Select the row closest to a selected value

blog.find_row_closest_value_to_input.ipynb

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   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Import\" data-toc-modified-id=\"Import-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Import</a></span><ul class=\"toc-item\"><li><span><a href=\"#Modules\" data-toc-modified-id=\"Modules-1.1\"><span class=\"toc-item-num\">1.1&nbsp;&nbsp;</span>Modules</a></span></li><li><span><a href=\"#Generating-Data\" data-toc-modified-id=\"Generating-Data-1.2\"><span class=\"toc-item-num\">1.2&nbsp;&nbsp;</span>Generating Data</a></span></li></ul></li><li><span><a href=\"#Problem-Statement\" data-toc-modified-id=\"Problem-Statement-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Problem Statement</a></span></li><li><span><a href=\"#Solution\" data-toc-modified-id=\"Solution-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Solution</a></span><ul class=\"toc-item\"><li><span><a href=\"#Explanation\" data-toc-modified-id=\"Explanation-3.1\"><span class=\"toc-item-num\">3.1&nbsp;&nbsp;</span>Explanation</a></span></li></ul></li><li><span><a href=\"#References\" data-toc-modified-id=\"References-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>References</a></span></li></ul></div>"
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
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     "start_time": "2020-06-04T04:36:23.295959Z"
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   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generating Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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     "end_time": "2020-06-04T04:36:23.718185Z",
     "start_time": "2020-06-04T04:36:23.712717Z"
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   "outputs": [],
   "source": [
    "df = pd.DataFrame.from_dict({\"delta_n\": np.random.rand(100, 1).squeeze(), \n",
    "                             \"col1\": np.random.randint(-100, 100, size=(100, 1)).squeeze()})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem Statement"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Select the row closest to a selected `value` in the column `delta_n`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Solution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let"
   ]
  },
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   "execution_count": 3,
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     "start_time": "2020-06-04T04:36:23.720241Z"
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   "outputs": [],
   "source": [
    "value = 0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
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     "end_time": "2020-06-04T04:36:23.749972Z",
     "start_time": "2020-06-04T04:36:23.728031Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "delta_n     0.048184\n",
       "col1       79.000000\n",
       "Name: 92, dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idx = df['delta_n'].sub(value).abs().idxmin()\n",
    "df.loc[idx, :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explanation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Subtract `value` from the `delta_n` column"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
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     "end_time": "2020-06-04T04:36:23.759891Z",
     "start_time": "2020-06-04T04:36:23.752279Z"
    },
    "scrolled": true
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     0.487641\n",
       "1     0.208109\n",
       "2     0.221288\n",
       "3     0.524160\n",
       "4     0.559814\n",
       "        ...   \n",
       "95    0.096815\n",
       "96    0.819692\n",
       "97    0.363321\n",
       "98    0.630596\n",
       "99    0.457670\n",
       "Name: delta_n, Length: 100, dtype: float64"
      ]
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     "execution_count": 5,
     "metadata": {},
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   ],
   "source": [
    "interim_result_1 = df['delta_n'].sub(value)\n",
    "interim_result_1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get absolute values of this subtraction"
   ]
  },
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   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
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     "end_time": "2020-06-04T04:36:23.772031Z",
     "start_time": "2020-06-04T04:36:23.763792Z"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     0.487641\n",
       "1     0.208109\n",
       "2     0.221288\n",
       "3     0.524160\n",
       "4     0.559814\n",
       "        ...   \n",
       "95    0.096815\n",
       "96    0.819692\n",
       "97    0.363321\n",
       "98    0.630596\n",
       "99    0.457670\n",
       "Name: delta_n, Length: 100, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "interim_result_2 = interim_result_1.abs()\n",
    "interim_result_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get the index of the minimum value of the absolute values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-04T04:36:23.783889Z",
     "start_time": "2020-06-04T04:36:23.776136Z"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "92"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "idx = interim_result_2.idxmin()\n",
    "idx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get the closest row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-04T04:36:23.795129Z",
     "start_time": "2020-06-04T04:36:23.786703Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "delta_n     0.048184\n",
       "col1       79.000000\n",
       "Name: 92, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[idx, :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# References"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://stackoverflow.com/questions/52587436/find-row-closest-value-to-input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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