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You're reading from Python Data Analysis Perform data collection, data processing, wrangling, visualization, and model building using Python

Product type Paperback

Published in Feb 2021

Publisher Packt

ISBN-13 9781789955248

Length 478 pages

Edition 3rd Edition

Languages

Python

Tools

Matplotlib

Concepts

Data Analysis

Authors (2):

Ivan Idris

Avinash Navlani

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Table of Contents (20) Chapters

Preface

1. Section 1: Foundation for Data Analysis

2. Getting Started with Python Libraries FREE CHAPTER

3. NumPy and pandas

4. Statistics

5. Linear Algebra

6. Section 2: Exploratory Data Analysis and Data Cleaning

7. Data Visualization

8. Retrieving, Processing, and Storing Data

9. Cleaning Messy Data

10. Signal Processing and Time Series

11. Section 3: Deep Dive into Machine Learning

12. Supervised Learning - Regression Analysis

13. Supervised Learning - Classification Techniques

14. Unsupervised Learning - PCA and Clustering

15. Section 4: NLP, Image Analytics, and Parallel Computing

16. Analyzing Textual Data

17. Analyzing Image Data

18. Parallel Computing Using Dask

19. Other Books You May Enjoy

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NumPy and pandas

Now that we have understood data analysis, its process, and its installation on different platforms, it's time to learn about NumPy arrays and pandas DataFrames. This chapter acquaints you with the fundamentals of NumPy arrays and pandas DataFrames. By the end of this chapter, you will have a basic understanding of NumPy arrays, and pandas DataFrames and their related functions.

pandas is named after panel data (an econometric term) and Python data analysis and is a popular open-source Python library. We shall learn about basic pandas functionalities, data structures, and operations in this chapter. The official pandas documentation insists on naming the project pandas in all lowercase letters. The other convention the pandas project insists on is the import pandas as pd import statement.

In this chapter, our focus will be on the following topics:

Understanding...

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Authors (2)

Navlani

Avinash Navlani has over 8 years of experience working in data science and AI. Currently, he is working as a senior data scientist, improving products and services for customers by using advanced analytics, deploying big data analytical tools, creating and maintaining models, and onboarding compelling new datasets. Previously, he was a university lecturer, where he trained and educated people in data science subjects such as Python for analytics, data mining, machine learning, database management, and NoSQL. Avinash has been involved in research activities in data science and has been a keynote speaker at many conferences in India.

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Idris

Ivan Idris has an MSc in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a Java developer, data warehouse developer, and QA analyst. His main professional interests are business intelligence, big data, and cloud computing. Ivan Idris enjoys writing clean, testable code and interesting technical articles. Ivan Idris is the author of NumPy 1.5. Beginner's Guide and NumPy Cookbook by Packt Publishing.

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