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Exploratory Data Analysis with Python
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Exploratory Data Analysis with Python.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Exploratory Data Analysis (EDA) with Python"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is an exploratory data analysis project. In this project, I explore the `Absenteeism time in hours` dataset.\n",
"\n",
"It is categorized into various sections which are listed in table of contents as follows:-\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Table of contents:-\n",
"\n",
"\n",
"1.\tIntroduction to EDA\n",
"2.\tDistribution of a variable\n",
"3.\tTypes of EDA\n",
"4.\tObjectives of EDA\n",
"5.\tExploratory data analysis – prerequisites\n",
"6.\tImport the required Python libraries\n",
"7.\tThe dataset description\n",
"8.\tImport the dataset\n",
"9.\tOverview of the dataset\n",
"10.\tCheck for anomalies in the dataset\n",
"11.\tUnivariate analysis\n",
"12.\tMultivariate analysis\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Introduction to EDA\n",
"\n",
"\n",
"Several questions come to mind when we come across a new dataset. The below list shed light on some of these questions:-\n",
"\n",
"•\tWhat is the distribution of the dataset?\n",
"\n",
"•\tAre there any missing numerical values, outliers or anomalies in the dataset?\n",
"\n",
"•\tWhat are the underlying assumptions in the dataset?\n",
"\n",
"•\tWhether there exists relationships between variables in the dataset?\n",
"\n",
"•\tHow to be sure that our dataset is ready for input in a machine learning algorithm?\n",
"\n",
"•\tHow to select the most suitable algorithm for a given dataset?\n",
"\n",
"So, how do we get answer to the above questions? \n",
"\n",
"\n",
"The answer is **Exploratory Data Analysis**. It enable us to answer all of the above questions.\n",
"\n",
"**Exploratory Data Analysis** or EDA is a critical first step in analyzing a new dataset. The primary objective of EDA is to analyze the data for distribution, outliers and anomalies in the dataset. It enable us to direct specific testing of the hypothesis. It includes analysing the data to find the distribution of data, its main characteristics, identifying patterns and visualizations. It also provides tools for hypothesis generation by visualizing and understanding the data through graphical representation. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Distribution of a variable\n",
"\n",
"There are three types of distribution of a variable. They are **Univariate**, **Bivariate** and **Multivariate** distribution. Variables mean the number of objects that are under consideration as a sample in an experiment. \n",
"\n",
"**Univariate distribution**\n",
"\n",
"In univariate distribution, there is only one variable under consideration. It is the simplest form of analysis because only one quantity changes. It does not deal with causes or relationships. The main purpose of the analysis is to describe the data and find patterns that exist within it. We can describe patterns found in univariate data using central tendency (mean, median and mode) and dispersion (range, variance, standard deviation, maximum and minimum values and interquartile range). We can visualize the univariate data using various types of charts and graphs. These are frequency distribution tables, histograms, bar charts, pie charts and frequency polygons.\n",
"\n",
"\n",
"**Bivariate distribution**\n",
"\n",
"This type of data distribution involves two different variables. The analysis of this type of data deals with causes and relationships and the analysis is done to find out the relationship among the two variables. A very common example of bivariate distribution is height and weight of a single person.\n",
"\n",
"Bivariate analysis means the analysis of bivariate data. It is one of the simplest forms of statistical analysis, used to find out if there is a relationship between two sets of values. Thus bivariate data analysis involves comparisons, exploring relationships, finding causes and explanations. These variables are often plotted on X and Y axis on the graph for better understanding of data and one of these variables is independent while the other is dependent.\n",
"\n",
"Common types of bivariate analysis include drawing scatter plot, regression analysis and finding correlation coefficients. A scatter plot is used to find out if there exists any relationship between two variables. Regression analysis is a statistical method for estimating the relationships between variables. Correlation coefficient analysis measures the strength and direction of a linear relationship between two variables on a scatter plot.\n",
"\n",
"\n",
"**Multivariate distribution**\n",
"\n",
"When the dataset involves three or more variables, it is categorized under multivariate distribution. Multivariate analysis is used to study more complex sets of data. It is usually unsuitable for small sets of data.\n",
"\n",
"There are wide variety of analysis techniques to perform multivariate analysis. The choice of analysis techniques depends on the dataset and our goals to be achieved. Some examples of multivariate analysis techniques are additive tree, cluster analysis, correspondence analysis, factor analysis, MANOVA (multivariate analysis of variance), multidimensional scaling, multiple regression analysis, principal component analysis and redundancy analysis.\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Types of EDA\n",
"\n",
"\n",
"EDA is generally cross-classified in two ways. First, each method is either non-graphical or graphical. Second, each method is either univariate or multivariate (usually bivariate). The non-graphical methods provide insight into the characteristics and the distribution of the variable(s) of interest. So, non-graphical methods involve calculation of summary statistics while graphical methods include summarizing the data diagrammatically.\n",
"\n",
"\n",
"There are four types of exploratory data analysis (EDA) based on the above cross-classification methods. Each of these types of EDA are described below:-\n",
"\n",
"\n",
"### i. Univariate non-graphical EDA\n",
"\n",
"The objective of the univariate non-graphical EDA is to understand the sample distribution and also to make some initial conclusions about population distributions. Outlier detection is also a part of this analysis.\n",
"\n",
"\n",
"### ii. Multivariate non-graphical EDA\n",
"\n",
"Multivariate non-graphical EDA techniques show the relationship between two or more variables in the form of either cross-tabulation or statistics.\n",
"\n",
"\n",
"### iii. Univariate graphical EDA\n",
"\n",
"In addition to finding the various sample statistics of univariate distribution (discussed above), we also look graphically at the distribution of the sample. The non-graphical methods are quantitative and objective. They do not give full picture of the data. Hence, we need graphical methods, which are more qualitative in nature and presents an overview of the data. \n",
"\n",
"\n",
"### iv. Multivariate graphical EDA\n",
"\n",
"There are several useful multivariate graphical EDA techniques, which are used to look at the distribution of multivariate data. These are as follows:-\n",
"\n",
"Side-by-Side Boxplots\n",
"\n",
"Scatterplots\n",
"\n",
"Curve Fitting\n",
"\n",
"Heat Maps and 3-D Surface Plots\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4. Objectives of EDA\n",
"\n",
"\n",
"The objectives of the EDA are as follows:-\n",
"\n",
"i.\tTo get an overview of the distribution of the dataset.\n",
"\n",
"ii.\tCheck for missing numerical values, outliers or other anomalies in the dataset.\n",
"\n",
"iii.Discover patterns and relationships between variables in the dataset.\n",
"\n",
"iv.\tCheck the underlying assumptions in the dataset.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5. Exploratory data analysis - prerequisites\n",
"\n",
"\n",
"We need two Python libraries for exploratory data analysis – **NumPy** and **Pandas**.\n",
"\n",
"\n",
"•\t**NumPy** – NumPy is the fundamental Python library for scientific computing. It adds support for large and multi-dimensional arrays and matrices. It also supports large collection of high-level mathematical functions to operate on these arrays.\n",
"\n",
"\n",
"•\t**Pandas** - Pandas is a software library for Python programming language which provide tools for data manipulation and analysis tasks. It will enable us to manipulate numerical tables and time series using data structures and operations.\n",
"\n",
"\n",
"We need two more libraries for data visualization purpose. These are **Seaborn** and **Matplotlib**.\n",
"\n",
"\n",
"•\t**Seaborn** - Seaborn is a Python data visualization library based on Matplotlib. It provides a high level interface for drawing attractive and informative statistical graphics.\n",
"\n",
"\n",
"•\t**Matplotlib** - Matplotlib is the core data visualization library of Python programming language. It provides an object-oriented API for embedding plots into applications.\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 6. Import the required Python libraries\n",
"\n",
"\n",
"We have seen that we need two Python libraries – **NumPy** and **Pandas** for the exploratory data analysis process. \n",
"Also, we need two more libraries – **Seaborn** and **Matplotlib** for data visualization purposes. \n",
"\n",
"\n",
"We need to import these libraries before we actually start using them. We can import them with their usual shorthand notation as follows:-\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# ignore the warnings\n",
"\n",
"import warnings\n",
"warnings.simplefilter(action = \"ignore\", category = FutureWarning)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"import scipy.stats as st\n",
"%matplotlib inline\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"sns.set(style=\"whitegrid\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 7. The dataset description\n",
"\n",
"For this project, I have used the Absenteeism at work dataset. This dataset can be found at the following url-\n",
"\n",
"https://archive.ics.uci.edu/ml/datasets/Absenteeism+at+work\n",
"\n",
"The dataset consists of records of absenteeism at work from July 2007 to July 2010 at a courier company in Brazil. The dataset contains 740 number of instances and 21 number of attributes.\n",
"It was created by Andrea Martiniano, Ricardo Pinto Ferreira and Renato Jose Sassi.\n",
"\n",
"Attribute information in the dataset is as follows:-\n",
"\n",
"1.\tID – represents individual identification ID\n",
"2.\tReason for absence (ICD) – \n",
"Absences attested by the International Code of Diseases (ICD) stratified into 21 categories (I to XXI) as follows: \n",
"\n",
"I Certain infectious and parasitic diseases\n",
"\n",
"II Neoplasms \n",
"\n",
"III Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism \n",
"\n",
"IV Endocrine, nutritional and metabolic diseases \n",
"\n",
"V Mental and behavioural disorders \n",
"\n",
"VI Diseases of the nervous system\n",
"\n",
"VII Diseases of the eye and adnexa\n",
"\n",
"VIII Diseases of the ear and mastoid process \n",
"\n",
"IX Diseases of the circulatory system \n",
"\n",
"X Diseases of the respiratory system\n",
"\n",
"XI Diseases of the digestive system\n",
"\n",
"XII Diseases of the skin and subcutaneous tissue \n",
"\n",
"XIII Diseases of the musculoskeletal system and connective tissue\n",
"\n",
"XIV Diseases of the genitourinary system\n",
"\n",
"XV Pregnancy, childbirth and the puerperium\n",
"\n",
"XVI Certain conditions originating in the perinatal period\n",
"\n",
"XVII Congenital malformations, deformations and chromosomal abnormalities\n",
"\n",
"XVIII Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified\n",
"\n",
"XIX Injury, poisoning and certain other consequences of external causes\n",
"\n",
"XX External causes of morbidity and mortality \n",
"\n",
"XXI Factors influencing health status and contact with health services. \n",
"\n",
"And 7 categories without (CID) patient follow-up (22), medical consultation (23), blood donation (24), laboratory examination (25), unjustified absence (26), physiotherapy (27), dental consultation (28).\n",
"\n",
"3.\tMonth of absence \n",
"4. Day of the week (Monday (2), Tuesday (3), Wednesday (4), Thursday (5), Friday (6)) \n",
"5. Seasons (summer (1), autumn (2), winter (3), spring (4)) \n",
"6. Transportation expense \n",
"7. Distance from Residence to Work (kilometers) \n",
"8. Service time \n",
"9. Age \n",
"10. Work load Average/day \n",
"11. Hit target \n",
"12. Disciplinary failure (yes=1; no=0) \n",
"13. Education (high school (1), graduate (2), postgraduate (3), master and doctor (4)) \n",
"14. Son (number of children) \n",
"15. Social drinker (yes=1; no=0) \n",
"16. Social smoker (yes=1; no=0) \n",
"17. Pet (number of pet) \n",
"18. Weight \n",
"19. Height \n",
"20. Body mass index \n",
"21. Absenteeism time in hours (target) \n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 8. Import the dataset\n",
"\n",
"We can import the dataset using the usual **read_csv()** function as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"data = \"C:/eda/Absenteeism_at_work.csv\"\n",
"\n",
"df = pd.read_csv(data, sep=\";\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Generally, in the csv file the values are separated by a comma. So, there is no need to use the sep parameter which describes how the values are separated. In this case, the values are separated by semicolon (;). So, I used the **sep = \";\"** parameter to denote that the values are separated by semicolon. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 9. Overview of the dataset\n",
"\n",
"\n",
"Now, we should get to know our data. We should know its dimensions, structure and column data types. \n",
"\n",
"We can proceed as follows:-"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### df.shape attribute\n",
"\n",
"\n",
"The first thing that I do is to check the dimensions of the dataset. We can check the dimensions of the data with \n",
"**df.shape** attribute as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(740, 21)\n"
]
}
],
"source": [
"print(df.shape)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Interpretation**\n",
"\n",
"We can see that our dataset has 740 rows and 21 columns."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### df.columns attribute\n",
"\n",
"I can view the column names in the dataset with **df.columns** attribute as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Index(['ID', 'Reason for absence', 'Month of absence', 'Day of the week',\n",
" 'Seasons', 'Transportation expense', 'Distance from Residence to Work',\n",
" 'Service time', 'Age', 'Work load Average/day ', 'Hit target',\n",
" 'Disciplinary failure', 'Education', 'Son', 'Social drinker',\n",
" 'Social smoker', 'Pet', 'Weight', 'Height', 'Body mass index',\n",
" 'Absenteeism time in hours'],\n",
" dtype='object')\n"
]
}
],
"source": [
"print(df.columns)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### df.head() and df.tail() methods\n",
"\n",
"Now, it is time to get an overview of the dataset. We can view the top five and bottom five rows of the dataset with **df.head()** and **df.tail()** methods respectively.\n",
"\n",
"So, we proceed as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
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"text/plain": [
" ID Reason for absence Month of absence Day of the week Seasons \\\n",
"0 11 26 7 3 1 \n",
"1 36 0 7 3 1 \n",
"2 3 23 7 4 1 \n",
"3 7 7 7 5 1 \n",
"4 11 23 7 5 1 \n",
"\n",
" Transportation expense Distance from Residence to Work Service time Age \\\n",
"0 289 36 13 33 \n",
"1 118 13 18 50 \n",
"2 179 51 18 38 \n",
"3 279 5 14 39 \n",
"4 289 36 13 33 \n",
"\n",
" Work load Average/day ... Disciplinary failure \\\n",
"0 239.554 ... 0 \n",
"1 239.554 ... 1 \n",
"2 239.554 ... 0 \n",
"3 239.554 ... 0 \n",
"4 239.554 ... 0 \n",
"\n",
" Education Son Social drinker Social smoker Pet Weight Height \\\n",
"0 1 2 1 0 1 90 172 \n",
"1 1 1 1 0 0 98 178 \n",
"2 1 0 1 0 0 89 170 \n",
"3 1 2 1 1 0 68 168 \n",
"4 1 2 1 0 1 90 172 \n",
"\n",
" Body mass index Absenteeism time in hours \n",
"0 30 4 \n",
"1 31 0 \n",
"2 31 2 \n",
"3 24 4 \n",
"4 30 2 \n",
"\n",
"[5 rows x 21 columns]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
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" <th>Pet</th>\n",
" <th>Weight</th>\n",
" <th>Height</th>\n",
" <th>Body mass index</th>\n",
" <th>Absenteeism time in hours</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>735</th>\n",
" <td>11</td>\n",
" <td>14</td>\n",
" <td>7</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>289</td>\n",
" <td>36</td>\n",
" <td>13</td>\n",
" <td>33</td>\n",
" <td>264.604</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>90</td>\n",
" <td>172</td>\n",
" <td>30</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>736</th>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" <td>7</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>235</td>\n",
" <td>11</td>\n",
" <td>14</td>\n",
" <td>37</td>\n",
" <td>264.604</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>88</td>\n",
" <td>172</td>\n",
" <td>29</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>737</th>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>118</td>\n",
" <td>14</td>\n",
" <td>13</td>\n",
" <td>40</td>\n",
" <td>271.219</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>8</td>\n",
" <td>98</td>\n",
" <td>170</td>\n",
" <td>34</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>738</th>\n",
" <td>8</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" <td>231</td>\n",
" <td>35</td>\n",
" <td>14</td>\n",
" <td>39</td>\n",
" <td>271.219</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>100</td>\n",
" <td>170</td>\n",
" <td>35</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>739</th>\n",
" <td>35</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>3</td>\n",
" <td>179</td>\n",
" <td>45</td>\n",
" <td>14</td>\n",
" <td>53</td>\n",
" <td>271.219</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>77</td>\n",
" <td>175</td>\n",
" <td>25</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 21 columns</p>\n",
"</div>"
],
"text/plain": [
" ID Reason for absence Month of absence Day of the week Seasons \\\n",
"735 11 14 7 3 1 \n",
"736 1 11 7 3 1 \n",
"737 4 0 0 3 1 \n",
"738 8 0 0 4 2 \n",
"739 35 0 0 6 3 \n",
"\n",
" Transportation expense Distance from Residence to Work Service time \\\n",
"735 289 36 13 \n",
"736 235 11 14 \n",
"737 118 14 13 \n",
"738 231 35 14 \n",
"739 179 45 14 \n",
"\n",
" Age Work load Average/day ... \\\n",
"735 33 264.604 ... \n",
"736 37 264.604 ... \n",
"737 40 271.219 ... \n",
"738 39 271.219 ... \n",
"739 53 271.219 ... \n",
"\n",
" Disciplinary failure Education Son Social drinker Social smoker Pet \\\n",
"735 0 1 2 1 0 1 \n",
"736 0 3 1 0 0 1 \n",
"737 0 1 1 1 0 8 \n",
"738 0 1 2 1 0 2 \n",
"739 0 1 1 0 0 1 \n",
"\n",
" Weight Height Body mass index Absenteeism time in hours \n",
"735 90 172 30 8 \n",
"736 88 172 29 4 \n",
"737 98 170 34 0 \n",
"738 100 170 35 0 \n",
"739 77 175 25 0 \n",
"\n",
"[5 rows x 21 columns]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.tail()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### df.info() method\n",
"\n",
"We can get a concise summary of the dataset with **df.info()** method. This method prints information about a dataFrame including the index, column names and data types, non-null values and memory usage.\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 740 entries, 0 to 739\n",
"Data columns (total 21 columns):\n",
"ID 740 non-null int64\n",
"Reason for absence 740 non-null int64\n",
"Month of absence 740 non-null int64\n",
"Day of the week 740 non-null int64\n",
"Seasons 740 non-null int64\n",
"Transportation expense 740 non-null int64\n",
"Distance from Residence to Work 740 non-null int64\n",
"Service time 740 non-null int64\n",
"Age 740 non-null int64\n",
"Work load Average/day 740 non-null float64\n",
"Hit target 740 non-null int64\n",
"Disciplinary failure 740 non-null int64\n",
"Education 740 non-null int64\n",
"Son 740 non-null int64\n",
"Social drinker 740 non-null int64\n",
"Social smoker 740 non-null int64\n",
"Pet 740 non-null int64\n",
"Weight 740 non-null int64\n",
"Height 740 non-null int64\n",
"Body mass index 740 non-null int64\n",
"Absenteeism time in hours 740 non-null int64\n",
"dtypes: float64(1), int64(20)\n",
"memory usage: 121.5 KB\n"
]
}
],
"source": [
"df.info()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Interpretation**\n",
"\n",
"We can see that this method prints information about all columns. There are no missing values in the dataset. We need to \n",
"confirm this further.\n",
"\n",
"The data types of several columns like \"Month of absence\", \"Transportation expense\", \"Distance from Residence to work\", \"Hit target\", \"Education\", \"Weight\", \"Height\", \"Body mass index\" and \"Absenteeism time in hours\" should be real or float. But, the above cell shows that they have integer data types. So, we need to convert their data types into float.\n",
"\n",
"We can do it as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"df[[\"Month of absence\",\"Transportation expense\",\"Distance from Residence to Work\", \"Hit target\",\"Education\",\"Weight\",\"Height\",\n",
"\"Body mass index\",\"Absenteeism time in hours\"]]=df[[\"Month of absence\",\"Transportation expense\",\"Distance from Residence to Work\",\n",
"\"Hit target\",\"Education\",\"Weight\",\"Height\",\"Body mass index\",\"Absenteeism time in hours\"]].astype(float)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We should again check the data types of modified columns."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 740 entries, 0 to 739\n",
"Data columns (total 21 columns):\n",
"ID 740 non-null int64\n",
"Reason for absence 740 non-null int64\n",
"Month of absence 740 non-null float64\n",
"Day of the week 740 non-null int64\n",
"Seasons 740 non-null int64\n",
"Transportation expense 740 non-null float64\n",
"Distance from Residence to Work 740 non-null float64\n",
"Service time 740 non-null int64\n",
"Age 740 non-null int64\n",
"Work load Average/day 740 non-null float64\n",
"Hit target 740 non-null float64\n",
"Disciplinary failure 740 non-null int64\n",
"Education 740 non-null float64\n",
"Son 740 non-null int64\n",
"Social drinker 740 non-null int64\n",
"Social smoker 740 non-null int64\n",
"Pet 740 non-null int64\n",
"Weight 740 non-null float64\n",
"Height 740 non-null float64\n",
"Body mass index 740 non-null float64\n",
"Absenteeism time in hours 740 non-null float64\n",
"dtypes: float64(10), int64(11)\n",
"memory usage: 121.5 KB\n"
]
}
],
"source": [
"df.info()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Interpretation**\n",
"\n",
"We can see that the data types of modified columns are float64. Now, all the columns are appropriate data types.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### drop redundant columns\n",
"\n",
"\n",
"There are two columns `ID` and `Pet` which have no correlation with the target variable `Absenteeism time in hours`. So, we should drop these columns. We can do it as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"df.drop(['ID','Pet'], axis = 1, inplace=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### df.describe() method\n",
"\n",
"We can view the summary statistics of numerical columns with **df.describe()** method. It enable us to detect outliers \n",
"in the data which require further investigation.\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reason for absence Month of absence Day of the week Seasons \\\n",
"count 740.000000 740.000000 740.000000 740.000000 \n",
"mean 19.216216 6.324324 3.914865 2.544595 \n",
"std 8.433406 3.436287 1.421675 1.111831 \n",
"min 0.000000 0.000000 2.000000 1.000000 \n",
"25% 13.000000 3.000000 3.000000 2.000000 \n",
"50% 23.000000 6.000000 4.000000 3.000000 \n",
"75% 26.000000 9.000000 5.000000 4.000000 \n",
"max 28.000000 12.000000 6.000000 4.000000 \n",
"\n",
" Transportation expense Distance from Residence to Work Service time \\\n",
"count 740.000000 740.000000 740.000000 \n",
"mean 221.329730 29.631081 12.554054 \n",
"std 66.952223 14.836788 4.384873 \n",
"min 118.000000 5.000000 1.000000 \n",
"25% 179.000000 16.000000 9.000000 \n",
"50% 225.000000 26.000000 13.000000 \n",
"75% 260.000000 50.000000 16.000000 \n",
"max 388.000000 52.000000 29.000000 \n",
"\n",
" Age Work load Average/day Hit target Disciplinary failure \\\n",
"count 740.000000 740.000000 740.000000 740.000000 \n",
"mean 36.450000 271.490235 94.587838 0.054054 \n",
"std 6.478772 39.058116 3.779313 0.226277 \n",
"min 27.000000 205.917000 81.000000 0.000000 \n",
"25% 31.000000 244.387000 93.000000 0.000000 \n",
"50% 37.000000 264.249000 95.000000 0.000000 \n",
"75% 40.000000 294.217000 97.000000 0.000000 \n",
"max 58.000000 378.884000 100.000000 1.000000 \n",
"\n",
" Education Son Social drinker Social smoker Weight \\\n",
"count 740.000000 740.000000 740.000000 740.000000 740.000000 \n",
"mean 1.291892 1.018919 0.567568 0.072973 79.035135 \n",
"std 0.673238 1.098489 0.495749 0.260268 12.883211 \n",
"min 1.000000 0.000000 0.000000 0.000000 56.000000 \n",
"25% 1.000000 0.000000 0.000000 0.000000 69.000000 \n",
"50% 1.000000 1.000000 1.000000 0.000000 83.000000 \n",
"75% 1.000000 2.000000 1.000000 0.000000 89.000000 \n",
"max 4.000000 4.000000 1.000000 1.000000 108.000000 \n",
"\n",
" Height Body mass index Absenteeism time in hours \n",
"count 740.000000 740.000000 740.000000 \n",
"mean 172.114865 26.677027 6.924324 \n",
"std 6.034995 4.285452 13.330998 \n",
"min 163.000000 19.000000 0.000000 \n",
"25% 169.000000 24.000000 2.000000 \n",
"50% 170.000000 25.000000 3.000000 \n",
"75% 172.000000 31.000000 8.000000 \n",
"max 196.000000 38.000000 120.000000 \n"
]
}
],
"source": [
"print(df.describe())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Interpretation**\n",
"\n",
"We can see that the minimum value of **Month of absence** is zero. It cannot be zero. The minimum value should be one. So, we need to replace zero by one. We can do it as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"df['Month of absence'].replace(0,1,inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reason for absence Month of absence Day of the week Seasons \\\n",
"count 740.000000 740.000000 740.000000 740.000000 \n",
"mean 19.216216 6.328378 3.914865 2.544595 \n",
"std 8.433406 3.429397 1.421675 1.111831 \n",
"min 0.000000 1.000000 2.000000 1.000000 \n",
"25% 13.000000 3.000000 3.000000 2.000000 \n",
"50% 23.000000 6.000000 4.000000 3.000000 \n",
"75% 26.000000 9.000000 5.000000 4.000000 \n",
"max 28.000000 12.000000 6.000000 4.000000 \n",
"\n",
" Transportation expense Distance from Residence to Work Service time \\\n",
"count 740.000000 740.000000 740.000000 \n",
"mean 221.329730 29.631081 12.554054 \n",
"std 66.952223 14.836788 4.384873 \n",
"min 118.000000 5.000000 1.000000 \n",
"25% 179.000000 16.000000 9.000000 \n",
"50% 225.000000 26.000000 13.000000 \n",
"75% 260.000000 50.000000 16.000000 \n",
"max 388.000000 52.000000 29.000000 \n",
"\n",
" Age Work load Average/day Hit target Disciplinary failure \\\n",
"count 740.000000 740.000000 740.000000 740.000000 \n",
"mean 36.450000 271.490235 94.587838 0.054054 \n",
"std 6.478772 39.058116 3.779313 0.226277 \n",
"min 27.000000 205.917000 81.000000 0.000000 \n",
"25% 31.000000 244.387000 93.000000 0.000000 \n",
"50% 37.000000 264.249000 95.000000 0.000000 \n",
"75% 40.000000 294.217000 97.000000 0.000000 \n",
"max 58.000000 378.884000 100.000000 1.000000 \n",
"\n",
" Education Son Social drinker Social smoker Weight \\\n",
"count 740.000000 740.000000 740.000000 740.000000 740.000000 \n",
"mean 1.291892 1.018919 0.567568 0.072973 79.035135 \n",
"std 0.673238 1.098489 0.495749 0.260268 12.883211 \n",
"min 1.000000 0.000000 0.000000 0.000000 56.000000 \n",
"25% 1.000000 0.000000 0.000000 0.000000 69.000000 \n",
"50% 1.000000 1.000000 1.000000 0.000000 83.000000 \n",
"75% 1.000000 2.000000 1.000000 0.000000 89.000000 \n",
"max 4.000000 4.000000 1.000000 1.000000 108.000000 \n",
"\n",
" Height Body mass index Absenteeism time in hours \n",
"count 740.000000 740.000000 740.000000 \n",
"mean 172.114865 26.677027 6.924324 \n",
"std 6.034995 4.285452 13.330998 \n",
"min 163.000000 19.000000 0.000000 \n",
"25% 169.000000 24.000000 2.000000 \n",
"50% 170.000000 25.000000 3.000000 \n",
"75% 172.000000 31.000000 8.000000 \n",
"max 196.000000 38.000000 120.000000 \n"
]
}
],
"source": [
"print(df.describe())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, the **Month of absence** column has minimum value one. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 10. Check for anomalies in the dataset\n",
"\n",
"\n",
"Now, we should check for any discrepancy in the dataset. \n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Check for missing numerical values\n",
"\n",
"\n",
"The first step is to check for any missing values in the dataset. We can check for missing values in the dataset using\n",
"the `df.isnull().sum()` command. This command returns the total number of missing values in each column in the dataset.\n",
"\n",
"\n",
"If we want to check for 'NA' values in a particular column in the dataframe, then we should use the following command\n",
"`pd.isna(df['col_name'])`.\n",
"\n",
"We can proceed as follows:-\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Reason for absence 0\n",
"Month of absence 0\n",
"Day of the week 0\n",
"Seasons 0\n",
"Transportation expense 0\n",
"Distance from Residence to Work 0\n",
"Service time 0\n",
"Age 0\n",
"Work load Average/day 0\n",
"Hit target 0\n",
"Disciplinary failure 0\n",
"Education 0\n",
"Son 0\n",
"Social drinker 0\n",
"Social smoker 0\n",
"Weight 0\n",
"Height 0\n",
"Body mass index 0\n",
"Absenteeism time in hours 0\n",
"dtype: int64"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.isnull().sum()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Interpretation**\n",
"\n",
"The above command shows that there are no missing values in the dataset. \n",
"\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Check with ASSERT statement\n",
"\n",
"We should confirm that our dataset has no missing values. We can write an **assert statement** to verify this. We can use an **assert statement** to programmatically check that no missing, unexpected 0 or negative values are present. This gives us confidence that our code is running properly.\n",
"\n",
"\n",
"Assert statement will return nothing if the value being tested is true and will throw an AssertionError if the value is false.\n",
"\n",
"Asserts\n",
"\n",
"•\tassert 1 == 1 (return Nothing if the value is True)\n",
"\n",
"•\tassert 1 == 2 (return AssertionError if the value is False)\n"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"#assert that there are no missing values in the dataframe\n",
"\n",
"assert pd.notnull(df).all().all()\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"#assert all values are greater than or equal to 0\n",
"\n",
"assert (df >= 0).all().all()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Interpretation**\n",
"\n",
"The above two commands do not throw any error. Hence, it is confirmed that there are no missing or negative values in the dataset. All the values are greater than or equal to zero."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 11. Univariate analysis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Measures of central tendency and dispersion\n",
"\n",
"\n",
"**Central tendency** means a central value which describe a probability distribution. It may also be called a center or location of the distribution. The most common measures of central tendency are the arithmetic mean, the median and the mode. The most common measure of central tendency is the mean. For skewed distribution or when there is concern about outliers, the median\n",
"may be preferred. So, median is more robust measure than the mean.\n",
"\n",
"**Dispersion** is an indicator of how far away from the center, we can find the data values. The most common measures of dispersion are variance, standard deviation and interquartile range(IQR). Variance is the standard measure of spread. The \n",
"standard deviation is the square root of the variance. The variance and standard deviation are two useful measures of\n",
"spread. \n",
"\n",
"A third measure of spread is the interquartile range (IQR). The IQR is calculated using the boundaries of data situated between the 1st and the 3rd quartiles. So, IQR can be calculated as IQR = Q3 - Q1. It is a robust measure of spread."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The above measures can be calculated by `df.describe()` method as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"count 740.000000\n",
"mean 6.924324\n",
"std 13.330998\n",
"min 0.000000\n",
"25% 2.000000\n",
"50% 3.000000\n",
"75% 8.000000\n",
"max 120.000000\n",
"Name: Absenteeism time in hours, dtype: float64\n"
]
}
],
"source": [
"print(df['Absenteeism time in hours'].describe())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Interpretation**\n",
"\n",
"The count, min and max values represent the number of counts, minimum and maximum values of the target variable `Absenteeism time in hours`. \n",
"\n",
"The measures of central tendency are given by the mean(6.924324) and median(50% value-3.00). \n",
"\n",
"The measure of dispersion is given by the standard deviation given by std(13.330998).\n",
"\n",
"The 25%, 50% and 75% values show the corresponding percentiles. 50th percentile denote the median of the distribution.\n",
"\n",
"The IQR is the difference between 75th and 25th percentiles. Hence, IQR = 8.00 - 2.00 = 6.00"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Measures of shape\n",
"\n",
"\n",
"We have looked at the measures of central tendency of the data (mean and median) and spread of the data (standard deviation(std), interquartile range, minimum (min) and maximum (max) values. These quantities can only be used for quantitative \n",
"variables not for categorical variables.\n",
"\n",
"Now, we will take a look at measures of shape of distribution. There are two statistical measures that can tell us about the shape of the distribution. These measures are **skewness** and **kurtosis**. These measures can be used to convey information about the shape of the distribution of the dataset.\n",
"\n",
"First, we will look at skewness and later we get to know about kurtosis."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Skewness\n",
"\n",
"\n",
"Skewness is a measure of a distribution's symmetry or more precisely lack of symmetry. It is used to mean the absence of symmetry from the mean of the dataset. It is a characteristic of the deviation from the mean. It is used to indicate the \n",
"shape of the distribution of data.\n",
"\n",
"\n",
"\n",
"### Negative skewness\n",
"\n",
"Negative values for skewness indicate negative skewness. In this case, the data are skewed or tail to left. By skewed left, \n",
"we mean that the left tail is long relative to the right tail. The data values may extend further to the left but concentrated\n",
"in the right. So, there is a long tail and distortion is caused by extremely small values which pull the mean downward so that it is less than the median. Hence, in this case\n",
"\n",
"**Mean < Median < Mode**\n",
"\n",
"\n",
"\n",
"### Zero skewness\n",
"\n",
"Zero skewness means skewness value of zero. It means the dataset is symmetrical. A data set is symmetrical if it looks the \n",
"same to the left and right to the center point. The dataset looks bell shaped or symmetrical. A perfectly symmetrical data set will have a skewness of zero. So, the normal distribution which is perfectly symmetrical has a skewness of 0. So, in this case\n",
"\n",
"**Mean = Median = Mode**\n",
"\n",
"\n",
"\n",
"### Positive skewness\n",
"\n",
"Positive values for skewness indicate positive skewness. The dataset are skewed or tail to right. By skewed right, we mean that the right tail is long relative to the left tail. The data values are concentrated in the right. So, there is a long tail to the \n",
"right that is caused by extremely large values which pull the mean upward so that it is greater than the median. So, we have\n",
"\n",
"**Mean > Median > Mode**\n",
"\n",
"\n",
"\n",
"### Reference range on skewness values\n",
"\n",
"The rule of thumb for skewness values are:\n",
"\n",
"If the skewness is between -0.5 and 0.5, the data are fairly symmetrical.\n",
"\n",
"If the skewness is between -1 and – 0.5 or between 0.5 and 1, the data are moderately skewed.\n",
"\n",
"If the skewness is less than -1 or greater than 1, the data are highly skewed.\n",
"\n",
"\n",
"We can proceed as follows:-\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5.720727863123873"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['Absenteeism time in hours'].skew()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Interpretation of skewness**\n",
"\n",
"The skewness of our target variable `Absenteeism time in hours` comes out to be greater than +1. So, we can conclude that the \n",
"target variable is highly positively skewed. \n",
"\n",
"We can confirm this by plotting a Seaborn distplot diagram as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize= (10,8))\n",
"sns.distplot(df[\"Absenteeism time in hours\"])\n",
"plt.title(\"Distribution of Absenteeism time in hours\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"The above plot confirms that the target variable `Absenteeism time in hours` is highly positively skewed."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Kurtosis\n",
"\n",
"Kurtosis is the degree of peakedness of a distribution. \n",
"\n",
"Data sets with high kurtosis tend to have a distinct peak near the mean, decline rather rapidly and have heavy tails.\n",
"\n",
"Data sets with low kurtosis tend to have a flat top near the mean rather than a sharp peak. \n",
"\n",
"\n",
"### Reference range for kurtosis\n",
"\n",
"The reference standard is a normal distribution, which has a kurtosis of 3. Often, **excess kurtosis** is presented instead of kurtosis, where **excess kurtosis** is simply **kurtosis - 3**. \n",
"\n",
"\n",
"**Mesokurtic curve**\n",
"\n",
"A normal distribution has kurtosis exactly 3 (**excess kurtosis** exactly 0). Any distribution with kurtosis ≈3 (excess ≈ 0) is called **mesokurtic**.\n",
"\n",
"\n",
"**Platykurtic curve**\n",
"\n",
"A distribution with kurtosis < 3 (**excess kurtosis** < 0) is called **platykurtic**. As compared to a normal distribution, its \n",
"central peak is lower and broader, and its tails are shorter and thinner.\n",
"\n",
"\n",
"**Leptokurtic curve**\n",
"\n",
"A distribution with kurtosis > 3 (**excess kurtosis** > 0) is called **leptokurtic**. As compared to a normal distribution, its central peak is higher and sharper, and its tails are longer and fatter.\n",
"\n",
"\n",
"We can calculate kurtosis as follows:-\n"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"38.77730707753998"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['Absenteeism time in hours'].kurt()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"The kurtosis value of the `Absenteeism time in hours` is much much greater than 3. So, we can conclude that the distribution \n",
"curve is a **Leptokurtic curve**. Its central peak is higher and sharper and its tails are longer and fatter.\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Distribution of target variable\n",
"\n",
"\n",
"Now, we should plot the distribution of target variable. We can use Seaborn's **distplot()** function to plot the distribution.\n",
"\n",
"First, I will draw the plot using **distplot()** function. This function plot a univariate distribution of observations. \n",
"This function combines the matplotlib **hist()** function with the seaborn **kdeplot()** function.\n",
"\n",
"We can proceed as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"y = df['Absenteeism time in hours']"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x432 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(8,6))\n",
"sns.distplot(y, kde=False, fit=st.norm)\n",
"plt.title('Normal fit')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can see that the data values do not fit the normal distribution well. So, I will change the fit to lognormal distribution."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x432 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(8,6))\n",
"sns.distplot(y, kde=False, fit=st.lognorm)\n",
"plt.title('Log Normal fit')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"We can see that the `Absenteeism time in hours` data values follow the lognormal distribution relatively closely as compared to normal distribution."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Findings of univariate analysis\n",
"\n",
"\n",
"Findings of univariate analysis are as follows:-\n",
"\n",
"\n",
"•\tThe target variable `Absenteeism time in hours` is highly positively skewed.\n",
"\n",
"•\tIts distribution curve is a **Leptokurtic curve**. Its central peak is higher and sharper and its tails are longer and fatter.\n",
"\n",
"•\tThe `Absenteeism time in hours` data values follow the lognormal distribution relatively closely as compared to normal distribution.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 12. Multivariate analysis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Examine relationship between target variable and categorical attributes\n",
"\n",
"\n",
"In the dataset, we have several categorical attributes like `Seasons`, `Education`, `Social drinker` and `Social smoker`. \n",
"In this section, I will explore the relationship between these categorical attributes and target variable."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Frequency distribution and visualization of categorical attributes\n",
"\n",
"`Seasons` is a categorical attribute. We can find out what categories exist and how many values belong to each category using the `value_counts()` method as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4 195\n",
"2 192\n",
"3 183\n",
"1 170\n",
"Name: Seasons, dtype: int64"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['Seasons'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df['Seasons'].value_counts().plot(kind = 'bar', figsize=(10,5))\n",
"plt.title('Absenteeism time in hours in various seasons')\n",
"plt.xlabel('Seasons')\n",
"plt.ylabel('Absenteeism time in hours')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"`Seasons` attribute contain 4 data values as 1, 2, 3 and 4. These values represent 4 different seasons in a year which are coded as summer = 1, autumn = 2, winter = 3, spring = 4. So, we can conclude that spring contains highest number of `Absenteeism time in hours`.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Similarly, `Education`, `Social drinker` and `Social smoker` are also categorical attributes. We can visualize their frequency distribution using the value_counts() method and visualize them as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1.0 611\n",
"3.0 79\n",
"2.0 46\n",
"4.0 4\n",
"Name: Education, dtype: int64"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['Education'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df['Education'].value_counts().plot(kind = 'bar', figsize=(10,5))\n",
"plt.title('Absenteeism time in hours in various seasons')\n",
"plt.xlabel('Education')\n",
"plt.ylabel('Absenteeism time in hours')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"Education categorical attribute is coded as 1.0, 2.0, 3.0 and 4.0 which stands for different categories. The categories are \n",
"high school (1), graduate (2), postgraduate (3), master and doctor (4). We can see that the high school category consists of highest number of `Absenteeism time in hours`."
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1 420\n",
"0 320\n",
"Name: Social drinker, dtype: int64"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['Social drinker'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df['Social drinker'].value_counts().plot(kind = 'bar', figsize=(10,5))\n",
"plt.title('Absenteeism time in hours in various seasons')\n",
"plt.xlabel('Social drinker')\n",
"plt.ylabel('Absenteeism time in hours')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"Social drinker consists of two categories - (yes=1; no=0). From the graph, we can conclude that `Social drinker` have higher \n",
"number of `Absenteeism time in hours`."
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 686\n",
"1 54\n",
"Name: Social smoker, dtype: int64"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['Social smoker'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df['Social smoker'].value_counts().plot(kind = 'bar', figsize=(10,5))\n",
"plt.title('Absenteeism time in hours in various seasons')\n",
"plt.xlabel('Social smoker')\n",
"plt.ylabel('Absenteeism time in hours')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"Social smoker consists of two categories - (yes=1; no=0). From the graph, we can conclude that `Social smoker` have lesser \n",
"number of `Absenteeism time in hours`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Findings of multivariate analysis\n",
"\n",
"Findings of bivariate analysis are as follows:-\n",
"\n",
"•\tThe spring season contains highest number of `Absenteeism time in hours`.\n",
"\n",
"•\tThe high school category consists of highest number of `Absenteeism time in hours`.\n",
"\n",
"•\tThe `Social drinker` category have higher number of `Absenteeism time in hours`.\n",
"\n",
"•\tThe `Social smoker` category have lesser number of `Absenteeism time in hours`.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Estimating correlation coefficients\n",
"\n",
"Our dataset is very small. So, we can compute the standard correlation coefficient (also called Pearson's r) between every pair of attributes. We can compute it using the `df.corr()` method as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"correlation = df.corr()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Our target variable is `Absenteeism time in hours`. So, we should check how each attribute correlates with the `Absenteeism time\n",
"in hours` variable. We can do it as follows:-"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Absenteeism time in hours 1.000000\n",
"Height 0.144420\n",
"Son 0.113756\n",
"Age 0.065760\n",
"Social drinker 0.065067\n",
"Transportation expense 0.027585\n",
"Hit target 0.026695\n",
"Work load Average/day 0.024749\n",
"Month of absence 0.023779\n",
"Service time 0.019029\n",
"Weight 0.015789\n",
"Seasons -0.005615\n",
"Social smoker -0.008936\n",
"Education -0.046235\n",
"Body mass index -0.049719\n",
"Distance from Residence to Work -0.088363\n",
"Disciplinary failure -0.124248\n",
"Day of the week -0.124361\n",
"Reason for absence -0.173116\n",
"Name: Absenteeism time in hours, dtype: float64"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"correlation['Absenteeism time in hours'].sort_values(ascending=False)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Interpretation of correlation coefficient**\n",
"\n",
"The correlation coefficient ranges from -1 to +1. \n",
"\n",
"When it is close to +1, this signifies that there is a strong positive correlation. So, we can see that there is a small positive correlation between `Absenteeism time in hours` and `Height`. \n",
"\n",
"\n",
"When it is clsoe to -1, it means that there is a strong negative correlation. So, there is a small negative correlation between `Absenteeism time in hours` and `Reason for absence`.\n",
"\n",
"\n",
"When it is close to 0, it means that there is no correlation. So, there is no correlation between `Absenteeism time in hours` and `Seasons`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Discover patterns and relationships \n",
"\n",
"\n",
"An important step in EDA is to discover patterns and relationhsips between variables in the dataset. We will use the following\n",
"graphs and plots to explore the patterns and relationships in the dataset.\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Correlation Heat Map"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x864 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(16,12))\n",
"plt.title('Correlation of Attributes with Absenteeism time in hours')\n",
"a = sns.heatmap(correlation, square=True, annot=True, fmt='.2f', linecolor='white')\n",
"a.set_xticklabels(a.get_xticklabels(), rotation=90)\n",
"a.set_yticklabels(a.get_yticklabels(), rotation=30) \n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"From the above correlation heat map, we can conclude that :-\n",
"\n",
"1. `Month of absence` and `Seasons` are positively correlated (correlation coefficient = 0.41).\n",
"\n",
"2. `Body mass index` and `Service time` are positively correlated (correlation coefficient = 0.50).\n",
"\n",
"3. Smilarly, `Body mass index` and `Age` are positively correlated (correlation coefficient = 0.47).\n",
"\n",
"4. Also, `Body mass index` and `Weight` are highly positively correlated (correlation coefficient = 0.90).\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Pair Plot"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x1080 with 42 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"num_var = ['Transportation expense', 'Distance from Residence to Work', 'Service time', 'Age', 'Work load Average/day ', \n",
" 'Absenteeism time in hours']\n",
"sns.pairplot(df[num_var], kind='scatter', diag_kind='hist')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"1. The above pair plot confirms that there is strong positive correlation between `Service time` and `Age`.\n",
"\n",
"2. Similarly, `Distance from Residence to Work` and `Transportation expense` are positively correlated. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Scatter Plot of Absenteeism time in hours and height"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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Xrw8WiChwCSHtZjQLMBgFGMwCqnQGClsnKHAJIW0WyBPJ+AIFLiHELXQgrO0ocAkhLhElBr3BTAfC2oEClxDSIotgG3Fgob7ZdqLAJYQ0K5jPCPOWoA7cLfvOIuvgZdQaLMDfrwEAFAoOKiUHnldCpVQgorMGDAwGk4jYqFCkj+vncHWG1EVZTdrdvSbNrTpy8oqRmX0RxeX6ZtchVxuEANYzwmoNAkwWgQ6EeZis1zTzJ1v2ncW2r85bw7YBSWIwWaxfoaprTbj6czWuFeugAENFtQEbMk8hJ68YQPNh29Ly5uTkFWND5ilUVBvQWcs3WYdcbZDgxhiD3mhBaYUBN6qNMFLYekXQBm7WwcsA5/x+xqwXTGcAFByHqlozQtQ8eJ5DZvZFj9WRmX0RPM8hRM2D47g2rcMTbZDgJEoMOoMZJeV6VNSYYBZEX5fUoQVtl4LBJIBXAC19vGz9VhxnPXAAABqVEiXleo/VUVyuR2et49vg7jo80QYJLsE4NaI/CNo9XK2Gh9jKdyaOs/4wBqh466YyWUTERIV6rI7YqFCYLI6x7+46PNEGCQ4WQURljQklFXrUGChs5Ra0gZs2pi9a6qTiOGuPAwdAYgxdOqlhNAsQBIb0cf08Vkf6uH4QBOulRWyXGHF3HZ5og3RsJpOA8iojSisNqDVaaNSBjwRt4M6eNBAPTExEJ63KYblCwUGjUiA0RIXwThr07h6OuNgwMHCIDNfi0fSh9qP/zkYjuDNKIXlQLB5NH4rIcC10BqHJOuRqg3Q8jFkvLV5WdyCMhnf5XtD24QLW0J09aSBOnDiBESNGtKkNd4eANSd5UGy7w9ETbZCOQZKYfY4DOvXWv7i0h/v11183WbZr1y6PF0MIaTtRlFBTa0JJRS0qdWYKWz/U4h7ugQMHIAgCVq1aBUmqf/MEQcD777+PX//6114vkBDSMotQP+KATr31by0Gbl5eHr777jvcuHEDn332Wf2TeB4PPfSQt2sjhLSATr0NPC0G7sKFC7Fw4UJs3rwZc+fOlasmQkgLaA7awOXSQbP77rsP//znP1FeXg7W4L/Shx9+2GuFEULqMcbAOBVKyvXUNxvAXArcRYsWoaioCImJieC4Fs6HJYR4lChZ5zjQGyworzagB4VtQHMpcM+fP48vv/wSCkXQDtslRFb2U2+NFvsZkYw6agOeSwnatWtXCILgduM6nQ4pKSm4ds069eE333yDX/3qV0hJScFLL70Es9kMACgsLMTcuXMxZcoUPP7446itrXV7XYR0BGZLo1NvKWM7lBYDd+PGjdi4cSOio6Mxb948/OUvf7Ev27hxY4sNnzx5ErNnz0Z+fr592auvvor33nsPe/bsgdFoRFaWdRrD3//+95gzZw727t2LpKQkfPDBB+1/ZYQEEJNJwI0qI8qq6NTbjqzFwD1//jzOnz+PsLAw9O3bFz/99JN92fnz51tsePv27cjIyEBMTIx9mSiK0Ol0EEURJpMJGo0GFosFx48fx+TJkwEA6enp2Lt3rwdeGiH+rfGpt0Ya3hUwxDb2pbfYh7ty5co2NQoAK1asaLJs2bJlmDdvHsLCwhAXF4cpU6agoqICYWFh4HlrKdHR0SgupomzScfFGIPeRFe9DSSiKOHKzzU4f7UC569W4NK1Kny4+B6323HpoNmECRMcRidwHAetVov+/ftj8eLFDnuxzpSWlmL16tXYs2cP4uLisHLlSqxcuRKPPfZYk5EPbRkJkZub6/ZzGjpx4kS7ni+XQKkTCJxa5apToVBCYFzdGFqhTQfB2vs5l0ug1ylKDKVVFly/YcH1G2YUlVtg8UCHukuB+8tf/hK1tbWYO3cuFAoFduzYgdraWgwYMACvv/46Pvzww1bbyMnJQWJiInr37g0AmDlzJp599lksWbIENTU1EEURSqUSpaWlLgV4Y0lJSdBoNG4/D0C7Jq+RU6DUCQROrXLU2dyIg7bIzc1FUlKS5wrzkkCsUxQlXC2uwbkr9XuwjeeYBoDoSC0G9I5EYu/INq3TpcDNyclBZmam/fbSpUsxY8YMrFy5Ep9//rlLK0pMTMQ777yDsrIydOvWDfv378eQIUOgUqmQnJyML774Aqmpqdi1axfGjBnTphdDiD+xCCL0BoHmOPBDoijh5woLrn+Xj/NXK3HxWiVM5qYBGxOpRWJdwPbvHYHIziHtWq9LgVtbWwudToewsDAA1uFeRqPRrRUlJCTgmWeewfz586FUKtGnTx8sX74cAJCRkYHFixfjz3/+M3r06IG1a9e6+TII8R80x4H/se3BWvtgGwZsucPjbAHbv3ckEj0QsI25fGrvzJkzMWXKFDDGsG/fPtx///347LPP0Ldv3xafe+DAAfvv06dPx/Tp05s8plevXg6T4xASiIwmATqDheY48APOA9ZRTKS2LlwjkRgfgchwzwZsYy4F7u9+9zvccsst+O9//wue5/Haa6/hjjvuQG5ubrMBSkiwsA7tEqwHwuiKtz7jasBGN+giYPpi3DFymKx1thi4ly5dQkJCAs6cOYPIyEiH+W/PnDkTEB3jhHgDXVXBt0RJwtWfXQvYAU76YHNzy+QsGUArgbtq1Sps2LABTz31VJP7OI7D/v37vVYYIf5IlBj0BjNqjQJEOhImm/qArcT5qxUu7cHK0UXgrhYDd8OGDQAc+2EJCUa2oV21RhpxIAe3AzY+Aom9I/0uYBtzeZTCmjVrcOnSJfzhD3/A2rVr8fLLL6NTp07ero8Qn7IIImrrhnbRiAPvESUJBcU6+5lcFwsqYWwuYCO0SOzjv3uwrXEpcN98803ExMTgxo0b0Gg00Ol0eP3117FmzRpv10eITxjNAvQGAUYLDe3yBpcDNlKLxPhIa8gGYMA25lLg5uXlYeXKlfjvf/8LrVaL1atXIyUlxdu1ESI7unyNdzTuIrh0rfmA7RZhPcjVv7e1iyAqwAO2MZcCt/HE46Io0mTkpMOwDe3S0WQyHmPbg60/VdZ5F0H/3hF1IdvxArYxlwJ35MiRePfdd2E0GnHo0CFs3rwZo0aN8nZtXjfzld0wmOv+gf39WouPjYkKRWxUKNLH9UPyoFj78tRFWU0eu3tNmkfrdMWWfWeRdfAyDCYBWg2PtDF9MXvSQNnrCCSiKEEEj5JyPQQ/PhKWe6kM+45eRVFpFXqc+h6TRvVGUkI3X5floGEXwYkzFfho30HnfbA+3oP15fbkmAtTFlksFvzlL39BdnY2RFHE3XffjSeeeKLNk8V4kslksk9C4U49DmHroriYThAEhkfThyJ5UGyzYWvjjdB1NtHKln1nse2r8wAHKDlYJ0hhwAMTE30Wuv48eY3ZIkJvFGAwWXDqtH9PtJJ7qQxb952DUslBFMxQ8mqIIsOsSQN8Grqu9sF26xKCxD6RfrMH68ntqVEp0S1C69ZzXNrDValU9kumdxTuhi0AhKh5GCEgM/uiw16ur2UdvAxwAF/XzcNzgCBJyDp4mfZyG7CfeiuIAXMgbN/Rq1AqOWhUShhE698miNh39KqsgetywEZoEd2ZYdSwvkiMj0RUF//qIvD19mwxcB977LEWn+zKtIwdjUalREm53tdlODCYBPCNutSVnHV5sAv0yb7LqgzopFE6LFPzCtyoMnh1vZLEUFBcg3MuBGxiXfeALWCt3zh7eLW+tvLV9rRpMXBtl70BgD/+8Y94+umnvV6QvzNZRMREhfq6DAdaDQ+jWQDfYN52kVmXBytRlKyXFzcKft0/25puXbSo0hmhUdWHhFmQ0LWLe19lWyNKEq4V63DuagUuXK3AhWuVMJqcdxE0DNhAItf2dKbFf5ENJ6b529/+1qEmqtGqFW53KxjNAgSBIX1cPy9V1TZpY/pi21fnIUiSQx9u2piWZ3LriMwWEQZjx5mDdtKo3ti67xxMEMEYg8kiQhQZJo3q3a52XQ5Y2x5svDVkAy1gG/PW9nSVy7tAbbnsjT/bvjLVrQNnsVGhiAzXOoxS2L0mzS9GKdj6aYN5lIKxbsYuk9CxTlRISuiGWZNQd1TdhB4RIW06qi5JDAUlNTh/xTrZy4VrFR1yD7Y1ntqebRW83zlhDV2gfUfUfTEErDmzJw0MqoAFAr9/1lVJCd2QlNDNrUvXuBWwvW1ncnW8gG1OW7anp7QYuJWVlfbfRVFEVVWVw4XvIiIivFcZIU6IErP2zxosAd0/60luB2zdWFi5+i6JVYuBe8cdd4DjOHvINjzZgeM45OXlebc6QhqgGbvquRqwXbuEOMwHSwHrWy0G7tmzZ+WqgxCnbCcqBPOMXZLEUFJpwVdHr7QasPY92PgItwfmE+8K6j5c4t9MJgG6DnggzBXO92AdL3oYFR6CAX0oYAMFBS7xK4wxGM0CdHoBFiF4ZuxqHLAXr1U2e+JK1y4h6B8fiQF9KGADEQUu8QuSxKA3WaAPkmuESRLDtZL66QovFDgPWNveK4yluOt2eS96SDyLApf4lCBKMBitB8I6cs66GrAtdRHk5pY3eTwJLBS4xCdMDc4I64j9s+4ErH0ugt6R1EXQwVHgEtnY+mc74hUVrAFbP5tWywEbaQ9ZCtjgQoFLvE4UJehNQoc6UaFxwF4sqISe9mBJKyhwiVcoFAqHib4DPWfdC1jagyXNo8AlHmXvNjBb5x4N1P5ZCljiDRS4xCNs8xsYjNZhXbV6U0CFLXUREDlQ4JJ2sQgi9IbAm39WYgzXS3T44XItDp496XLAdu0S0uGmKiXyocAlbrN1G+gNYsCcdmsL2IajCPRGW8Dq7I+LDNfYJ3uhgCWeRoFLXCZKDIYAORus5YCtFxaiwOCEGPvJBhSwxJu8Hrg6nQ6zZs3Chx9+iEuXLmHt2rX2+4qLizFs2DBs2LAB69evx+eff47w8HAAwMyZMzF37lxvl0dcYBHqZuvy42kRXQ3YyHCN/XIxiX0i8XPBRQwZMtgHFZNg5NXAPXnyJJYuXYr8/HwAwNixYzF27FgAQGlpKWbPno1XXnkFAJCbm4u1a9fi1ltv9WZJDnLyipGZfRGXr5UDO4vBJAmcQgGVUoH47p0dLqfjzJIPDuH0pfpTLockROGtJ+72duleZ+s2MBhFGC3+123Q1oDt1mgPtvia873Z3Etl2Hf0KsqqDOjWRSvrpVhIx+TVwN2+fTsyMjLw0ksvNblv1apVmDVrFm666SYA1sDdsGEDrl+/jpEjR+Lll1+GRqPxWm05ecXYkHkKFlGCwSQBnARJAjhOhILjUFiqw4bMU0D6UKeh2zhsAeD0pXIs+eBQwIau7SQF22gDf+FywHbW2PtfmwtYV+VeKsPWfeegVHLopFGiSmfE1n3nMGsSKHRJm3k1cFesWNHs8vz8fBw7dsx+f21tLQYNGoQXX3wRffr0weLFi/HBBx/gueee81ptmdkXwfMcqmoFcBwcviorFBz0RgFdu2iQmX3RaeA2DtvWlvsz29wG/nKSgsQYCkusV5U9f7USFwoqWg/Y3tbJXjzRB7vv6FUolZz9ctoalRImiNh39CoFLmkzjjHvf1mcMGECPv30U8TFxQEA3nnnHURERODRRx9t9vE//vgjlixZgl27drXatslkQm5urts1rcsqQoiaQ2mVNXCFBpPn80qAMSC6Cw+jmeHZtB7NtrHs79ectr9sTpzbNclNqVRClBQwmEUYzRaIPtyjZYzhRo2A62UWXL9hxvVyM0yWph/NsBAFenVV1/2oEB6q9MpBrr/tL4VGxTm0bb2sNsOD90R7fH0k8Iy4dZjb47B9Mkph//79+Pjjj+23CwsLceTIEcyYMQOA9YPN8+6VlpSU5FYXRPyxw6ioNkCtAswWa+gyBnAcwHEKqHgFeJUG8V21zq/o20LgtvUqwC1pz9WFG5LjIoytXRG1TXuw7egicLfOHqe+R5XOaN/DBazfAnpEhMh+pVcbX1xlti06Wp1c3R8cAAXHQalQQKnkoOIVbq9T9sAtLy+H0WhEfHy8fVlISAjeffddjBo1CnFxcdi8eTMmTpzo1TrSx/XDhsxTCA3hYTLXBy5gPesotBMPQWBIH9fPaRtDEqKa7T4YkhDlrbLbxTbawGC0QJS526BxwF4sqECtjF0E7po0qje27jsHE0SoeQXMggRRZJg0qreGF0rnAAAgAElEQVTstRDvUCoV4DhAAevcHwoFB2Xdj8L2w3H1y5XuB2xjsgfutWvX0L17d4dlUVFRWL58OR5//HFYLBbcdtttePjhh71aR/KgWCB9KDKzL8JoMgOc0mGUQs/osFZHKbz1xN1+P0rBVycpMMZwrbgmYAK2saSEbpg1ydqXe6PKgK40SiEgcPY/AAUHKBUK616pUgGlAuDqwpPjOER11iA2qhOUCvk+b7L04XqTrQ/X3S6Fhjz1Vd3b3KnTdklxvUmAKMNRMIkxFJbq7BNu5/1U1mwfbETnhmdy+T5gA+XrLxA4tXqjzoZBquQ4KBSKRnujqPu7LmDrlrfEF//ug/pMszWbc3Dwh0JIEoNi63WMGd4Ti+Ymu9XGk+/ux5Wf608N7dM9DOtfvMfTpbrMIliDttbLV1JoHLAXrja/BxtRtwc7wE8Clvhew/AEbF/pOXCcAgoOjl/nlVxdwNZ/tQ/kz0/QBu6azTnI/v66/bYkMfttV0O3cdgCwJWfdXjy3f2yh671JAUBBrN3ug3cDdhOilqMvysJ0RSwQcP2NqtVPFRKDgrOenDJ1g+qUHJ1gaqoX8YhqD4fQRu4B38oBFD3IWEA6g6aHfyhEItcPKO4cdi2ttzTGGMwmAToDQLMHr6kuMQYikpr6/pgnQdslzBN3TwEEegfH4mYSGvA5ubmIiYy1IMVEV9ofITe8at8/d4oZ/8ar0BJGI+YqE4+rtw/BW3gSk76NZ0t9yeiKFmHdRkFjw3rcnUPtkuYBom9I+yTvdAebOBp6cCSgkPdnqjjEXqFG1/lRVFs/UFBKmgDV6Hgmg3X1jrafUmh4FFVY/LI3LO2PVjbqbLnCypRa7A0eZyzPVjiXxxCFI7DnBr+rehA/aGBKGgDd8zwnsj+/np9fyerX+6qPt3Dmu0+6NM9zAMVWklS3bAuo4AbNWbEGJuGokvtuBGwtAfrP7gGIRqiUUGjUjqGZ6N+UVeOzhPfCdrAtR0Ys49SUHBuj1JY/+I9XhulYLKIMBoFGMwW2M64deermrsBm9g7EgP6UMB6W9M9UevBJYe9UAWa9IsqFRyKChR0SZ8AF7SBC1hDd9Hc9o3H8+RoBFFiMJos0BtFWNw8CCYxhqKy+oC9cLUSulYCNrE3dRG0F+fsazxnDU6uLjhtR+OVDb7Wu7vdJcl/Zm8jbRPUgesvjGYBJpPoVt8sBaznNdz7tB2V57j6r+/N74HWhywhraHA9RFRlGAwW4d0CaLU6t6sxBhuVAv4z4kCClg3OBvWZA1JoGtEKKLCNeBQfzDJtidKiKdR4MrMZBKgNwkwmoUW92ad78HecHhclzA1+sdH2g9yBUPAOg5rsn1Ntw2yd29YEydZoNWoZK2fBC8KXBm4chUF17sI1EjsHYn+8REY0CeqwwWs7aUoG0yDR8OaSEdBgetFRpMAg6n5023dDdjE3pGAsRSjRw0LuJBprm+0Yd+nLVSttxXglRSkpGOiwPUg6xUBRJjMIox1s3TZctbVgA3vpLYP0WrcRZCbW+EXQdTchMz1/Z/WZVFdQhHZWWM98NRoXlFCghUFbjtZBBFmQYLZLMJkESBJ1nMoWIOAPddKwA7o4/sugsZ7oQ79oo2+0luXKVoMTwWzIDSE+kYJaYgC1w2ixGCxiLAIEiyCBLPQKGBv1DrMRVCjd74HaxtJEBsV6tWAdfZ1Xql0/Dpv20ulI/SEeE9QB67D1Rr+fg1c3UQefN31ilS8EmqVAowBZkvdnqxFxM09u6B/fBfkXi7HlaLqFtdhDdj6YVrNBexf/3kax/NK7NdUGzkoBgt+NaTFdhufsbTlq3M4eaEMCo4Dz3O4bUAMHpo22K2v81v2nUXWwcswmARoNTzSxvTF7EkDW3xOYzl5xcjMvoiCogrEHzvc6lUzvMVWR3G5HrFRoW2qwxNtEEf+8L748jOqXLZs2TJZ1uQloiiipKQEMTExbl148vUN3+B8QTVCQ3h00qoQ3kmNzp3U0KiV4JXWkDWaBVTrLdDpLTCarXu2ksRwo8qICwWVqNKZnLY/Z/IA3DehP349NgEjBsaiT49whIWqmw3bYz+WOCy7XlqLsko9bk2MAccBvIKDildCr6tCfM/uCA3hEapVIUyrRnioGp9+8SMOnyqC2SLCYBJQU2vG+auVKK3Q4+7hcfazm1qyZd9ZbPvqPARJAq8ALKKEM5dugIFhiIuXlcnJK8aGzFMwWwQoOBFmgeH4mWL0jA5Dz2jPzS/hTh2hGh46g9lpHUVFRejZs+n8Ge60IRdntfobb27T9rbh689o+6+KFiAEUaqbBMaCmloTrpXqoVErIUkMtUYLyioNKCqrRWmFAeXVRlTXmmE0i22ernHMrXHo3rVTi90FHIAffypHeCc1osJDEB2hRfeuoejRrRN+KqxGtwgtukd1QmzXTugWoYVaKaFzJzVCQ1QIUfNQ8dZugH3HCqA3CjBZRIeTKGxz/roi6+BlgAN4hQIcpwCvUABc3XIXZWZfBM9zCFHz4Djr3zzPITP7ostteIIn6vCX19KR+MP74uv3tcN0KZjMIiRYIEkMkmQdFSBJDILIIIoiJMBhaFZphaFd61NwcPk0XNuVQZVKBXiltctCqVTYfwSRQRCtZ5yJEoNYd0lddYNLdAPWfuLmeGJuX4NJQOOrPis563JXFZfr0Vnr+JHSqJQoKde73IYneKIOf3ktHYk/vC++fl87TOBW1pqgNMo4uYftShF1FByg4pXgeQVUvAKhGh4qlXVPUalUOL2GfY3e+p9E4x1hd6bY88TcvloND6NZAN/gKSKzLndVbFQoKqoNCFHXP8dkERETJe+VHzxRh7+8lo7EH94XX7+vHaZLobXreNmGaf33+2v4f7tOt+tIvIIDQlRKdA5VISo8BLFRoYiN6oTOnVTglRxMZhGR4SEI06oRouGdhi1QP/8uY/U/DZe7whNtpI3pCzBAkCQwJkGoG36RNqavy22kj+sHQbDO32u7PLsgMKSP6+dyG57giTr85bV0JP7wvvj6fe0wB81CO0dCoaj/Cs4Yw8839Pj+bAm+OnoFW786h31HryL30g0UldW6faFFjVqJzlo1wjupceuAGNw9vBfAWQ9w6QxmVNearf2oZhE7V6W63O5dQ3uiqEyHq8U6MGbdKx17a69m5+V1djDCnTacGZLQDQwMl65VwSxI0Gp43Dehn1ujFGwHHvKLalBeZUBst86Yd+8g2Y/sN6yjosaEbhGhTutwtk3daUMugX7QzBPbtL1t+PozyjFnHYMBwmQyITc3F9163IzSKkv9hNstjIO1nmQQif7xkejeNRRnzpxBUlJSk8dyAHilAlqNEmo1D02jPlW5tWfeXrkFSq2BUicQOLVSnc51mD7clX87hutlTYdp2cbB2mbUajgOds83l7H/eIH1wNCeYgDWDnRtCA+tmodZsJ6ia2hmtMKQhCi89cTdSH8pC5YGF2JQKYHMVWlu1b5mc067rjwB+Mf4RqDRa9l6vU2vxV/QOFziaR0mcGsN1qPpnUNV9pMMEntb92CbG5q155vL+OLwT5AYwCs5hIaooNXwkBiD3iigWlfb4iiE05fKkbooq8lyiwikv5Tlcuiu2ZyD7O+v229LErPfdjWobGMLeZ5DZy2PimoDNmSeAtKHuhwQnmjDE6/FX3hiexDSWIcJ3NS7+6JvXFenAdvYgZwCdNLyCFGroFBwMJgE3KgyQnAyfaI7LG5cJdo2VrZhyYxZly+a61obDccWAkCImocRAjKzL7ocDp5ow+G1MACc+6/FX3hiexDSWIcJ3FFJPcDzrU+WwsE6fCsiTANBEFClN8NkdiMhPcwTY2j9YXwj4JnX4i98PV6TdEwdZlhYa3gFh85aFbpFaBEdqUW13owbNb4NW8D5WFl3xtDGRoXC1Gi3ui3jG9vbhidei7/wxPYgpLEOHbgcB4RqeESFaxATFYrwMI397K1f3d0Xbl0W1w3uDGbwxBhafxjf2OS1oG2vxV/4erwm6Zg6ZOCqlAqEh6oQGxmKyPAQaDWqJv26sycNxAMTE9FJ27Y5W4ckRGH3mrQm4eruKIVFc5Mx7rZe9r1AhYLDuNvcG0ObPCgWj6YPRWS4FjqDgMhwLR518+COJ9rwxGvxF57YHoQ01mHG4cb06ovQEC1CtUr7xBSuonGDnhcotQZKnUDg1Ep1Ouf1g2Y6nQ6zZs3Chx9+iEuXLmHt2rX2+4qLizFs2DBs2LABeXl5ePXVV1FbW4vk5GT8/ve/d2u6xahwDTqFhrhV25Pv7seVn3XWG3+/5vLzdq+p34NtbmhYw/td4YlxuAve2IvSyvpxyNERGvz1tSlutdGR5sMlxB95tUvh5MmTmD17NvLz8wEAY8eORVZWFrKysvDRRx8hLCwMr7zyCgDgxRdfxOuvv44vv/wSjDFs377drXXxSvfOAnMIWzfZQra5sG1peXNsY1dtR/JtY1fXbM5xuY3GYQsApZUmLHhjr8tt2ObDNZqts4YZzQK2fXUeW/addbkN29hV6+QgnH3sak5escttENKReTVwt2/fjoyMDMTExDS5b9WqVZg1axZuuukmXL9+HUajEcOHDwcApKenY+9e18OiLdoatp7WcOyq7afhclc0DtvWljenI82HS4i/8mqXwooVK5pdnp+fj2PHjtnvLykpQXR0tP3+6OhoFBe7t1eUm5vb9kLb4MSJE+2638Y+RrXxZdQl1mwbrrbr7uP1Rot1jl+pwYkfjEFvtLjcRkFRBULUHGoFMwCgVq8HYwwFRUa365aTP9fWWKDUGgx1tqX/1ycnPmzbtg1z5syBWq0GYP1H3vAgF2PM7QsrJiUlQaPRuP4EN/psmzNixIgW23D1zVBsretOaPhy62b8atyG005+D9QRurMYRrMAhaL+S48kSQjV8C63EX/ssH2u0Vq9Hp1CQ2E0C4jvqvXbgyiBcoAHCJxaqU7nfDIsbP/+/Zg6dar9dvfu3VFaWmq/XVZW1mw3hCf16e6b61I15olxuNERzf9H42x5czrSfLiE+CvZA7e8vBxGoxHx8fH2Zb169YJGo7Hv3mdlZWHMmDFerWP9i/e0OXRtoxCcjUZwZ5SCJ8au/vW1KU3C1d1RCrZxySFqHoJknTvggYmJbo1SaDh21WhmNHaVkEZk71K4du0aunfv3mT56tWrsXTpUuh0OgwePBjz58/3ei3rX7wHQPu+Wrg7BKw5i+Ymt3tyF3eHgDVn9qSBbg8Dayx5UCySB8UGzNdKQuQkS+AeOHDA/vvQoUObHfI1cOBA7NixQ45y7No6DndIv2728aWeGIfrL3PZEv9EY5sdBfJnvUOe2uuK9ozDPX2xDBsyT3lkHG7DsasN5111Z+yqJ9og/onGNjsK9M960AZue8fh8rxnZsDyxNhVGv/acdF76yjQt0fQBm57eer6ZsXl+iZttWUu2/a2QfwTvbeOAn17UOC2UeO5UtvKX+ayJf6J3ltHgb49gjZw2zsOVxA8M8mav8xlS/wTvbeOAn17BG3gtmcc7pB+3fBo+lCPjMP1l7lsiX+isc2OAv2z3mGuadYW/jIO1zZ21ddtEP9EY5sdBfJnPagDt/E43PBQHiLjUGuwtPg8f5wP11/4y5jRQB6rSTquoO1SaG4cbrVeaDVsAf+bD9df+MuY0UAfq0k6rqAN3I40H66/8Jcxkv5SByGNBW3g+gv7fLguLvdn/jJG0l/qIKQxClwfs80S5upyf+YvYyT9pQ5CGgvawO1I8+H6C38ZI+kvdRDSWNAGbnPjcMNDeXTSqlp9rr/Nh+sv/GXMaKCP1SQdV1APC/OXcbiemA/XX/jLmNFAHqtJOq6gDtzW5sPt0z0MvxjWC1kHL8NgEqDV8Egb09dhkm5PjMPdsu9si+sghHQMQdul4Mp8uFd+1uHvX56D0SyAVwBGs4BtX53Hln1nAXhmHO6WfWex7avzTtdBCOk4gjZw3RmHyysU4DgFeIUC4ICsg5c9VkfWwcsA5911EEL8Q9AGblspOcBgEjzWnsEkQNloBJin10EI8Q8UuG4SGaDVeK7rW6vhITY6x8HT6yCE+IegDVx3xuEKkgTGJAiSBDAgbUxfj9WRNqYvwLy7DkKIfwjawHVlPtw+3cMwZ/IAhKh5CBIQoubxwMRE+wgCT4zDnT1pIB6YmOh0HYSQjiOov7e6Og63pfDzxDjc2ZMGUsASEgSCdg+XEELkRoFLCCEyocAlhBCZUOASQohMKHAJIUQmFLiEECITClxCCJEJBS4hhMjE64Gr0+mQkpKCa9es883+73//w8yZMzFt2jQ8//zzMJvNAID169dj/PjxSEtLQ1paGjZv3uzt0gghRFZePdPs5MmTWLp0KfLz8wFYw/epp57CRx99hIEDB+L555/Hjh07MGfOHOTm5mLt2rW49dZbvVmSg5y8YmRmX0TuxTKwZiYgb0ih4JqdHHzJB4dw+lK5/faQhCi89cTdXquZEBK4vLqHu337dmRkZCAmJgYAcPjwYQwfPhwDB1oDa+nSpZg4cSIAIDc3Fxs2bEBqaiqWL18Ok8nkzdKQk1eMDZmnkHe5DK5ckFySWJPJwRuHLQCcvlSOJR8c8kLFhJBA59XAXbFiBZKT6y+GeOXKFYSGhuK5555DWloa3n//fYSHh6O2thaDBg3Ciy++iJ07d6K6uhoffPCBN0tDZvZF8DwHQXL9OY0nB28ctjbOlhNCghvHGHNlB69dJkyYgE8//RS7d+/GZ599hm3btqFnz5549dVX0atXLzz11FMOj//xxx+xZMkS7Nq1q9W2TSYTcnNz3a5pXVYRQtQcfq5wfaJvlZKDxBgkBmTMjsOyFrohls2Jc7smQkjgaMtFUmWdLaxbt24YNmwY4uPjAQD33nsvNm3ahMLCQhw5cgQzZswAADDGwPPulZaUlASNRuPy4+OPHUZFtQGA64GrUCggSRJCNbx1Y7cQuN64Yq2vr4TrjkCpNVDqBAKnVqrTOVmHhY0ePRpnzpxBUVERAOA///kPBg8ejJCQELz77rsoKCgAYwybN2+29+16S/q4fhAEBt6NLdB4cvAhCVHNPs7ZckJIcJM1cHv06IHly5fjsccew5QpU1BVVYVHH30UUVFRWL58OR5//HFMmTIFjDE8/PDDXq0leVAsHk0fikF9u4Fr/eFQKLgmk4O/9cTdTcKVRikQQpyRpUvhwIED9t/HjRuHcePGNXnM5MmTMXnyZDnKsUseFIvkQbHt+mpB4UoIcRWdaUYIITKhwCWEEJlQ4BJCiEwocAkhRCYUuIQQIhMKXEIIkQkFLiGEyIQClxBCZCLrXAr+Zsu+s8g6eBl6gwXc1usIUSmREB+B9HH9kDwo1qU21mzOwcEfCiFJDAoFhzHDe2LR3OTWn0gICTpBu4e7Zd9ZbPvqPAwmCxis893qTQJ+KqzChsxTyMkrbrWNNZtzkP39dUiSdcI1SWLI/v461mzO8XL1hJBAFLSBm3XwMsABtskpuboJFfQGATzPITP7YqttHPyh0P5c20/D5YQQ0lDQBq7BJEDZIHBtJMagUSlRUq5vtQ3bnq2rywkhwS1oA1er4SGy+r1SGwXHwWQRERMV2mobCkXz84w5W04ICW5BG7hpY/oCDQLXtqcbquUhCAzp4/q12saY4T3tz7X9NFxOCCENBe0oBductvZRCgoOISolbu7ZxeVRCrbRCDRKgRDiiqANXMAaurMnDWzXfLiL5iZj0VwPF0YI6ZCCtkuBEELkRoFLCCEyocAlhBCZUOASQohMKHAJIUQmFLiEECITClxCCJFJwI/DZXWnd5nN5na1YzKZPFGO1wVKnUDg1BoodQKBU2uw1KlWq8E1nh+gBRxjjadvCSw1NTU4f/68r8sghAShpKQkaDQalx8f8IErSRJqa2uhUqnc+p+GEELaK+j2cAkhJFDQQTNCCJEJBS4hhMiEApcQQmRCgUsIITKhwCWEEJlQ4BJCiEwocAkhRCZBHbi7d+/G1KlTMWnSJGzevNnX5TSxfv16TJs2DdOmTcOqVasAAEeOHEFqaiomTZqE9957z8cVOnrnnXewePFiAEBeXh7S09MxefJkvPrqqxAEwcfVWR04cADp6em499578eabbwLwz22alZVlf+/feecdAP61TXU6HVJSUnDt2jUAzrehr2tuXOe2bduQkpKC1NRUvPLKK/YpAWSrkwWpn3/+mY0fP55VVFSw2tpalpqayi5cuODrsuwOHz7MHnjgAWYymZjZbGbz589nu3fvZmPHjmVXr15lFouFLViwgGVnZ/u6VMYYY0eOHGGjRo1iL7/8MmOMsWnTprH//e9/jDHGXnnlFbZ582ZflscYY+zq1ats9OjRrKioiJnNZjZ79myWnZ3td9tUr9ezkSNHshs3bjCLxcJmzJjBDh8+7Dfb9IcffmApKSls8ODBrKCggBkMBqfb0Jc1N67z8uXLbOLEiaympoZJksReeukltnHjRlnrDNo93CNHjuCOO+5AREQEQkNDMXnyZOzdu9fXZdlFR0dj8eLFUKvVUKlUSEhIQH5+Pvr06YP4+HjwPI/U1FS/qLmyshLvvfceHnvsMQDA9evXYTQaMXz4cABAenq6X9T51VdfYerUqejevTtUKhXee+89aLVav9umoihCkiQYDAYIggBBEMDzvN9s0+3btyMjIwMxMTEAgFOnTjW7DX39OWhcp1qtRkZGBsLCwsBxHBITE1FYWChrnQE/W1hblZSUIDo62n47JiYGp06d8mFFjvr372//PT8/H//+97/xm9/8pknNxcXFvijPweuvv47nnnsORUVFAJpu2+joaL+o88qVK1CpVHjsscdQVFSEcePGoX///n63TcPCwvDMM8/g3nvvhVarxciRI6FSqfxmm65YscLhdnP/loqLi33+OWhcZ69evdCrVy8AQHl5OTZv3oyVK1fKWmfQ7uFKkuQw6QRjzC8nv7lw4QIWLFiAl156CfHx8X5X8z/+8Q/06NEDd955p32Zv25bURTx7bff4q233sK2bdtw6tQpFBQU+F2tZ8+exeeff47//Oc/OHToEBQKBQ4fPux3ddo4e7/99XNQXFyMBx98EPfddx9GjRola51Bu4fbvXt35OTk2G+Xlpbav3r4ixMnTuDpp5/GkiVLMG3aNBw7dgylpaX2+/2h5i+++AKlpaVIS0tDVVUV9Ho9OI5zqLOsrMzndQJAt27dcOeddyIqKgoA8Mtf/hJ79+6FUqm0P8Yftuk333yDO++8E127dgVg/Yr78ccf++U2Baz/lpr7XDZe7g81X7p0CY888gjmzZuHBQsWAGhavzfrDNo93LvuugvffvstysvLYTAYsG/fPowZM8bXZdkVFRVh4cKFWL16NaZNmwYAGDZsGH766SdcuXIFoihiz549Pq9548aN2LNnD7KysvD0009jwoQJWLlyJTQaDU6cOAHAesTd13UCwPjx4/HNN9+guroaoiji0KFDmDJlit9t04EDB+LIkSPQ6/VgjOHAgQO4/fbb/XKbAs4/l7169fKrmnU6Hf7v//4PzzzzjD1sAchaZ9Du4cbGxuK5557D/PnzYbFYMGPGDAwdOtTXZdl9/PHHMJlMePvtt+3LZs2ahbfffhtPPfUUTCYTxo4diylTpviwSudWr16NpUuXQqfTYfDgwZg/f76vS8KwYcPwyCOPYM6cObBYLPjFL36B2bNno2/fvn61TUePHo0ff/wR6enpUKlUGDJkCH73u99h4sSJfrdNAUCj0Tj9XPrT52DHjh0oKyvDxo0bsXHjRgDAhAkT8Mwzz8hWJ82HSwghMgnaLgVCCJEbBS4hhMiEApcQQmRCgUsIITKhwCWEEJlQ4AYZi8WC0aNH45FHHrEvO3r0KFJSUmRZ/4IFC1BeXt7m5+/fv98+y5cn1dTUOAwFSktLQ3V1tcfXc/r0aTz99NNuPWfx4sX4+OOPPV4LkV/QjsMNVl999RUGDhyI3NxcXLp0CQkJCbKu//Dhw+16/j333IN77rnHQ9XUq6qqwunTp+23s7KyPL4OABgyZAj++Mc/eqVt4v8ocIPMli1bMHXqVPTu3Rt/+9vfsHz5cgCAXq/H008/jStXriA8PBzLly/HzTffjJycHLz99tuQJAkA8Oijj2Ly5Mkwm81YvXo1jh8/DlEUccstt2Dp0qUICwvDhAkTMH36dHz77bcoKipCWloann32WbzyyisAgAcffBB/+ctfoFAosHz5chQVFcFisWDatGn2Gce+//57rF69GgaDAQqFAk8++STGjx+PzMxMfPnll9iwYQP27duHP//5z+A4DkqlEi+99BJGjhyJefPmYfDgwfjhhx9QXl6OmTNnoqysDMeOHYPBYMC6deswYMAAh+3yyiuvwGg0Ii0tDZmZmbjlllvw7bffIjs7G/v27YMkSSgsLERsbCxmzpyJTZs2IT8/Hw8//LD9rKV//OMf2LJlCyRJQkREBF577bUm/6EdPXoUb7zxBvbs2YPFixcjLCwM586dw88//4wBAwbgnXfeQadOnZq8b//73/8wa9YslJWVoX///lizZg1CQ0ORk5ODVatWwWAwQKVS4dlnn8WYMWMcthMAh9uLFy9GZWUlCgoKMG7cOIwfP77Z95h4gVcmfSR+6cKFC2zw4MGsvLycnTx5kg0dOpSVl5ez7777jg0cOJCdOHGCMcbY1q1b2YwZMxhjjM2fP5/t2bOHMcZYXl4eW7ZsGWOMsffff5+9/fbbTJIkxhhja9asYRkZGYwxxsaPH8/efvttxph13uEhQ4awq1evMsYYS0xMZDdu3GCMMTZv3jy2f/9+xhhjRqORzZs3j/3rX/9ilZWVbNKkSaygoMDexpgxY9j169fZ559/zn73u98xxhi755577HOYHjp0iL3//vuMMcZ+85vfsCeffJIxZp0TNTEx0b6eFStWsKVLlzbZNgUFBf+mZqUAAAUCSURBVGz48OH227Y6P//8czZixAhWWFjIRFFkU6dOZU899RQTRZHl5eWxIUOGMFEU2dGjR9mcOXOYXq+31zNlypQm6/nuu+/YtGnTGGOMvfzyyw5zHv/6179mO3bsaPKcl19+mc2YMYPp9XomCAKbPn0627lzJysvL2d33nkn++GHHxhjjJ0/f57dfvvt7OrVqw7biTHmcPvll19mDz74oP0+Z+8x8Tzaww0iW7Zswfjx4xEZGYnIyEjExcVh+/btGD58OAYMGIDbbrsNADB9+nQsW7YMNTU1uPfee7F8+XIcOHAAd911F55//nkAQHZ2NmpqanDkyBEA1r5h22QrAOxf+2NjY9G1a1dUVVUhPj7efr9er8fx48dRVVWFP/zhD/ZlZ8+eRadOnVBaWoqFCxfaH89xHM6dO+fweqZNm4Ynn3wSY8eOxS9+8Qv89re/td83ceJEALCv8+677wYA9O7dG8eOHXNruw0ZMgQ9evQAAMTFxWH06NFQKBSIj4+HyWSCwWBAdnY2rly5glmzZtmfV11djcrKSkRERDht++6774ZarQYAJCYmoqqqqtnH/fKXv4RWqwVgnbqzvLwcp06dQu/evTFs2DD78ttuuw3Hjh1rdbarESNG2H939h4Tz6PADRJ6vR5ZWVlQq9WYMGECAOtkHps2bUJSUhIUCsfjpxzHged5zJo1C+PHj8fhw4dx6NAhrF+/Hnv37oUkSViyZAnGjh0LAKitrYXJZLI/X6PROLTFGp1BLkkSGGPYunWrPUjKy8uh0Whw9OhRJCQk4B//+If98cXFxYiKisLu3bvty5577jncd999OHz4MDIzM/HXv/4VO3bsAAB7iNmoVKo2b7vGbfF80382kiQhLS0NL774ov12SUkJunTp0mLbISEh9t+b207NrdP2OFEUmwQrYwyCIECtVju0ZbFYHB4XGhpq/93Ze9zwPSSeQaMUgsTu3bsRERGBQ4cO4cCBAzhw4AC+/vpr6PV6lJeX49y5c8jLywNgve7TiBEjoNVqMWvWLPv1nt544w1UV1ejtLQUo0ePxubNm2E2myFJEl577TWsXbu21TqUSiUEQUBYWBiGDx9un0Skuroas2fPxv79+zF8+HBcuXIFx48fB2C93tTkyZMdJoUWBAETJkyAwWDA7NmzkZGRgXPnztmvUeUunuchiqLTwGvN6NGj8a9//QslJSUArN8mHnzwwTa15arhw4fj8uXL9onzL1y4gOPHj+P2229HVFQULly4AJPJBIvFgi+//NJpO87eY+J5tIcbJLZs2YKHH37YYe7X8PBwzJs3D5988gn69u2L9evXo6CgAF27drXPUvbCCy/grbfewrp168BxHJ588knExcXhiSeewDvvvIPp06dDFEUMGjTIfgHJlkyZMgXz5s3D+++/j9WrV+ONN95AamoqzGYzUlJS8Ktf/QoA8Mc//hGrVq2CyWQCYwyrVq1CXFycvTuA53ksWbIEL7zwAnieB8dxeOutt5rsjboqOjoaQ4cOxbRp09p0QdHRo0fjt7/9LRYsWACO4xAWFob169d7dcLtqKgo/OEPf8Abb7wBo9EIjuOwcuVK3HzzzYiPj8fIkSNx7733Ijo6GqNGjWrSJWPj7D0mnkezhRFCiEyoS4EQQmRCgUsIITKhwCWEEJlQ4BJCiEwocAkhRCYUuIQQIhMKXEIIkQkFLiGEyOT/A5FlNpmFOUb6AAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.lmplot(x='Absenteeism time in hours', y='Height', data=df)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"The above scatter-plot shows that there is a mildly positive correlation between `Absenteeism time in hours` and `Height`. \n",
"Majority of data values lie below the fitted regression line."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Scatter Plot of Absenteeism time in hours and son"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.lmplot(x='Absenteeism time in hours', y='Son', data=df)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"The above scatter-plot shows that there is a weak correlation between `Absenteeism time in hours` and `Son`. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Scatter Plot of Body Mass Index and Service time"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.lmplot(x='Body mass index', y='Service time', data=df)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"The above scatter-plot shows that there is a strong positive correlation between `Body mass index` and `Service time`. \n",
"Approximately, half of the data values lie below the fitted regression line and half of the values lie above it."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Box Plot of Absenteeism time in hours and age"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.rcParams['figure.figsize']=(15,5)\n",
"ax = sns.boxplot(x='Age', y='Absenteeism time in hours', data=df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"The above box-plot confirms that the people aged 34 or 58 have highest number of `Absenteeism time in hours`."
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.rcParams['figure.figsize']=(15,5)\n",
"ax = sns.boxplot(x='Son', y='Absenteeism time in hours', data=df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Conclusion**\n",
"\n",
"The people who have 2 sons have highest number of `Absenteeism time in hours`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Findings of multivariate analysis\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Findings of multivariate analysis are as follows:-\n",
"\n",
"\n",
"•\t`Month of absence` and `Seasons` are positively correlated (correlation coefficient = 0.41).\n",
"\n",
"\n",
"•\t`Body mass index` and `Service time` are positively correlated (correlation coefficient = 0.50).\n",
"\n",
"\n",
"•\tSmilarly, `Body mass index` and `Age` are positively correlated (correlation coefficient = 0.47).\n",
"\n",
"\n",
"•\tAlso, `Body mass index` and `Weight` are highly positively correlated (correlation coefficient = 0.90).\n",
"\n",
"\n",
"•\tThe pair plot confirms that there is strong positive correlation between `Service time` and `Age`.\n",
"\n",
"\n",
"•\tSimilarly, `Distance from Residence to Work` and `Transportation expense` are positively correlated.\n",
"\n",
"\n",
"•\tThere is a mildly positive correlation between `Absenteeism time in hours` and `Height`. Majority of data values lie below \n",
" the fitted regression line.\n",
" \n",
"\n",
"•\tThere is a weak correlation between `Absenteeism time in hours` and `Son`.\n",
"\n",
"\n",
"•\tThere is a strong positive correlation between `Body mass index` and `Service time`. Approximately, half of the data values \n",
" lie below the fitted regression line and half of the values lie above it.\n",
"\n",
"\n",
"•\tThe people aged 34 or 58 have highest number of `Absenteeism time in hours`.\n",
"\n",
"\n",
"•\tThe people who have 2 sons have highest number of `Absenteeism time in hours`.\n"
]
}
],
"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": "3.7.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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