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Big Data Analytics with Java

You're reading from   Big Data Analytics with Java Data analysis, visualization & machine learning techniques

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787288980
Length 418 pages
Edition 1st Edition
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Author (1):
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RAJAT MEHTA RAJAT MEHTA
Author Profile Icon RAJAT MEHTA
RAJAT MEHTA
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Table of Contents (15) Chapters Close

Preface 1. Big Data Analytics with Java FREE CHAPTER 2. First Steps in Data Analysis 3. Data Visualization 4. Basics of Machine Learning 5. Regression on Big Data 6. Naive Bayes and Sentiment Analysis 7. Decision Trees 8. Ensembling on Big Data 9. Recommendation Systems 10. Clustering and Customer Segmentation on Big Data 11. Massive Graphs on Big Data 12. Real-Time Analytics on Big Data 13. Deep Learning Using Big Data Index

Bar charts


A bar chart shows variations in quantity of some entity using rectangles either drawn vertically or horizontally on a chart. As you visualize the different lengths of rectangles on the chart, it is easy to figure out which category is more and which one is less. Bar charts have three main advantages:

  • You can see the data relationships in the x and y axes

  • You can easily compare the values among different categories

  • You can also use them to visualize trends

As an example, take a look at the following bar chart, which shows the number of cars made by different countries (as shown in cars.json dataset):

As you can see in the preceding chart, this dataset has a maximum number of cars from the UK followed by the USA, followed by Italy, and so on.

Let's explore this example further with the actual code. The cars.json dataset that is analyzed by the preceding chart, has the following format:

{"make_id":"abarth","make_display":"Abarth","make_is_common":"0","make_country":"Italy"}

{"make_id"...
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