DAY 7.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "xlsx = pd.ExcelFile('RFOPCSV.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_excel(xlsx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>[s]</th>\n",
       "      <th>CH1[V]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.00600</td>\n",
       "      <td>1.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.00600</td>\n",
       "      <td>2.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.00600</td>\n",
       "      <td>2.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.00599</td>\n",
       "      <td>1.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.00599</td>\n",
       "      <td>2.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-0.00599</td>\n",
       "      <td>2.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-0.00599</td>\n",
       "      <td>2.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-0.00599</td>\n",
       "      <td>2.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-0.00598</td>\n",
       "      <td>1.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-0.00598</td>\n",
       "      <td>2.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>-0.00598</td>\n",
       "      <td>2.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>-0.00598</td>\n",
       "      <td>2.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>-0.00598</td>\n",
       "      <td>2.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>-0.00597</td>\n",
       "      <td>2.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>-0.00597</td>\n",
       "      <td>2.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>-0.00597</td>\n",
       "      <td>2.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>-0.00597</td>\n",
       "      <td>2.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>-0.00597</td>\n",
       "      <td>2.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>-0.00596</td>\n",
       "      <td>2.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>-0.00596</td>\n",
       "      <td>2.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>-0.00596</td>\n",
       "      <td>2.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>-0.00596</td>\n",
       "      <td>2.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>-0.00596</td>\n",
       "      <td>2.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>-0.00595</td>\n",
       "      <td>2.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>-0.00595</td>\n",
       "      <td>2.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>-0.00595</td>\n",
       "      <td>2.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>-0.00595</td>\n",
       "      <td>2.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>-0.00595</td>\n",
       "      <td>2.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>-0.00594</td>\n",
       "      <td>2.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>-0.00594</td>\n",
       "      <td>2.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5970</th>\n",
       "      <td>0.00594</td>\n",
       "      <td>-2.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5971</th>\n",
       "      <td>0.00594</td>\n",
       "      <td>-2.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5972</th>\n",
       "      <td>0.00594</td>\n",
       "      <td>-2.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5973</th>\n",
       "      <td>0.00595</td>\n",
       "      <td>-2.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5974</th>\n",
       "      <td>0.00595</td>\n",
       "      <td>-2.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5975</th>\n",
       "      <td>0.00595</td>\n",
       "      <td>-2.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5976</th>\n",
       "      <td>0.00595</td>\n",
       "      <td>-2.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5977</th>\n",
       "      <td>0.00595</td>\n",
       "      <td>-2.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5978</th>\n",
       "      <td>0.00596</td>\n",
       "      <td>-2.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5979</th>\n",
       "      <td>0.00596</td>\n",
       "      <td>-2.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5980</th>\n",
       "      <td>0.00596</td>\n",
       "      <td>-2.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5981</th>\n",
       "      <td>0.00596</td>\n",
       "      <td>-2.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5982</th>\n",
       "      <td>0.00596</td>\n",
       "      <td>-2.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5983</th>\n",
       "      <td>0.00597</td>\n",
       "      <td>-2.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5984</th>\n",
       "      <td>0.00597</td>\n",
       "      <td>-2.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5985</th>\n",
       "      <td>0.00597</td>\n",
       "      <td>-2.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5986</th>\n",
       "      <td>0.00597</td>\n",
       "      <td>-2.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5987</th>\n",
       "      <td>0.00597</td>\n",
       "      <td>-2.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5988</th>\n",
       "      <td>0.00598</td>\n",
       "      <td>-2.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5989</th>\n",
       "      <td>0.00598</td>\n",
       "      <td>-2.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5990</th>\n",
       "      <td>0.00598</td>\n",
       "      <td>-2.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5991</th>\n",
       "      <td>0.00598</td>\n",
       "      <td>-2.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5992</th>\n",
       "      <td>0.00598</td>\n",
       "      <td>-2.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5993</th>\n",
       "      <td>0.00599</td>\n",
       "      <td>-2.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5994</th>\n",
       "      <td>0.00599</td>\n",
       "      <td>-2.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5995</th>\n",
       "      <td>0.00599</td>\n",
       "      <td>-2.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5996</th>\n",
       "      <td>0.00599</td>\n",
       "      <td>-2.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5997</th>\n",
       "      <td>0.00599</td>\n",
       "      <td>-2.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5998</th>\n",
       "      <td>0.00600</td>\n",
       "      <td>-2.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5999</th>\n",
       "      <td>0.00600</td>\n",
       "      <td>-2.52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          [s]  CH1[V]\n",
       "0    -0.00600    1.96\n",
       "1    -0.00600    2.28\n",
       "2    -0.00600    2.12\n",
       "3    -0.00599    1.96\n",
       "4    -0.00599    2.12\n",
       "5    -0.00599    2.04\n",
       "6    -0.00599    2.28\n",
       "7    -0.00599    2.28\n",
       "8    -0.00598    1.96\n",
       "9    -0.00598    2.20\n",
       "10   -0.00598    2.44\n",
       "11   -0.00598    2.36\n",
       "12   -0.00598    2.44\n",
       "13   -0.00597    2.52\n",
       "14   -0.00597    2.36\n",
       "15   -0.00597    2.28\n",
       "16   -0.00597    2.28\n",
       "17   -0.00597    2.28\n",
       "18   -0.00596    2.52\n",
       "19   -0.00596    2.12\n",
       "20   -0.00596    2.04\n",
       "21   -0.00596    2.36\n",
       "22   -0.00596    2.76\n",
       "23   -0.00595    2.76\n",
       "24   -0.00595    2.84\n",
       "25   -0.00595    2.76\n",
       "26   -0.00595    2.52\n",
       "27   -0.00595    2.60\n",
       "28   -0.00594    2.52\n",
       "29   -0.00594    2.68\n",
       "...       ...     ...\n",
       "5970  0.00594   -2.84\n",
       "5971  0.00594   -2.92\n",
       "5972  0.00594   -2.76\n",
       "5973  0.00595   -2.76\n",
       "5974  0.00595   -2.84\n",
       "5975  0.00595   -2.76\n",
       "5976  0.00595   -2.76\n",
       "5977  0.00595   -2.84\n",
       "5978  0.00596   -2.84\n",
       "5979  0.00596   -2.92\n",
       "5980  0.00596   -2.60\n",
       "5981  0.00596   -2.52\n",
       "5982  0.00596   -2.60\n",
       "5983  0.00597   -2.76\n",
       "5984  0.00597   -2.76\n",
       "5985  0.00597   -2.36\n",
       "5986  0.00597   -2.44\n",
       "5987  0.00597   -2.44\n",
       "5988  0.00598   -2.52\n",
       "5989  0.00598   -2.36\n",
       "5990  0.00598   -2.44\n",
       "5991  0.00598   -2.68\n",
       "5992  0.00598   -2.44\n",
       "5993  0.00599   -2.20\n",
       "5994  0.00599   -2.44\n",
       "5995  0.00599   -2.44\n",
       "5996  0.00599   -2.44\n",
       "5997  0.00599   -2.36\n",
       "5998  0.00600   -2.36\n",
       "5999  0.00600   -2.52\n",
       "\n",
       "[6000 rows x 2 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.487611</td>\n",
       "      <td>1.295476</td>\n",
       "      <td>-1.753653</td>\n",
       "      <td>0.016856</td>\n",
       "      <td>1.888206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.539450</td>\n",
       "      <td>-0.650807</td>\n",
       "      <td>0.763296</td>\n",
       "      <td>1.804309</td>\n",
       "      <td>-0.478329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.964746</td>\n",
       "      <td>-0.069561</td>\n",
       "      <td>0.738514</td>\n",
       "      <td>-0.432296</td>\n",
       "      <td>-1.157984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.244807</td>\n",
       "      <td>-1.935851</td>\n",
       "      <td>-0.779262</td>\n",
       "      <td>-0.305350</td>\n",
       "      <td>0.012864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.733446</td>\n",
       "      <td>0.164785</td>\n",
       "      <td>1.307421</td>\n",
       "      <td>-0.014975</td>\n",
       "      <td>-0.742341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.136418</td>\n",
       "      <td>-1.835363</td>\n",
       "      <td>-0.329547</td>\n",
       "      <td>0.440153</td>\n",
       "      <td>0.074751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-1.027367</td>\n",
       "      <td>0.289991</td>\n",
       "      <td>0.970123</td>\n",
       "      <td>1.593434</td>\n",
       "      <td>1.073812</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4\n",
       "0 -0.487611  1.295476 -1.753653  0.016856  1.888206\n",
       "1 -0.539450 -0.650807  0.763296  1.804309 -0.478329\n",
       "2 -0.964746 -0.069561  0.738514 -0.432296 -1.157984\n",
       "3  0.244807 -1.935851 -0.779262 -0.305350  0.012864\n",
       "4 -0.733446  0.164785  1.307421 -0.014975 -0.742341\n",
       "5  0.136418 -1.835363 -0.329547  0.440153  0.074751\n",
       "6 -1.027367  0.289991  0.970123  1.593434  1.073812"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "df = pd.DataFrame(np.random.randn(7,5))\n",
    "df\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Detecting and Filtering Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.067684</td>\n",
       "      <td>0.067924</td>\n",
       "      <td>0.025598</td>\n",
       "      <td>-0.002298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.998035</td>\n",
       "      <td>0.992106</td>\n",
       "      <td>1.006835</td>\n",
       "      <td>0.996794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-3.428254</td>\n",
       "      <td>-3.548824</td>\n",
       "      <td>-3.184377</td>\n",
       "      <td>-3.745356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.774890</td>\n",
       "      <td>-0.591841</td>\n",
       "      <td>-0.641675</td>\n",
       "      <td>-0.644144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-0.116401</td>\n",
       "      <td>0.101143</td>\n",
       "      <td>0.002073</td>\n",
       "      <td>-0.013611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.616366</td>\n",
       "      <td>0.780282</td>\n",
       "      <td>0.680391</td>\n",
       "      <td>0.654328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.366626</td>\n",
       "      <td>2.653656</td>\n",
       "      <td>3.260383</td>\n",
       "      <td>3.927528</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 0            1            2            3\n",
       "count  1000.000000  1000.000000  1000.000000  1000.000000\n",
       "mean     -0.067684     0.067924     0.025598    -0.002298\n",
       "std       0.998035     0.992106     1.006835     0.996794\n",
       "min      -3.428254    -3.548824    -3.184377    -3.745356\n",
       "25%      -0.774890    -0.591841    -0.641675    -0.644144\n",
       "50%      -0.116401     0.101143     0.002073    -0.013611\n",
       "75%       0.616366     0.780282     0.680391     0.654328\n",
       "max       3.366626     2.653656     3.260383     3.927528"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "np.random.seed(12345)\n",
    "data = pd.DataFrame(np.random.randn(1000, 4))\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "97     3.927528\n",
       "305   -3.399312\n",
       "400   -3.745356\n",
       "Name: 3, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col = data[3]\n",
    "col[np.abs(col) > 3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-0.539741</td>\n",
       "      <td>0.476985</td>\n",
       "      <td>3.248944</td>\n",
       "      <td>-1.021228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>-0.774363</td>\n",
       "      <td>0.552936</td>\n",
       "      <td>0.106061</td>\n",
       "      <td>3.927528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>-0.655054</td>\n",
       "      <td>-0.565230</td>\n",
       "      <td>3.176873</td>\n",
       "      <td>0.959533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>-2.315555</td>\n",
       "      <td>0.457246</td>\n",
       "      <td>-0.025907</td>\n",
       "      <td>-3.399312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>324</th>\n",
       "      <td>0.050188</td>\n",
       "      <td>1.951312</td>\n",
       "      <td>3.260383</td>\n",
       "      <td>0.963301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400</th>\n",
       "      <td>0.146326</td>\n",
       "      <td>0.508391</td>\n",
       "      <td>-0.196713</td>\n",
       "      <td>-3.745356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>-0.293333</td>\n",
       "      <td>-0.242459</td>\n",
       "      <td>-3.056990</td>\n",
       "      <td>1.918403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>523</th>\n",
       "      <td>-3.428254</td>\n",
       "      <td>-0.296336</td>\n",
       "      <td>-0.439938</td>\n",
       "      <td>-0.867165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586</th>\n",
       "      <td>0.275144</td>\n",
       "      <td>1.179227</td>\n",
       "      <td>-3.184377</td>\n",
       "      <td>1.369891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>808</th>\n",
       "      <td>-0.362528</td>\n",
       "      <td>-3.548824</td>\n",
       "      <td>1.553205</td>\n",
       "      <td>-2.186301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>900</th>\n",
       "      <td>3.366626</td>\n",
       "      <td>-2.372214</td>\n",
       "      <td>0.851010</td>\n",
       "      <td>1.332846</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            0         1         2         3\n",
       "5   -0.539741  0.476985  3.248944 -1.021228\n",
       "97  -0.774363  0.552936  0.106061  3.927528\n",
       "102 -0.655054 -0.565230  3.176873  0.959533\n",
       "305 -2.315555  0.457246 -0.025907 -3.399312\n",
       "324  0.050188  1.951312  3.260383  0.963301\n",
       "400  0.146326  0.508391 -0.196713 -3.745356\n",
       "499 -0.293333 -0.242459 -3.056990  1.918403\n",
       "523 -3.428254 -0.296336 -0.439938 -0.867165\n",
       "586  0.275144  1.179227 -3.184377  1.369891\n",
       "808 -0.362528 -3.548824  1.553205 -2.186301\n",
       "900  3.366626 -2.372214  0.851010  1.332846"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(np.abs(data) > 3).any(1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[np.abs(data) > 3] = np.sign(data) * 3\n",
    "x = data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.show(df[2].any(),df[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}