Reversing a Pandas Column.ipynb

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   "source": [
    "import pandas as pd"
   ]
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   "execution_count": 2,
   "id": "7e0ea46c",
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   "outputs": [],
   "source": [
    "df = pd.read_csv('data/sample_data.csv', index_col=0)[['state', 'food']].iloc[:4]"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "# Trying to reverse a pandas columns?\n",
    "\n",
    "* It won't work due to automatic alignment of the index\n",
    "* Use `.values` to get a numpy array, which as no index"
   ]
  },
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   "execution_count": 3,
   "id": "f7d17c29",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>food</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Jane</th>\n",
       "      <td>NY</td>\n",
       "      <td>Steak</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Niko</th>\n",
       "      <td>TX</td>\n",
       "      <td>Lamb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron</th>\n",
       "      <td>FL</td>\n",
       "      <td>Mango</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Penelope</th>\n",
       "      <td>AL</td>\n",
       "      <td>Apple</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "         state   food\n",
       "Jane        NY  Steak\n",
       "Niko        TX   Lamb\n",
       "Aaron       FL  Mango\n",
       "Penelope    AL  Apple"
      ]
     },
     "execution_count": 3,
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   "source": [
    "df"
   ]
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   "id": "54631a3b",
   "metadata": {},
   "source": [
    "## Doesn't work due to automatic alignment of the index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d4123c14",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>food</th>\n",
       "      <th>food_reverse</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Jane</th>\n",
       "      <td>NY</td>\n",
       "      <td>Steak</td>\n",
       "      <td>Steak</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Niko</th>\n",
       "      <td>TX</td>\n",
       "      <td>Lamb</td>\n",
       "      <td>Lamb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron</th>\n",
       "      <td>FL</td>\n",
       "      <td>Mango</td>\n",
       "      <td>Mango</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Penelope</th>\n",
       "      <td>AL</td>\n",
       "      <td>Apple</td>\n",
       "      <td>Apple</td>\n",
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       "         state   food food_reverse\n",
       "Jane        NY  Steak        Steak\n",
       "Niko        TX   Lamb         Lamb\n",
       "Aaron       FL  Mango        Mango\n",
       "Penelope    AL  Apple        Apple"
      ]
     },
     "execution_count": 4,
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   ],
   "source": [
    "df['food_reverse'] = df['food'][::-1]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a9563a6",
   "metadata": {},
   "source": [
    "## Extract numpy array, which has no index!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ed5cf34e",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>food</th>\n",
       "      <th>food_reverse</th>\n",
       "      <th>food_reverse2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Jane</th>\n",
       "      <td>NY</td>\n",
       "      <td>Steak</td>\n",
       "      <td>Steak</td>\n",
       "      <td>Apple</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Niko</th>\n",
       "      <td>TX</td>\n",
       "      <td>Lamb</td>\n",
       "      <td>Lamb</td>\n",
       "      <td>Mango</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron</th>\n",
       "      <td>FL</td>\n",
       "      <td>Mango</td>\n",
       "      <td>Mango</td>\n",
       "      <td>Lamb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Penelope</th>\n",
       "      <td>AL</td>\n",
       "      <td>Apple</td>\n",
       "      <td>Apple</td>\n",
       "      <td>Steak</td>\n",
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      "text/plain": [
       "         state   food food_reverse food_reverse2\n",
       "Jane        NY  Steak        Steak         Apple\n",
       "Niko        TX   Lamb         Lamb         Mango\n",
       "Aaron       FL  Mango        Mango          Lamb\n",
       "Penelope    AL  Apple        Apple         Steak"
      ]
     },
     "execution_count": 5,
     "metadata": {},
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   ],
   "source": [
    "df['food_reverse2'] = df['food'].values[::-1]\n",
    "df"
   ]
  },
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   "execution_count": null,
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