Applied Data Science with Java

,Contents

Preface 1

1 Introduction 3
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2 Automobile 4
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 Data Visualization and Interpretation . . . . . . . . . . . . . . . . . . . . . . 5
2.2.1 F1 Race Data Analysis Report . . . . . . . . . . . . . . . . . . . . . . 5
2.2.2 Visualization Of Indian Automobile Dataset Using Java Programming 27
2.3 Machine Learning Part . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
2.3.1 Car Classification and Analysis Using Java Programming . . . . . . . 58
2.3.2 Auto Parts Export Forecastinga Machine Learning Approach For
The Indian Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

3 Aviation 121
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
3.2 Statistical Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
3.2.1 Exploratory Data Analysis Of Airline Delays W/ Weather And Airport
Detail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
3.3 Data Visualization and Interpretation . . . . . . . . . . . . . . . . . . . . . . 147
3.3.1 Aviation Casualty Analysis . . . . . . . . . . . . . . . . . . . . . . . 147


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, 3.3.2 Visualising Airline dataset . . . . . . . . . . . . . . . . . . . . . . . . 192
3.3.3 Exploratory Data Analysis And Visualization of Flight Fares . . . . . 215
3.4 Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263
3.4.1 Airline Satisfaction Analysis . . . . . . . . . . . . . . . . . . . . . . . 263
3.4.2 Airline Schedule Performance Analysis . . . . . . . . . . . . . . . . . 301

4 Economics 330
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330
4.2 Data Visualization and Interpretation . . . . . . . . . . . . . . . . . . . . . . 331
4.2.1 Economic Analysis and Insights . . . . . . . . . . . . . . . . . . . . . 331
4.2.2 Visualizing How The Income Of Each Employed Person Helps In
The Development Of The Country . . . . . . . . . . . . . . . . . . . 344
4.3 Statistical Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362
4.3.1 Supermarket-Sales Using Java Programming Language . . . . . . . . 362
4.3.2 Statistical Analysis On Bank Marketing . . . . . . . . . . . . . . . . 385
4.3.3 World Income Inequality Analysis . . . . . . . . . . . . . . . . . . . . 417
4.4 Machine Learning Part . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432
4.4.1 RBI Liabilities and Assets Dataset . . . . . . . . . . . . . . . . . . . 432
4.4.2 Global Unemployment Trend Analysis . . . . . . . . . . . . . . . . . 439
4.4.3 GDP Prediction Using Java . . . . . . . . . . . . . . . . . . . . . . . 464

5 Environment 501
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501
5.2 Data Visualization and Interpretation . . . . . . . . . . . . . . . . . . . . . . 502
5.2.1 Analyzing Renewable Energy Trends in India through Data Visualization502
5.3 Statistical Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 536
5.3.1 Statistical Analysis of CO2 Emission by countries Year wise . . . . . 536
5.3.2 Statistical Analysis of Food Waste Across Various Countries . . . . . 555
5.3.3 Statistical Analysis of Food Supply Quantities Across Various Countries586
5.4 Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 639
5.4.1 Weather Prediction Java Program . . . . . . . . . . . . . . . . . . . . 639
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, 5.4.2 Analysis of Indian Crop Dataset for Yield Prediction . . . . . . . . . 642
5.4.3 Predicting Daily Weather Conditions Using Historical Data . . . . . . 667
5.4.4 Air Quality Prediction Using Machine Learning Models . . . . . . . . 701

6 Marketing 726
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 726
6.2 Data Loading and Cleaning . . . . . . . . . . . . . . . . . . . . . . . . . . . 727
6.2.1 Data Analysis for Marketing Strategy . . . . . . . . . . . . . . . . . . 727
6.3 Data Visualization and Interpretation . . . . . . . . . . . . . . . . . . . . . . 745
6.3.1 Data Visualisation And Interpretation On Marketing Analytics Dataset
Using Java Programming . . . . . . . . . . . . . . . . . . . . . . . . . 745
6.3.2 Marketing Data Analysis and Interpretation . . . . . . . . . . . . . . 751
6.4 Statistical Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 793
6.4.1 Statistical Data Analysis On Walmart Sales Using Java Programming 793
6.5 Machine Learning Part . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 808
6.5.1 Applying Machine Learning Algorithm On Bank Marketing Campaigns
Dataset Using Java Programming . . . . . . . . . . . . . . . . . . . . 808
6.5.2 Churn Prediction On Telco Dataset Using Java Programming Language824
6.5.3 Applying Machine Learning Algorithm On Marketing . . . . . . . . . 836

7 Sports 844
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 844
7.2 Data Visualization and Interpretation . . . . . . . . . . . . . . . . . . . . . . 845
7.2.1 Data Visualization On A Div-1 College Basketball
Players Dataset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 845
7.2.2 Insightful Visualization Of IPL Data Using Java . . . . . . . . . . . . 864
7.3 Statistical Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 894
7.3.1 Impact Analysis Of Test Match Scores In Cricket . . . . . . . . . . . 894
7.4 Machine Learning Part . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 914
7.4.1 Applying Machine Learning Algorithm On NBA Dataset Using Java
Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 914
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