{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.437237</td>\n",
       "    </tr>\n",
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       "      <td>-0.059133</td>\n",
       "      <td>0.412722</td>\n",
       "    </tr>\n",
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       "    </tr>\n",
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      ],
      "text/plain": [
       "          a         b         c\n",
       "0  0.283832  0.134834 -0.250957\n",
       "1  0.258076 -0.186923  0.437237\n",
       "2 -0.457135 -0.059133  0.412722\n",
       "3 -0.044996  0.007934 -0.415092\n",
       "4 -0.073650  0.245717  0.367081"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "np.random.seed(46)\n",
    "df = pd.DataFrame(np.random.rand(5,3), columns=list('abc')) - 0.5\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0.245717</td>\n",
       "      <td>0.367081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.258076</td>\n",
       "      <td>-0.186923</td>\n",
       "      <td>0.437237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.283832</td>\n",
       "      <td>0.134834</td>\n",
       "      <td>-0.250957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.457135</td>\n",
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       "      <td>0.412722</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c\n",
       "3 -0.044996  0.007934 -0.415092\n",
       "4 -0.073650  0.245717  0.367081\n",
       "1  0.258076 -0.186923  0.437237\n",
       "0  0.283832  0.134834 -0.250957\n",
       "2 -0.457135 -0.059133  0.412722"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sort by absolute value\n",
    "df.iloc[df['a'].abs().argsort()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "    <tr>\n",
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       "      <td>-0.186923</td>\n",
       "      <td>0.437237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.283832</td>\n",
       "      <td>0.134834</td>\n",
       "      <td>-0.250957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.457135</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c\n",
       "0 -0.044996  0.007934 -0.415092\n",
       "1 -0.073650  0.245717  0.367081\n",
       "2  0.258076 -0.186923  0.437237\n",
       "3  0.283832  0.134834 -0.250957\n",
       "4 -0.457135 -0.059133  0.412722"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# If necessary, we can reset the index.\n",
    "df.iloc[df['a'].abs().argsort()].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.457135</td>\n",
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       "      <td>0.412722</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>0.437237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.073650</td>\n",
       "      <td>0.245717</td>\n",
       "      <td>0.367081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.044996</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c\n",
       "2 -0.457135 -0.059133  0.412722\n",
       "0  0.283832  0.134834 -0.250957\n",
       "1  0.258076 -0.186923  0.437237\n",
       "4 -0.073650  0.245717  0.367081\n",
       "3 -0.044996  0.007934 -0.415092"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To sort in descending order, negate df['a'].abs()\n",
    "df.iloc[(-df['a'].abs()).argsort()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "It is important to enclose -df['b'].abs() in parentheses since\n",
      "otherwise the negative sign is applied after the argsort which\n",
      "will give wrong results.\n"
     ]
    },
    {
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       "      <td>-0.059133</td>\n",
       "      <td>0.412722</td>\n",
       "    </tr>\n",
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       "      <th>1</th>\n",
       "      <td>0.258076</td>\n",
       "      <td>-0.186923</td>\n",
       "      <td>0.437237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.073650</td>\n",
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       "      <td>0.367081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.283832</td>\n",
       "      <td>0.134834</td>\n",
       "      <td>-0.250957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.044996</td>\n",
       "      <td>0.007934</td>\n",
       "      <td>-0.415092</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c\n",
       "2 -0.457135 -0.059133  0.412722\n",
       "1  0.258076 -0.186923  0.437237\n",
       "4 -0.073650  0.245717  0.367081\n",
       "0  0.283832  0.134834 -0.250957\n",
       "3 -0.044996  0.007934 -0.415092"
      ]
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     "execution_count": 5,
     "metadata": {},
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    }
   ],
   "source": [
    "# Note\n",
    "print(\"It is important to enclose -df['b'].abs() in parentheses since\\n\"\n",
    "      \"otherwise the negative sign is applied after the argsort which\\n\"\n",
    "      \"will give wrong results.\")\n",
    "df.iloc[-df['a'].abs().argsort()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th>2</th>\n",
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       "      <td>0.437237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.073650</td>\n",
       "      <td>0.245717</td>\n",
       "      <td>0.367081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.044996</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c\n",
       "0 -0.457135 -0.059133  0.412722\n",
       "1  0.283832  0.134834 -0.250957\n",
       "2  0.258076 -0.186923  0.437237\n",
       "3 -0.073650  0.245717  0.367081\n",
       "4 -0.044996  0.007934 -0.415092"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# If necessary, index can be reset as before.\n",
    "df.iloc[(-df['a'].abs()).argsort()].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ref:\n",
    "* https://stackoverflow.com/a/54299995/6305733 <- https://stackoverflow.com/questions/30486263/sorting-by-absolute-value-without-changing-the-data"
   ]
  }
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