{
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  {
   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "# Prepare: Remove Constant Columns and Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ac4ed764",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8ed50135",
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "   col1  col2  col3\n",
       "0     1   1.0     1\n",
       "1     2   1.0     2\n",
       "2     3   1.0   101\n",
       "3     4   1.0     3\n",
       "4     5   1.0     4"
      ]
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     "execution_count": 2,
     "metadata": {},
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   ],
   "source": [
    "df = pd.DataFrame()\n",
    "df['col1'] = [1,2,3,4,5]\n",
    "df['col2'] = np.ones(5)\n",
    "df['col3'] = [1,2,101,3,4]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73c64aed",
   "metadata": {},
   "source": [
    "### Removing Constant Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "95164e4f",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   col1  col3\n",
       "0     1     1\n",
       "1     2     2\n",
       "2     3   101\n",
       "3     4     3\n",
       "4     5     4"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from chemml.preprocessing import ConstantColumns, Outliers\n",
    "df1 = ConstantColumns(df)\n",
    "df1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f811cf0",
   "metadata": {},
   "source": [
    "### Removing oultiers based on mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "82e21710",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   col1  col2  col3\n",
       "0     1   1.0     1\n",
       "1     2   1.0     2\n",
       "2     3   1.0   101\n",
       "3     4   1.0     3\n",
       "4     5   1.0     4"
      ]
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     "execution_count": 4,
     "metadata": {},
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    }
   ],
   "source": [
    "df_clean = Outliers(df, m=2.0,strategy='mean')\n",
    "df_clean"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f5f338e",
   "metadata": {},
   "source": [
    "### Removing outliers based on median"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2ebb849b",
   "metadata": {},
   "outputs": [
    {
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       "   col1  col2  col3\n",
       "0     1   1.0     1\n",
       "1     2   1.0     2\n",
       "3     4   1.0     3\n",
       "4     5   1.0     4"
      ]
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     "execution_count": 5,
     "metadata": {},
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   ],
   "source": [
    "df_clean = Outliers(df, m=2.0,strategy='median')\n",
    "df_clean"
   ]
  }
 ],
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