ]
2923 |      },
2924 |      "execution_count": 84,
2925 |      "metadata": {},
2926 |      "output_type": "execute_result"
2927 |     }
2928 |    ],
2929 |    "source": [
2930 |     "a3"
2931 |    ]
2932 |   },
2933 |   {
2934 |    "cell_type": "code",
2935 |    "execution_count": 85,
2936 |    "id": "a73903e8-ee36-4925-aec1-818e90db861d",
2937 |    "metadata": {},
2938 |    "outputs": [
2939 |     {
2940 |      "data": {
2941 |       "text/plain": [
2942 |        "3"
2943 |       ]
2944 |      },
2945 |      "execution_count": 85,
2946 |      "metadata": {},
2947 |      "output_type": "execute_result"
2948 |     }
2949 |    ],
2950 |    "source": [
2951 |     "a3.ndim"
2952 |    ]
2953 |   },
2954 |   {
2955 |    "cell_type": "code",
2956 |    "execution_count": 86,
2957 |    "id": "c89ab63e-a4f7-44db-91cd-6c863c452e3d",
2958 |    "metadata": {},
2959 |    "outputs": [],
2960 |    "source": [
2961 |     "l = [1,2,3,4]"
2962 |    ]
2963 |   },
2964 |   {
2965 |    "cell_type": "code",
2966 |    "execution_count": 90,
2967 |    "id": "f8904384-5afe-4ca3-b1d9-6ecda7d1fdc1",
2968 |    "metadata": {},
2969 |    "outputs": [],
2970 |    "source": [
2971 |     "a = np.asarray(l)"
2972 |    ]
2973 |   },
2974 |   {
2975 |    "cell_type": "code",
2976 |    "execution_count": 89,
2977 |    "id": "cb904727-8761-4abd-a299-8023cb291c90",
2978 |    "metadata": {},
2979 |    "outputs": [],
2980 |    "source": [
2981 |     "m = np.matrix(l)"
2982 |    ]
2983 |   },
2984 |   {
2985 |    "cell_type": "code",
2986 |    "execution_count": 93,
2987 |    "id": "5a9db928-647b-429b-b9df-5457e2ee61d8",
2988 |    "metadata": {},
2989 |    "outputs": [
2990 |     {
2991 |      "data": {
2992 |       "text/plain": [
2993 |        "array([1, 2, 3, 4])"
2994 |       ]
2995 |      },
2996 |      "execution_count": 93,
2997 |      "metadata": {},
2998 |      "output_type": "execute_result"
2999 |     }
3000 |    ],
3001 |    "source": [
3002 |     "np.asanyarray(l)"
3003 |    ]
3004 |   },
3005 |   {
3006 |    "cell_type": "code",
3007 |    "execution_count": 91,
3008 |    "id": "05739d24-0006-4822-8308-0c09c9ad2c91",
3009 |    "metadata": {},
3010 |    "outputs": [
3011 |     {
3012 |      "data": {
3013 |       "text/plain": [
3014 |        "array([1, 2, 3, 4])"
3015 |       ]
3016 |      },
3017 |      "execution_count": 91,
3018 |      "metadata": {},
3019 |      "output_type": "execute_result"
3020 |     }
3021 |    ],
3022 |    "source": [
3023 |     "np.asanyarray(a)"
3024 |    ]
3025 |   },
3026 |   {
3027 |    "cell_type": "code",
3028 |    "execution_count": 92,
3029 |    "id": "a69c8a25-5fd7-4be4-a539-f556f6d6b23d",
3030 |    "metadata": {},
3031 |    "outputs": [
3032 |     {
3033 |      "data": {
3034 |       "text/plain": [
3035 |        "matrix([[1, 2, 3, 4]])"
3036 |       ]
3037 |      },
3038 |      "execution_count": 92,
3039 |      "metadata": {},
3040 |      "output_type": "execute_result"
3041 |     }
3042 |    ],
3043 |    "source": [
3044 |     "np.asanyarray(m)"
3045 |    ]
3046 |   },
3047 |   {
3048 |    "cell_type": "code",
3049 |    "execution_count": 94,
3050 |    "id": "7bc1cccf-ab21-4f96-bbea-6055f87211d7",
3051 |    "metadata": {},
3052 |    "outputs": [
3053 |     {
3054 |      "data": {
3055 |       "text/plain": [
3056 |        "array([1, 2, 3, 4])"
3057 |       ]
3058 |      },
3059 |      "execution_count": 94,
3060 |      "metadata": {},
3061 |      "output_type": "execute_result"
3062 |     }
3063 |    ],
3064 |    "source": [
3065 |     "a"
3066 |    ]
3067 |   },
3068 |   {
3069 |    "cell_type": "code",
3070 |    "execution_count": 95,
3071 |    "id": "e82a186b-49a9-4cc3-98a6-a854a63bd49a",
3072 |    "metadata": {},
3073 |    "outputs": [],
3074 |    "source": [
3075 |     "a1 = a "
3076 |    ]
3077 |   },
3078 |   {
3079 |    "cell_type": "code",
3080 |    "execution_count": 96,
3081 |    "id": "489017ea-102f-4608-8bd0-f309e5a81dc1",
3082 |    "metadata": {},
3083 |    "outputs": [
3084 |     {
3085 |      "data": {
3086 |       "text/plain": [
3087 |        "array([1, 2, 3, 4])"
3088 |       ]
3089 |      },
3090 |      "execution_count": 96,
3091 |      "metadata": {},
3092 |      "output_type": "execute_result"
3093 |     }
3094 |    ],
3095 |    "source": [
3096 |     "a1"
3097 |    ]
3098 |   },
3099 |   {
3100 |    "cell_type": "code",
3101 |    "execution_count": 97,
3102 |    "id": "d108d7bd-b0e4-4caf-b48a-08717f904e0f",
3103 |    "metadata": {},
3104 |    "outputs": [
3105 |     {
3106 |      "data": {
3107 |       "text/plain": [
3108 |        "array([1, 2, 3, 4])"
3109 |       ]
3110 |      },
3111 |      "execution_count": 97,
3112 |      "metadata": {},
3113 |      "output_type": "execute_result"
3114 |     }
3115 |    ],
3116 |    "source": [
3117 |     "a"
3118 |    ]
3119 |   },
3120 |   {
3121 |    "cell_type": "code",
3122 |    "execution_count": 98,
3123 |    "id": "3561d72c-753f-45f9-a460-376590750774",
3124 |    "metadata": {},
3125 |    "outputs": [
3126 |     {
3127 |      "data": {
3128 |       "text/plain": [
3129 |        "array([1, 2, 3, 4])"
3130 |       ]
3131 |      },
3132 |      "execution_count": 98,
3133 |      "metadata": {},
3134 |      "output_type": "execute_result"
3135 |     }
3136 |    ],
3137 |    "source": [
3138 |     "a"
3139 |    ]
3140 |   },
3141 |   {
3142 |    "cell_type": "code",
3143 |    "execution_count": 100,
3144 |    "id": "c95a3e81-3aa2-4f3a-95b7-0050174a706d",
3145 |    "metadata": {},
3146 |    "outputs": [],
3147 |    "source": [
3148 |     "a[0] = 10"
3149 |    ]
3150 |   },
3151 |   {
3152 |    "cell_type": "code",
3153 |    "execution_count": 101,
3154 |    "id": "0dca2851-0cee-4fe3-a3b5-6eccc4f11388",
3155 |    "metadata": {},
3156 |    "outputs": [
3157 |     {
3158 |      "data": {
3159 |       "text/plain": [
3160 |        "array([10,  2,  3,  4])"
3161 |       ]
3162 |      },
3163 |      "execution_count": 101,
3164 |      "metadata": {},
3165 |      "output_type": "execute_result"
3166 |     }
3167 |    ],
3168 |    "source": [
3169 |     "a"
3170 |    ]
3171 |   },
3172 |   {
3173 |    "cell_type": "code",
3174 |    "execution_count": 102,
3175 |    "id": "8c416e48-2de1-4374-930f-f05346205989",
3176 |    "metadata": {},
3177 |    "outputs": [
3178 |     {
3179 |      "data": {
3180 |       "text/plain": [
3181 |        "array([10,  2,  3,  4])"
3182 |       ]
3183 |      },
3184 |      "execution_count": 102,
3185 |      "metadata": {},
3186 |      "output_type": "execute_result"
3187 |     }
3188 |    ],
3189 |    "source": [
3190 |     "a1"
3191 |    ]
3192 |   },
3193 |   {
3194 |    "cell_type": "code",
3195 |    "execution_count": 104,
3196 |    "id": "2104476a-e1fd-4df9-b08e-b9c559b2a103",
3197 |    "metadata": {},
3198 |    "outputs": [],
3199 |    "source": [
3200 |     "a1[3] = 50"
3201 |    ]
3202 |   },
3203 |   {
3204 |    "cell_type": "code",
3205 |    "execution_count": 105,
3206 |    "id": "4c14a0c4-3f70-4251-a113-66fb593b8381",
3207 |    "metadata": {},
3208 |    "outputs": [
3209 |     {
3210 |      "data": {
3211 |       "text/plain": [
3212 |        "array([10,  2,  3, 50])"
3213 |       ]
3214 |      },
3215 |      "execution_count": 105,
3216 |      "metadata": {},
3217 |      "output_type": "execute_result"
3218 |     }
3219 |    ],
3220 |    "source": [
3221 |     "a1"
3222 |    ]
3223 |   },
3224 |   {
3225 |    "cell_type": "code",
3226 |    "execution_count": 106,
3227 |    "id": "411029ac-9aa6-4429-b4e2-5c6c5ede6e54",
3228 |    "metadata": {},
3229 |    "outputs": [
3230 |     {
3231 |      "data": {
3232 |       "text/plain": [
3233 |        "array([10,  2,  3, 50])"
3234 |       ]
3235 |      },
3236 |      "execution_count": 106,
3237 |      "metadata": {},
3238 |      "output_type": "execute_result"
3239 |     }
3240 |    ],
3241 |    "source": [
3242 |     "a"
3243 |    ]
3244 |   },
3245 |   {
3246 |    "cell_type": "code",
3247 |    "execution_count": 107,
3248 |    "id": "eb73a9bb-f4a0-42cb-be16-119625194db9",
3249 |    "metadata": {},
3250 |    "outputs": [],
3251 |    "source": [
3252 |     "a2 = np.copy(a)"
3253 |    ]
3254 |   },
3255 |   {
3256 |    "cell_type": "code",
3257 |    "execution_count": 108,
3258 |    "id": "0f8e53b8-3efc-4699-be1c-2309a4a8e48a",
3259 |    "metadata": {},
3260 |    "outputs": [
3261 |     {
3262 |      "data": {
3263 |       "text/plain": [
3264 |        "array([10,  2,  3, 50])"
3265 |       ]
3266 |      },
3267 |      "execution_count": 108,
3268 |      "metadata": {},
3269 |      "output_type": "execute_result"
3270 |     }
3271 |    ],
3272 |    "source": [
3273 |     "a2"
3274 |    ]
3275 |   },
3276 |   {
3277 |    "cell_type": "code",
3278 |    "execution_count": 111,
3279 |    "id": "f5144950-f06e-4d62-8367-436e51c877ae",
3280 |    "metadata": {},
3281 |    "outputs": [],
3282 |    "source": [
3283 |     "a2[2] = 30"
3284 |    ]
3285 |   },
3286 |   {
3287 |    "cell_type": "code",
3288 |    "execution_count": 112,
3289 |    "id": "6235e46a-0ec7-47a1-b61a-49c17d8ec117",
3290 |    "metadata": {},
3291 |    "outputs": [
3292 |     {
3293 |      "data": {
3294 |       "text/plain": [
3295 |        "array([10,  2, 30, 50])"
3296 |       ]
3297 |      },
3298 |      "execution_count": 112,
3299 |      "metadata": {},
3300 |      "output_type": "execute_result"
3301 |     }
3302 |    ],
3303 |    "source": [
3304 |     "a2"
3305 |    ]
3306 |   },
3307 |   {
3308 |    "cell_type": "code",
3309 |    "execution_count": 113,
3310 |    "id": "47373eeb-80c8-46b7-bbd0-37a66bed9f3d",
3311 |    "metadata": {},
3312 |    "outputs": [
3313 |     {
3314 |      "data": {
3315 |       "text/plain": [
3316 |        "array([10,  2,  3, 50])"
3317 |       ]
3318 |      },
3319 |      "execution_count": 113,
3320 |      "metadata": {},
3321 |      "output_type": "execute_result"
3322 |     }
3323 |    ],
3324 |    "source": [
3325 |     "a"
3326 |    ]
3327 |   },
3328 |   {
3329 |    "cell_type": "code",
3330 |    "execution_count": 114,
3331 |    "id": "0e7ce447-386a-4c0a-acfa-57ba497e96bc",
3332 |    "metadata": {},
3333 |    "outputs": [
3334 |     {
3335 |      "data": {
3336 |       "text/plain": [
3337 |        "array([[ True, False, False, False],\n",
3338 |        "       [False,  True, False, False],\n",
3339 |        "       [False, False,  True, False]])"
3340 |       ]
3341 |      },
3342 |      "execution_count": 114,
3343 |      "metadata": {},
3344 |      "output_type": "execute_result"
3345 |     }
3346 |    ],
3347 |    "source": [
3348 |     "np.fromfunction(lambda i,j : i==j , (3,4))"
3349 |    ]
3350 |   },
3351 |   {
3352 |    "cell_type": "code",
3353 |    "execution_count": 116,
3354 |    "id": "fd421eb4-5197-4baf-91f3-3039bd4c6649",
3355 |    "metadata": {},
3356 |    "outputs": [
3357 |     {
3358 |      "data": {
3359 |       "text/plain": [
3360 |        "array([[ True, False, False, False],\n",
3361 |        "       [False,  True, False, False],\n",
3362 |        "       [False, False,  True, False]])"
3363 |       ]
3364 |      },
3365 |      "execution_count": 116,
3366 |      "metadata": {},
3367 |      "output_type": "execute_result"
3368 |     }
3369 |    ],
3370 |    "source": [
3371 |     "np.fromfunction(lambda i,j: i==j, (3,4))"
3372 |    ]
3373 |   },
3374 |   {
3375 |    "cell_type": "code",
3376 |    "execution_count": 118,
3377 |    "id": "72296cbc-ab35-4cec-ace1-2e601b9b503c",
3378 |    "metadata": {},
3379 |    "outputs": [
3380 |     {
3381 |      "data": {
3382 |       "text/plain": [
3383 |        "array([[[0.8537019 , 0.89559976],\n",
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3385 |        "        [0.43384847, 0.47219106]],\n",
3386 |        "\n",
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3388 |        "        [0.04490197, 0.73227366],\n",
3389 |        "        [0.2114251 , 0.7732894 ]]])"
3390 |       ]
3391 |      },
3392 |      "execution_count": 118,
3393 |      "metadata": {},
3394 |      "output_type": "execute_result"
3395 |     }
3396 |    ],
3397 |    "source": [
3398 |     "np.random.rand(2,3,2)"
3399 |    ]
3400 |   },
3401 |   {
3402 |    "cell_type": "code",
3403 |    "execution_count": 119,
3404 |    "id": "ea49e53b-7d14-4e2e-86bd-f70fb5da0ed1",
3405 |    "metadata": {},
3406 |    "outputs": [
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3418 |        "\n",
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3427 |        "         [0.33217116, 0.97522411]]]])"
3428 |       ]
3429 |      },
3430 |      "execution_count": 119,
3431 |      "metadata": {},
3432 |      "output_type": "execute_result"
3433 |     }
3434 |    ],
3435 |    "source": [
3436 |     "np.random.rand(2,3,2,2)"
3437 |    ]
3438 |   },
3439 |   {
3440 |    "cell_type": "code",
3441 |    "execution_count": 123,
3442 |    "id": "f34d4a91-f829-45e5-b1b8-4f48da258386",
3443 |    "metadata": {},
3444 |    "outputs": [
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3456 |        "\n",
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3462 |        "         5.25020759e-02],\n",
3463 |        "        [6.35797430e-01, 8.16778744e-01, 7.61395700e-01, 7.18578055e-01,\n",
3464 |        "         2.76044227e-01]],\n",
3465 |        "\n",
3466 |        "       [[1.44572781e-02, 9.19394486e-02, 4.45699994e-01, 7.56659750e-01,\n",
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3469 |        "         5.02090497e-01],\n",
3470 |        "        [6.54299995e-01, 5.18945152e-01, 5.41727605e-01, 6.34531055e-01,\n",
3471 |        "         3.08507114e-01],\n",
3472 |        "        [2.74715955e-01, 8.49466402e-01, 6.35123288e-01, 7.76779365e-01,\n",
3473 |        "         3.27604916e-01]]])"
3474 |       ]
3475 |      },
3476 |      "execution_count": 123,
3477 |      "metadata": {},
3478 |      "output_type": "execute_result"
3479 |     }
3480 |    ],
3481 |    "source": [
3482 |     "np.random.rand(3,4,5)"
3483 |    ]
3484 |   },
3485 |   {
3486 |    "cell_type": "code",
3487 |    "execution_count": 130,
3488 |    "id": "3152344c-7acf-4b37-bf93-560ddb67010f",
3489 |    "metadata": {},
3490 |    "outputs": [],
3491 |    "source": [
3492 |     "d = np.random.randn(3,4)"
3493 |    ]
3494 |   },
3495 |   {
3496 |    "cell_type": "code",
3497 |    "execution_count": 131,
3498 |    "id": "9f752550-0999-4fe1-afab-e89d0b65127b",
3499 |    "metadata": {},
3500 |    "outputs": [
3501 |     {
3502 |      "data": {
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3504 |        "<div>\n",
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3519 |        "  <thead>\n",
3520 |        "    <tr style=\"text-align: right;\">\n",
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3522 |        "      <th>0</th>\n",
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3525 |        "      <th>3</th>\n",
3526 |        "    </tr>\n",
3527 |        "  </thead>\n",
3528 |        "  <tbody>\n",
3529 |        "    <tr>\n",
3530 |        "      <th>0</th>\n",
3531 |        "      <td>-0.976138</td>\n",
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3533 |        "      <td>1.007809</td>\n",
3534 |        "      <td>-0.089897</td>\n",
3535 |        "    </tr>\n",
3536 |        "    <tr>\n",
3537 |        "      <th>1</th>\n",
3538 |        "      <td>0.212211</td>\n",
3539 |        "      <td>-0.893465</td>\n",
3540 |        "      <td>-0.005551</td>\n",
3541 |        "      <td>1.240048</td>\n",
3542 |        "    </tr>\n",
3543 |        "    <tr>\n",
3544 |        "      <th>2</th>\n",
3545 |        "      <td>0.367181</td>\n",
3546 |        "      <td>-1.252373</td>\n",
3547 |        "      <td>1.449878</td>\n",
3548 |        "      <td>-0.699765</td>\n",
3549 |        "    </tr>\n",
3550 |        "  </tbody>\n",
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3555 |        "          0         1         2         3\n",
3556 |        "0 -0.976138 -0.805954  1.007809 -0.089897\n",
3557 |        "1  0.212211 -0.893465 -0.005551  1.240048\n",
3558 |        "2  0.367181 -1.252373  1.449878 -0.699765"
3559 |       ]
3560 |      },
3561 |      "execution_count": 131,
3562 |      "metadata": {},
3563 |      "output_type": "execute_result"
3564 |     }
3565 |    ],
3566 |    "source": [
3567 |     "pd.DataFrame(d)"
3568 |    ]
3569 |   },
3570 |   {
3571 |    "cell_type": "code",
3572 |    "execution_count": 132,
3573 |    "id": "859bdc07-eb8e-4310-9e74-0a9c05092cdb",
3574 |    "metadata": {},
3575 |    "outputs": [],
3576 |    "source": [
3577 |     "d1=np.random.randint(0,10,(4,4,2))"
3578 |    ]
3579 |   },
3580 |   {
3581 |    "cell_type": "code",
3582 |    "execution_count": 133,
3583 |    "id": "cf911994-4b2b-45a0-a30f-29978c842ef5",
3584 |    "metadata": {},
3585 |    "outputs": [
3586 |     {
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3593 |        "\n",
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3597 |        "        [4, 1]],\n",
3598 |        "\n",
3599 |        "       [[6, 6],\n",
3600 |        "        [6, 3],\n",
3601 |        "        [8, 8],\n",
3602 |        "        [5, 4]],\n",
3603 |        "\n",
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3605 |        "        [5, 1],\n",
3606 |        "        [0, 8],\n",
3607 |        "        [4, 4]]])"
3608 |       ]
3609 |      },
3610 |      "execution_count": 133,
3611 |      "metadata": {},
3612 |      "output_type": "execute_result"
3613 |     }
3614 |    ],
3615 |    "source": [
3616 |     "d1"
3617 |    ]
3618 |   },
3619 |   {
3620 |    "cell_type": "code",
3621 |    "execution_count": 135,
3622 |    "id": "d88bf048-418e-43ae-82f8-b6a5c23c3670",
3623 |    "metadata": {},
3624 |    "outputs": [
3625 |     {
3626 |      "data": {
3627 |       "text/plain": [
3628 |        "array([[0, 3],\n",
3629 |        "       [2, 4],\n",
3630 |        "       [2, 1],\n",
3631 |        "       [2, 4],\n",
3632 |        "       [9, 5],\n",
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3642 |        "       [0, 8],\n",
3643 |        "       [4, 4]])"
3644 |       ]
3645 |      },
3646 |      "execution_count": 135,
3647 |      "metadata": {},
3648 |      "output_type": "execute_result"
3649 |     }
3650 |    ],
3651 |    "source": [
3652 |     "d1.reshape(16,2)"
3653 |    ]
3654 |   },
3655 |   {
3656 |    "cell_type": "code",
3657 |    "execution_count": 136,
3658 |    "id": "3c4d6088-f66a-4f35-a7e3-6e73b8fda110",
3659 |    "metadata": {},
3660 |    "outputs": [
3661 |     {
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3672 |       ]
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3675 |      "metadata": {},
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3677 |     }
3678 |    ],
3679 |    "source": [
3680 |     "d1.reshape(8,4)"
3681 |    ]
3682 |   },
3683 |   {
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3685 |    "execution_count": 145,
3686 |    "id": "a99c725b-0fda-4af9-b1cb-2d37d301982e",
3687 |    "metadata": {},
3688 |    "outputs": [
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3721 |        "    </tr>\n",
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3723 |        "      <th>2</th>\n",
3724 |        "      <td>2</td>\n",
3725 |        "    </tr>\n",
3726 |        "    <tr>\n",
3727 |        "      <th>3</th>\n",
3728 |        "      <td>4</td>\n",
3729 |        "    </tr>\n",
3730 |        "    <tr>\n",
3731 |        "      <th>4</th>\n",
3732 |        "      <td>2</td>\n",
3733 |        "    </tr>\n",
3734 |        "    <tr>\n",
3735 |        "      <th>5</th>\n",
3736 |        "      <td>1</td>\n",
3737 |        "    </tr>\n",
3738 |        "    <tr>\n",
3739 |        "      <th>6</th>\n",
3740 |        "      <td>2</td>\n",
3741 |        "    </tr>\n",
3742 |        "    <tr>\n",
3743 |        "      <th>7</th>\n",
3744 |        "      <td>4</td>\n",
3745 |        "    </tr>\n",
3746 |        "    <tr>\n",
3747 |        "      <th>8</th>\n",
3748 |        "      <td>9</td>\n",
3749 |        "    </tr>\n",
3750 |        "    <tr>\n",
3751 |        "      <th>9</th>\n",
3752 |        "      <td>5</td>\n",
3753 |        "    </tr>\n",
3754 |        "    <tr>\n",
3755 |        "      <th>10</th>\n",
3756 |        "      <td>0</td>\n",
3757 |        "    </tr>\n",
3758 |        "    <tr>\n",
3759 |        "      <th>11</th>\n",
3760 |        "      <td>7</td>\n",
3761 |        "    </tr>\n",
3762 |        "    <tr>\n",
3763 |        "      <th>12</th>\n",
3764 |        "      <td>9</td>\n",
3765 |        "    </tr>\n",
3766 |        "    <tr>\n",
3767 |        "      <th>13</th>\n",
3768 |        "      <td>7</td>\n",
3769 |        "    </tr>\n",
3770 |        "    <tr>\n",
3771 |        "      <th>14</th>\n",
3772 |        "      <td>4</td>\n",
3773 |        "    </tr>\n",
3774 |        "    <tr>\n",
3775 |        "      <th>15</th>\n",
3776 |        "      <td>1</td>\n",
3777 |        "    </tr>\n",
3778 |        "    <tr>\n",
3779 |        "      <th>16</th>\n",
3780 |        "      <td>6</td>\n",
3781 |        "    </tr>\n",
3782 |        "    <tr>\n",
3783 |        "      <th>17</th>\n",
3784 |        "      <td>6</td>\n",
3785 |        "    </tr>\n",
3786 |        "    <tr>\n",
3787 |        "      <th>18</th>\n",
3788 |        "      <td>6</td>\n",
3789 |        "    </tr>\n",
3790 |        "    <tr>\n",
3791 |        "      <th>19</th>\n",
3792 |        "      <td>3</td>\n",
3793 |        "    </tr>\n",
3794 |        "    <tr>\n",
3795 |        "      <th>20</th>\n",
3796 |        "      <td>8</td>\n",
3797 |        "    </tr>\n",
3798 |        "    <tr>\n",
3799 |        "      <th>21</th>\n",
3800 |        "      <td>8</td>\n",
3801 |        "    </tr>\n",
3802 |        "    <tr>\n",
3803 |        "      <th>22</th>\n",
3804 |        "      <td>5</td>\n",
3805 |        "    </tr>\n",
3806 |        "    <tr>\n",
3807 |        "      <th>23</th>\n",
3808 |        "      <td>4</td>\n",
3809 |        "    </tr>\n",
3810 |        "    <tr>\n",
3811 |        "      <th>24</th>\n",
3812 |        "      <td>7</td>\n",
3813 |        "    </tr>\n",
3814 |        "    <tr>\n",
3815 |        "      <th>25</th>\n",
3816 |        "      <td>9</td>\n",
3817 |        "    </tr>\n",
3818 |        "    <tr>\n",
3819 |        "      <th>26</th>\n",
3820 |        "      <td>5</td>\n",
3821 |        "    </tr>\n",
3822 |        "    <tr>\n",
3823 |        "      <th>27</th>\n",
3824 |        "      <td>1</td>\n",
3825 |        "    </tr>\n",
3826 |        "    <tr>\n",
3827 |        "      <th>28</th>\n",
3828 |        "      <td>0</td>\n",
3829 |        "    </tr>\n",
3830 |        "    <tr>\n",
3831 |        "      <th>29</th>\n",
3832 |        "      <td>8</td>\n",
3833 |        "    </tr>\n",
3834 |        "    <tr>\n",
3835 |        "      <th>30</th>\n",
3836 |        "      <td>4</td>\n",
3837 |        "    </tr>\n",
3838 |        "    <tr>\n",
3839 |        "      <th>31</th>\n",
3840 |        "      <td>4</td>\n",
3841 |        "    </tr>\n",
3842 |        "  </tbody>\n",
3843 |        "</table>\n",
3844 |        "</div>"
3845 |       ],
3846 |       "text/plain": [
3847 |        "    0\n",
3848 |        "0   0\n",
3849 |        "1   3\n",
3850 |        "2   2\n",
3851 |        "3   4\n",
3852 |        "4   2\n",
3853 |        "5   1\n",
3854 |        "6   2\n",
3855 |        "7   4\n",
3856 |        "8   9\n",
3857 |        "9   5\n",
3858 |        "10  0\n",
3859 |        "11  7\n",
3860 |        "12  9\n",
3861 |        "13  7\n",
3862 |        "14  4\n",
3863 |        "15  1\n",
3864 |        "16  6\n",
3865 |        "17  6\n",
3866 |        "18  6\n",
3867 |        "19  3\n",
3868 |        "20  8\n",
3869 |        "21  8\n",
3870 |        "22  5\n",
3871 |        "23  4\n",
3872 |        "24  7\n",
3873 |        "25  9\n",
3874 |        "26  5\n",
3875 |        "27  1\n",
3876 |        "28  0\n",
3877 |        "29  8\n",
3878 |        "30  4\n",
3879 |        "31  4"
3880 |       ]
3881 |      },
3882 |      "execution_count": 145,
3883 |      "metadata": {},
3884 |      "output_type": "execute_result"
3885 |     }
3886 |    ],
3887 |    "source": [
3888 |     "pd.DataFrame(d1.reshape(32,-1987987))"
3889 |    ]
3890 |   },
3891 |   {
3892 |    "cell_type": "code",
3893 |    "execution_count": 134,
3894 |    "id": "b53d211c-3ae5-4e8a-9f4d-ce0b9a4ea4c9",
3895 |    "metadata": {},
3896 |    "outputs": [
3897 |     {
3898 |      "ename": "ValueError",
3899 |      "evalue": "Must pass 2-d input. shape=(4, 4, 2)",
3900 |      "output_type": "error",
3901 |      "traceback": [
3902 |       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
3903 |       "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
3904 |       "Cell \u001b[0;32mIn [134], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mDataFrame\u001b[49m\u001b[43m(\u001b[49m\u001b[43md1\u001b[49m\u001b[43m)\u001b[49m\n",
3905 |       "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/pandas/core/frame.py:720\u001b[0m, in \u001b[0;36mDataFrame.__init__\u001b[0;34m(self, data, index, columns, dtype, copy)\u001b[0m\n\u001b[1;32m    710\u001b[0m         mgr \u001b[38;5;241m=\u001b[39m dict_to_mgr(\n\u001b[1;32m    711\u001b[0m             \u001b[38;5;66;03m# error: Item \"ndarray\" of \"Union[ndarray, Series, Index]\" has no\u001b[39;00m\n\u001b[1;32m    712\u001b[0m             \u001b[38;5;66;03m# attribute \"name\"\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    717\u001b[0m             typ\u001b[38;5;241m=\u001b[39mmanager,\n\u001b[1;32m    718\u001b[0m         )\n\u001b[1;32m    719\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 720\u001b[0m         mgr \u001b[38;5;241m=\u001b[39m \u001b[43mndarray_to_mgr\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    721\u001b[0m \u001b[43m            \u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    722\u001b[0m \u001b[43m            \u001b[49m\u001b[43mindex\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    723\u001b[0m \u001b[43m            \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    724\u001b[0m \u001b[43m            \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    725\u001b[0m \u001b[43m            \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    726\u001b[0m \u001b[43m            \u001b[49m\u001b[43mtyp\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmanager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    727\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    729\u001b[0m \u001b[38;5;66;03m# For data is list-like, or Iterable (will consume into list)\u001b[39;00m\n\u001b[1;32m    730\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m is_list_like(data):\n",
3906 |       "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/pandas/core/internals/construction.py:329\u001b[0m, in \u001b[0;36mndarray_to_mgr\u001b[0;34m(values, index, columns, dtype, copy, typ)\u001b[0m\n\u001b[1;32m    324\u001b[0m         values \u001b[38;5;241m=\u001b[39m values\u001b[38;5;241m.\u001b[39mreshape(\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m    326\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    327\u001b[0m     \u001b[38;5;66;03m# by definition an array here\u001b[39;00m\n\u001b[1;32m    328\u001b[0m     \u001b[38;5;66;03m# the dtypes will be coerced to a single dtype\u001b[39;00m\n\u001b[0;32m--> 329\u001b[0m     values \u001b[38;5;241m=\u001b[39m \u001b[43m_prep_ndarraylike\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy_on_sanitize\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    331\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m dtype \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_dtype_equal(values\u001b[38;5;241m.\u001b[39mdtype, dtype):\n\u001b[1;32m    332\u001b[0m     \u001b[38;5;66;03m# GH#40110 see similar check inside sanitize_array\u001b[39;00m\n\u001b[1;32m    333\u001b[0m     rcf \u001b[38;5;241m=\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m (is_integer_dtype(dtype) \u001b[38;5;129;01mand\u001b[39;00m values\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mkind \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
3907 |       "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/pandas/core/internals/construction.py:583\u001b[0m, in \u001b[0;36m_prep_ndarraylike\u001b[0;34m(values, copy)\u001b[0m\n\u001b[1;32m    581\u001b[0m     values \u001b[38;5;241m=\u001b[39m values\u001b[38;5;241m.\u001b[39mreshape((values\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m], \u001b[38;5;241m1\u001b[39m))\n\u001b[1;32m    582\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m values\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m2\u001b[39m:\n\u001b[0;32m--> 583\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMust pass 2-d input. shape=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mvalues\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    585\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m values\n",
3908 |       "\u001b[0;31mValueError\u001b[0m: Must pass 2-d input. shape=(4, 4, 2)"
3909 |      ]
3910 |     }
3911 |    ],
3912 |    "source": [
3913 |     "pd.DataFrame(d1)"
3914 |    ]
3915 |   },
3916 |   {
3917 |    "cell_type": "code",
3918 |    "execution_count": null,
3919 |    "id": "11cdb3c9-bf4c-4568-b7be-a5935031a5d3",
3920 |    "metadata": {},
3921 |    "outputs": [],
3922 |    "source": []
3923 |   }
3924 |  ],
3925 |  "metadata": {
3926 |   "kernelspec": {
3927 |    "display_name": "Python 3 (ipykernel)",
3928 |    "language": "python",
3929 |    "name": "python3"
3930 |   },
3931 |   "language_info": {
3932 |    "codemirror_mode": {
3933 |     "name": "ipython",
3934 |     "version": 3
3935 |    },
3936 |    "file_extension": ".py",
3937 |    "mimetype": "text/x-python",
3938 |    "name": "python",
3939 |    "nbconvert_exporter": "python",
3940 |    "pygments_lexer": "ipython3",
3941 |    "version": "3.10.6"
3942 |   }
3943 |  },
3944 |  "nbformat": 4,
3945 |  "nbformat_minor": 5
3946 | }
3947 | 


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