Book Image

The Data Analysis Workshop

By : Gururajan Govindan, Shubhangi Hora, Konstantin Palagachev
Book Image

The Data Analysis Workshop

By: Gururajan Govindan, Shubhangi Hora, Konstantin Palagachev

Overview of this book

Businesses today operate online and generate data almost continuously. While not all data in its raw form may seem useful, if processed and analyzed correctly, it can provide you with valuable hidden insights. The Data Analysis Workshop will help you learn how to discover these hidden patterns in your data, to analyze them, and leverage the results to help transform your business. The book begins by taking you through the use case of a bike rental shop. You'll be shown how to correlate data, plot histograms, and analyze temporal features. As you progress, you’ll learn how to plot data for a hydraulic system using the Seaborn and Matplotlib libraries, and explore a variety of use cases that show you how to join and merge databases, prepare data for analysis, and handle imbalanced data. By the end of the book, you'll have learned different data analysis techniques, including hypothesis testing, correlation, and null-value imputation, and will have become a confident data analyst.
Table of Contents (12 chapters)
7. Analyzing the Heart Disease Dataset
9. Analysis of the Energy Consumed by Appliances

About the Dataset

The dataset we are using in this chapter has been obtained from the UCI repository of datasets. There are 12 separate CSV files consisting of approximately 35,000 entries each. Each file contains data specific to one locality. In total, across all 12 files, there are around 420,000 instances in the dataset.

The attributes include the amounts of a variety of pollutants found in the air, such as sulphur dioxide and ozone, and also the temperature and pressure. This data has been collected over 4 years—from March 1, 2013 to February 28, 2017.

Let's begin our data analysis process by taking a closer look at the data.


To find out more about the dataset, click here:

For further information on this topic, refer to the following: Zhang, S., Guo, B., Dong, A., He, J., Xu, Z., and Chen, S.X. (2017) Cautionary Tales on Air Quality Improvement in Beijing. Proceedings...