Maui-5-Boxplot.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Boxplots With Matplotlib\n",
    "\n",
    "Boxplots are a great tool for data visualisation, they can be used to understand the distribution of your data, whether it is skewed or not, and whether any outliers are present. In this article we will look at what boxplots are and how we can display them using pandas and matplotlib.\n",
    "\n",
    "## Importing Libraries and Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first few steps we will carry out in our Jupyter Notebook is loading in the libraries and data. In this case we are going to be using [lasio](https://lasio.readthedocs.io/en/latest/) to load our las file, [pandas](https://pandas.pydata.org/) for storing our well log data, and [matplotlib](https://matplotlib.org/) for visualising our data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import lasio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we will load in and view our data. We can do this using `lasio.read()` and passing in a text string. I have appended `.df()` to the end of this in order to convert it to a pandas dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Only engine='normal' can read wrapped files\n"
     ]
    }
   ],
   "source": [
    "df = lasio.read(\"/Users/isaacabrahamodeh/Desktop/Taranaki-wells/Taranaki/maui-5_final.las\").df()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>BS</th>\n",
       "      <th>CALI</th>\n",
       "      <th>DENS</th>\n",
       "      <th>DRHO</th>\n",
       "      <th>DTC</th>\n",
       "      <th>GR</th>\n",
       "      <th>NEUT</th>\n",
       "      <th>PEF</th>\n",
       "      <th>RESD</th>\n",
       "      <th>RESM</th>\n",
       "      <th>RESS</th>\n",
       "      <th>SP</th>\n",
       "      <th>TEMP</th>\n",
       "      <th>TENS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEPTH</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2098.5480</th>\n",
       "      <td>12.25</td>\n",
       "      <td>11.8895</td>\n",
       "      <td>2.3994</td>\n",
       "      <td>0.01217</td>\n",
       "      <td>90.5165</td>\n",
       "      <td>77.9562</td>\n",
       "      <td>0.33607</td>\n",
       "      <td>3.0077</td>\n",
       "      <td>1.9421</td>\n",
       "      <td>2000.0000</td>\n",
       "      <td>2.9335</td>\n",
       "      <td>125.9299</td>\n",
       "      <td>66.3632</td>\n",
       "      <td>1034.7947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2098.7004</th>\n",
       "      <td>12.25</td>\n",
       "      <td>11.8797</td>\n",
       "      <td>2.3821</td>\n",
       "      <td>0.00800</td>\n",
       "      <td>90.5101</td>\n",
       "      <td>74.8731</td>\n",
       "      <td>0.33063</td>\n",
       "      <td>2.9777</td>\n",
       "      <td>1.8981</td>\n",
       "      <td>2000.0000</td>\n",
       "      <td>2.7498</td>\n",
       "      <td>125.3827</td>\n",
       "      <td>66.3445</td>\n",
       "      <td>1035.5223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2098.8528</th>\n",
       "      <td>12.25</td>\n",
       "      <td>11.8698</td>\n",
       "      <td>2.3647</td>\n",
       "      <td>0.00383</td>\n",
       "      <td>90.5037</td>\n",
       "      <td>71.7900</td>\n",
       "      <td>0.32519</td>\n",
       "      <td>2.9476</td>\n",
       "      <td>1.8542</td>\n",
       "      <td>2000.0000</td>\n",
       "      <td>2.5661</td>\n",
       "      <td>124.8356</td>\n",
       "      <td>66.3257</td>\n",
       "      <td>1036.2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2099.0052</th>\n",
       "      <td>12.25</td>\n",
       "      <td>11.8603</td>\n",
       "      <td>2.3477</td>\n",
       "      <td>-0.00008</td>\n",
       "      <td>90.5051</td>\n",
       "      <td>68.7355</td>\n",
       "      <td>0.31990</td>\n",
       "      <td>2.9186</td>\n",
       "      <td>1.8103</td>\n",
       "      <td>2000.0000</td>\n",
       "      <td>2.3854</td>\n",
       "      <td>124.3008</td>\n",
       "      <td>66.3062</td>\n",
       "      <td>1036.9747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2099.1576</th>\n",
       "      <td>12.25</td>\n",
       "      <td>11.8590</td>\n",
       "      <td>2.3402</td>\n",
       "      <td>0.00344</td>\n",
       "      <td>90.7292</td>\n",
       "      <td>66.4895</td>\n",
       "      <td>0.31860</td>\n",
       "      <td>2.9193</td>\n",
       "      <td>1.7668</td>\n",
       "      <td>2000.0000</td>\n",
       "      <td>2.2900</td>\n",
       "      <td>124.1156</td>\n",
       "      <td>66.2658</td>\n",
       "      <td>1037.6138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3218.3832</th>\n",
       "      <td>8.50</td>\n",
       "      <td>8.1447</td>\n",
       "      <td>2.4099</td>\n",
       "      <td>-0.00238</td>\n",
       "      <td>72.4421</td>\n",
       "      <td>106.3622</td>\n",
       "      <td>0.19054</td>\n",
       "      <td>2.7925</td>\n",
       "      <td>2.7487</td>\n",
       "      <td>3.0201</td>\n",
       "      <td>3.0564</td>\n",
       "      <td>299.5000</td>\n",
       "      <td>97.6984</td>\n",
       "      <td>1362.6389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3218.5356</th>\n",
       "      <td>8.50</td>\n",
       "      <td>8.1416</td>\n",
       "      <td>2.4130</td>\n",
       "      <td>-0.00271</td>\n",
       "      <td>72.3869</td>\n",
       "      <td>106.3132</td>\n",
       "      <td>0.19196</td>\n",
       "      <td>2.8081</td>\n",
       "      <td>2.7209</td>\n",
       "      <td>3.0166</td>\n",
       "      <td>3.0907</td>\n",
       "      <td>299.5000</td>\n",
       "      <td>97.7140</td>\n",
       "      <td>1357.9783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3218.6880</th>\n",
       "      <td>8.50</td>\n",
       "      <td>8.1435</td>\n",
       "      <td>2.4074</td>\n",
       "      <td>-0.00389</td>\n",
       "      <td>72.1854</td>\n",
       "      <td>106.1410</td>\n",
       "      <td>0.19493</td>\n",
       "      <td>2.8267</td>\n",
       "      <td>2.7027</td>\n",
       "      <td>3.0200</td>\n",
       "      <td>3.1506</td>\n",
       "      <td>299.5000</td>\n",
       "      <td>97.6848</td>\n",
       "      <td>1353.7472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3218.8404</th>\n",
       "      <td>8.50</td>\n",
       "      <td>8.1454</td>\n",
       "      <td>2.4018</td>\n",
       "      <td>-0.00507</td>\n",
       "      <td>71.9840</td>\n",
       "      <td>105.9689</td>\n",
       "      <td>0.19791</td>\n",
       "      <td>2.8453</td>\n",
       "      <td>2.6846</td>\n",
       "      <td>3.0234</td>\n",
       "      <td>3.2105</td>\n",
       "      <td>299.5000</td>\n",
       "      <td>97.6556</td>\n",
       "      <td>1349.5161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3218.9928</th>\n",
       "      <td>8.50</td>\n",
       "      <td>8.1472</td>\n",
       "      <td>2.3962</td>\n",
       "      <td>-0.00626</td>\n",
       "      <td>71.7825</td>\n",
       "      <td>105.7967</td>\n",
       "      <td>0.20088</td>\n",
       "      <td>2.8639</td>\n",
       "      <td>2.6664</td>\n",
       "      <td>3.0267</td>\n",
       "      <td>3.2705</td>\n",
       "      <td>299.5000</td>\n",
       "      <td>97.6264</td>\n",
       "      <td>1345.2850</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7113 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              BS     CALI    DENS     DRHO      DTC        GR     NEUT  \\\n",
       "DEPTH                                                                    \n",
       "2098.5480  12.25  11.8895  2.3994  0.01217  90.5165   77.9562  0.33607   \n",
       "2098.7004  12.25  11.8797  2.3821  0.00800  90.5101   74.8731  0.33063   \n",
       "2098.8528  12.25  11.8698  2.3647  0.00383  90.5037   71.7900  0.32519   \n",
       "2099.0052  12.25  11.8603  2.3477 -0.00008  90.5051   68.7355  0.31990   \n",
       "2099.1576  12.25  11.8590  2.3402  0.00344  90.7292   66.4895  0.31860   \n",
       "...          ...      ...     ...      ...      ...       ...      ...   \n",
       "3218.3832   8.50   8.1447  2.4099 -0.00238  72.4421  106.3622  0.19054   \n",
       "3218.5356   8.50   8.1416  2.4130 -0.00271  72.3869  106.3132  0.19196   \n",
       "3218.6880   8.50   8.1435  2.4074 -0.00389  72.1854  106.1410  0.19493   \n",
       "3218.8404   8.50   8.1454  2.4018 -0.00507  71.9840  105.9689  0.19791   \n",
       "3218.9928   8.50   8.1472  2.3962 -0.00626  71.7825  105.7967  0.20088   \n",
       "\n",
       "              PEF    RESD       RESM    RESS        SP     TEMP       TENS  \n",
       "DEPTH                                                                       \n",
       "2098.5480  3.0077  1.9421  2000.0000  2.9335  125.9299  66.3632  1034.7947  \n",
       "2098.7004  2.9777  1.8981  2000.0000  2.7498  125.3827  66.3445  1035.5223  \n",
       "2098.8528  2.9476  1.8542  2000.0000  2.5661  124.8356  66.3257  1036.2500  \n",
       "2099.0052  2.9186  1.8103  2000.0000  2.3854  124.3008  66.3062  1036.9747  \n",
       "2099.1576  2.9193  1.7668  2000.0000  2.2900  124.1156  66.2658  1037.6138  \n",
       "...           ...     ...        ...     ...       ...      ...        ...  \n",
       "3218.3832  2.7925  2.7487     3.0201  3.0564  299.5000  97.6984  1362.6389  \n",
       "3218.5356  2.8081  2.7209     3.0166  3.0907  299.5000  97.7140  1357.9783  \n",
       "3218.6880  2.8267  2.7027     3.0200  3.1506  299.5000  97.6848  1353.7472  \n",
       "3218.8404  2.8453  2.6846     3.0234  3.2105  299.5000  97.6556  1349.5161  \n",
       "3218.9928  2.8639  2.6664     3.0267  3.2705  299.5000  97.6264  1345.2850  \n",
       "\n",
       "[7113 rows x 14 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The number of rows has reduced from 6701 to 6579."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>BS</th>\n",
       "      <th>CALI</th>\n",
       "      <th>DENS</th>\n",
       "      <th>DRHO</th>\n",
       "      <th>DTC</th>\n",
       "      <th>GR</th>\n",
       "      <th>NEUT</th>\n",
       "      <th>PEF</th>\n",
       "      <th>RESD</th>\n",
       "      <th>RESM</th>\n",
       "      <th>RESS</th>\n",
       "      <th>SP</th>\n",
       "      <th>TEMP</th>\n",
       "      <th>TENS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEPTH</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2098.5480</th>\n",
       "      <td>12.25</td>\n",
       "      <td>11.8895</td>\n",
       "      <td>2.3994</td>\n",
       "      <td>0.01217</td>\n",
       "      <td>90.5165</td>\n",
       "      <td>77.9562</td>\n",
       "      <td>0.33607</td>\n",
       "      <td>3.0077</td>\n",
       "      <td>1.9421</td>\n",
       "      <td>2000.0000</td>\n",
       "      <td>2.9335</td>\n",
       "      <td>125.9299</td>\n",
       "      <td>66.3632</td>\n",
       "      <td>1034.7947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2098.7004</th>\n",
       "      <td>12.25</td>\n",
       "      <td>11.8797</td>\n",
       "      <td>2.3821</td>\n",
       "      <td>0.00800</td>\n",
       "      <td>90.5101</td>\n",
       "      <td>74.8731</td>\n",
       "      <td>0.33063</td>\n",
       "      <td>2.9777</td>\n",
       "      <td>1.8981</td>\n",
       "      <td>2000.0000</td>\n",
       "      <td>2.7498</td>\n",
       "      <td>125.3827</td>\n",
       "      <td>66.3445</td>\n",
       "      <td>1035.5223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2098.8528</th>\n",
       "      <td>12.25</td>\n",
       "      <td>11.8698</td>\n",
       "      <td>2.3647</td>\n",
       "      <td>0.00383</td>\n",
       "      <td>90.5037</td>\n",
       "      <td>71.7900</td>\n",
       "      <td>0.32519</td>\n",
       "      <td>2.9476</td>\n",
       "      <td>1.8542</td>\n",
       "      <td>2000.0000</td>\n",
       "      <td>2.5661</td>\n",
       "      <td>124.8356</td>\n",
       "      <td>66.3257</td>\n",
       "      <td>1036.2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2099.0052</th>\n",
       "      <td>12.25</td>\n",
       "      <td>11.8603</td>\n",
       "      <td>2.3477</td>\n",
       "      <td>-0.00008</td>\n",
       "      <td>90.5051</td>\n",
       "      <td>68.7355</td>\n",
       "      <td>0.31990</td>\n",
       "      <td>2.9186</td>\n",
       "      <td>1.8103</td>\n",
       "      <td>2000.0000</td>\n",
       "      <td>2.3854</td>\n",
       "      <td>124.3008</td>\n",
       "      <td>66.3062</td>\n",
       "      <td>1036.9747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2099.1576</th>\n",
       "      <td>12.25</td>\n",
       "      <td>11.8590</td>\n",
       "      <td>2.3402</td>\n",
       "      <td>0.00344</td>\n",
       "      <td>90.7292</td>\n",
       "      <td>66.4895</td>\n",
       "      <td>0.31860</td>\n",
       "      <td>2.9193</td>\n",
       "      <td>1.7668</td>\n",
       "      <td>2000.0000</td>\n",
       "      <td>2.2900</td>\n",
       "      <td>124.1156</td>\n",
       "      <td>66.2658</td>\n",
       "      <td>1037.6138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3218.3832</th>\n",
       "      <td>8.50</td>\n",
       "      <td>8.1447</td>\n",
       "      <td>2.4099</td>\n",
       "      <td>-0.00238</td>\n",
       "      <td>72.4421</td>\n",
       "      <td>106.3622</td>\n",
       "      <td>0.19054</td>\n",
       "      <td>2.7925</td>\n",
       "      <td>2.7487</td>\n",
       "      <td>3.0201</td>\n",
       "      <td>3.0564</td>\n",
       "      <td>299.5000</td>\n",
       "      <td>97.6984</td>\n",
       "      <td>1362.6389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3218.5356</th>\n",
       "      <td>8.50</td>\n",
       "      <td>8.1416</td>\n",
       "      <td>2.4130</td>\n",
       "      <td>-0.00271</td>\n",
       "      <td>72.3869</td>\n",
       "      <td>106.3132</td>\n",
       "      <td>0.19196</td>\n",
       "      <td>2.8081</td>\n",
       "      <td>2.7209</td>\n",
       "      <td>3.0166</td>\n",
       "      <td>3.0907</td>\n",
       "      <td>299.5000</td>\n",
       "      <td>97.7140</td>\n",
       "      <td>1357.9783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3218.6880</th>\n",
       "      <td>8.50</td>\n",
       "      <td>8.1435</td>\n",
       "      <td>2.4074</td>\n",
       "      <td>-0.00389</td>\n",
       "      <td>72.1854</td>\n",
       "      <td>106.1410</td>\n",
       "      <td>0.19493</td>\n",
       "      <td>2.8267</td>\n",
       "      <td>2.7027</td>\n",
       "      <td>3.0200</td>\n",
       "      <td>3.1506</td>\n",
       "      <td>299.5000</td>\n",
       "      <td>97.6848</td>\n",
       "      <td>1353.7472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3218.8404</th>\n",
       "      <td>8.50</td>\n",
       "      <td>8.1454</td>\n",
       "      <td>2.4018</td>\n",
       "      <td>-0.00507</td>\n",
       "      <td>71.9840</td>\n",
       "      <td>105.9689</td>\n",
       "      <td>0.19791</td>\n",
       "      <td>2.8453</td>\n",
       "      <td>2.6846</td>\n",
       "      <td>3.0234</td>\n",
       "      <td>3.2105</td>\n",
       "      <td>299.5000</td>\n",
       "      <td>97.6556</td>\n",
       "      <td>1349.5161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3218.9928</th>\n",
       "      <td>8.50</td>\n",
       "      <td>8.1472</td>\n",
       "      <td>2.3962</td>\n",
       "      <td>-0.00626</td>\n",
       "      <td>71.7825</td>\n",
       "      <td>105.7967</td>\n",
       "      <td>0.20088</td>\n",
       "      <td>2.8639</td>\n",
       "      <td>2.6664</td>\n",
       "      <td>3.0267</td>\n",
       "      <td>3.2705</td>\n",
       "      <td>299.5000</td>\n",
       "      <td>97.6264</td>\n",
       "      <td>1345.2850</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7113 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              BS     CALI    DENS     DRHO      DTC        GR     NEUT  \\\n",
       "DEPTH                                                                    \n",
       "2098.5480  12.25  11.8895  2.3994  0.01217  90.5165   77.9562  0.33607   \n",
       "2098.7004  12.25  11.8797  2.3821  0.00800  90.5101   74.8731  0.33063   \n",
       "2098.8528  12.25  11.8698  2.3647  0.00383  90.5037   71.7900  0.32519   \n",
       "2099.0052  12.25  11.8603  2.3477 -0.00008  90.5051   68.7355  0.31990   \n",
       "2099.1576  12.25  11.8590  2.3402  0.00344  90.7292   66.4895  0.31860   \n",
       "...          ...      ...     ...      ...      ...       ...      ...   \n",
       "3218.3832   8.50   8.1447  2.4099 -0.00238  72.4421  106.3622  0.19054   \n",
       "3218.5356   8.50   8.1416  2.4130 -0.00271  72.3869  106.3132  0.19196   \n",
       "3218.6880   8.50   8.1435  2.4074 -0.00389  72.1854  106.1410  0.19493   \n",
       "3218.8404   8.50   8.1454  2.4018 -0.00507  71.9840  105.9689  0.19791   \n",
       "3218.9928   8.50   8.1472  2.3962 -0.00626  71.7825  105.7967  0.20088   \n",
       "\n",
       "              PEF    RESD       RESM    RESS        SP     TEMP       TENS  \n",
       "DEPTH                                                                       \n",
       "2098.5480  3.0077  1.9421  2000.0000  2.9335  125.9299  66.3632  1034.7947  \n",
       "2098.7004  2.9777  1.8981  2000.0000  2.7498  125.3827  66.3445  1035.5223  \n",
       "2098.8528  2.9476  1.8542  2000.0000  2.5661  124.8356  66.3257  1036.2500  \n",
       "2099.0052  2.9186  1.8103  2000.0000  2.3854  124.3008  66.3062  1036.9747  \n",
       "2099.1576  2.9193  1.7668  2000.0000  2.2900  124.1156  66.2658  1037.6138  \n",
       "...           ...     ...        ...     ...       ...      ...        ...  \n",
       "3218.3832  2.7925  2.7487     3.0201  3.0564  299.5000  97.6984  1362.6389  \n",
       "3218.5356  2.8081  2.7209     3.0166  3.0907  299.5000  97.7140  1357.9783  \n",
       "3218.6880  2.8267  2.7027     3.0200  3.1506  299.5000  97.6848  1353.7472  \n",
       "3218.8404  2.8453  2.6846     3.0234  3.2105  299.5000  97.6556  1349.5161  \n",
       "3218.9928  2.8639  2.6664     3.0267  3.2705  299.5000  97.6264  1345.2850  \n",
       "\n",
       "[7113 rows x 14 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple Box Plots Using Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that our data has been loaded we can generate our very first boxplot. We can do this by typing `df['GR']` which selects the GR column from the dataframe, followed by `.plot()`. \n",
    "\n",
    "Within the arguments for the plot method, we pass in `kind=box` to tell the function we want a boxplot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Simple boxplot using pandas\n",
    "df['GR'].plot(kind='box');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we run this cell, we get a very basic looking box plot. We have the inter quartile range box, which contains the median line. Extending from either side are the whiskers which extend to 1.5 times the inter quartile range. And then at the top here we have a series of circles, which represent outliers.\n",
    "\n",
    "### Boxplots with Logarithmic Axes\n",
    "\n",
    "We can look at another curve, in this case RDEP (deep resistivity)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Viewing logarithmically scaled data\n",
    "df['DENS'].plot(kind='box');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To solve this we can switch the Y-axis to a logarithmic scale by adding in `plt.semilogy()`. You will see here that we are now using matplotlib notation, and that is because pandas is calling upon matplotlib to build this box plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['DENS'].plot(kind='box')\n",
    "plt.semilogy();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Making Boxplots Horizontal\n",
    "\n",
    "If we prefer to view our boxplots horizontally, we can add in a `vert` argument which is used to tell the plot to appear either vertical (True) or horizontal (False). By default, it is set to True. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Rotating the box plot so it is horizontal\n",
    "df['GR'].plot(kind='box', vert=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Boxplots with Matplotlib\n",
    "\n",
    "The above code cells have been done using the pandas wrapper around matplotlib, if we want to use matplotlib functions and syntax we can generate the same plot as follows. First we call `plt.boxplot()` and then set the x argument to `df['GR']`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Using matplotlib to make a boxplot\n",
    "plt.boxplot(x=df['GR'], vert=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Styling the Boxplot\n",
    "\n",
    "First, we will add some colour to our plot by changing the colour of the outlier circles. To do this we create a new variable called `red_circle` and then we create a dictionary. Within this dictionary, we will set the the `markerfacecolor` and `marker`. These will be set these to red and to a circle respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Changing the outlier markers\n",
    "red_circle = dict(markerfacecolor='red', marker='o')\n",
    "plt.boxplot(x=df['NEUT'], vert=False, flierprops=red_circle);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also add on the mean of our data by creating another dictionary variable called `mean_shape`. \n",
    "\n",
    "We set up the same parameters as before for the `markerfacecolor` and the `marker`, which will both be set to green and a diamond. To choose a diamond, we can use the letter D. \n",
    "\n",
    "Additionally, we will change the edge colour of our mean marker by adding in a `markeredgecolor` variable. By default it is set to black, but here we will set it to green."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Adding the mean\n",
    "red_circle = dict(markerfacecolor='red', marker='o')\n",
    "mean_shape = dict(markerfacecolor='green', marker='D', markeredgecolor='green')\n",
    "\n",
    "plt.boxplot(x=df['NEUT'], vert=False, flierprops=red_circle, \n",
    "             showmeans=True, meanprops=mean_shape);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adding a Notch\n",
    "\n",
    "Instead of representing the median as a line, we can represent it by using a notch instead. This is done by simply by adding the argument `notch` and setting it to True."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Adding the median notch to the box\n",
    "red_circle = dict(markerfacecolor='red', marker='o')\n",
    "plt.boxplot(x=df['DENS'], vert=False, flierprops=red_circle, \n",
    "             showmeans=True, meanprops=mean_shape, notch=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Displaying Multiple Boxplots on a Figure\n",
    "\n",
    "There may be occassions where we want to create multiple boxplots on the same figure. The simplest way is to call `df.plot()`, and pass in `kind=True`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Displaying all columns in the dataframe on a single figure\n",
    "df.plot(kind='box');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This generates a plot with all of our columns, but it is not very appealing. Also, all of our measurements are on different measurement ranges. GR can typically range from 0 to 200 API, whereas DEN typically ranges from about 1.5 g/cc to around 3 g/cc.\n",
    "\n",
    "First we start be defining our outliers as a red underscore circle.\n",
    "\n",
    "```python\n",
    "red_circle = dict(markerfacecolor='red', marker='o', markeredgecolor='white')\n",
    "```\n",
    "\n",
    "We then define fig, axs as plt.subplots. In the arguments we pass in that we want 1 row, and then the number of columns. The number of columns will be equal to the length of df.columns. Finally, we will set the figsize to 20 by 10.\n",
    "\n",
    "```python\n",
    "fig, axs = plt.subplots(1, len(df.columns), figsize=(20,10))\n",
    "```\n",
    "\n",
    "We then need to create a small for loop which will loop over each of our plot axes. We are using the enumerate function here to keep track of i, our index value.\n",
    "\n",
    "```python\n",
    "for i, ax in enumerate(axs.flat):\n",
    "```\n",
    "\n",
    "Next we can add in our boxplot by calling upon `ax.boxplot()` and passing in df.iloc, which allows us to get columns by the index variable, i. We do this by creating square brackets, with a colon followed by a comma. This tells the iloc function to get all rows, and then we pass in the column index. Next we specify our outlier properties and pass in red_circle.\n",
    "\n",
    "```python\n",
    " ax.boxplot(df.iloc[:,i], flierprops=red_circle)\n",
    "```\n",
    "\n",
    "The next couple of lines allows us to set the title and the y tick label font size. At the end we call upon `plt.tight_layout` to space out the plots in a nice way."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 14 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Creating subplot of each column with its own scale\n",
    "red_circle = dict(markerfacecolor='red', marker='o', markeredgecolor='white')\n",
    "\n",
    "fig, axs = plt.subplots(1, len(df.columns), figsize=(20,10))\n",
    "\n",
    "for i, ax in enumerate(axs.flat):\n",
    "    ax.boxplot(df.iloc[:,i], flierprops=red_circle)\n",
    "    ax.set_title(df.columns[i], fontsize=20, fontweight='bold')\n",
    "    ax.tick_params(axis='y', labelsize=14)\n",
    "    \n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And when we run the cell, we have a much nicer looking plot, that we can read. Each subplot has its own y-axis scale. We can see that CALI, GR and NEU all have a large number of outliers. The final two subplots RMED and RDEP should be scaled logarithmically. \n",
    "\n",
    "To catch these, we can add a simple if statement to check if the column names are equal to RDEP and RMED, and then call upon `ax.semilogy()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2160x720 with 14 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "red_circle = dict(markerfacecolor='red', marker='o', markeredgecolor='white')\n",
    "\n",
    "fig, axs = plt.subplots(1, len(df.columns), figsize=(30,10))\n",
    "\n",
    "for i, ax in enumerate(axs.flat):\n",
    "    ax.boxplot(df.iloc[:,i], flierprops=red_circle)\n",
    "    df.iloc[:,i]\n",
    "    ax.set_title(df.columns[i], fontsize=20, fontweight='bold')\n",
    "    ax.tick_params(axis='y', labelsize=14)\n",
    "    \n",
    "    #Checking if column names are equal to columns we expect to be logarithmic\n",
    "    if df.columns[i] == 'RDEP' or df.columns[i] == 'RMED':\n",
    "        ax.semilogy()\n",
    "    \n",
    "plt.tight_layout()"
   ]
  },
  {
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}