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Python Data Analysis

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):

Navlani

Ivan Idris

View More author details

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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To get the most out of this book

The execution of the code examples provided in this book requires the installation of Python 3.5 or newer on Mac OS X, Linux, or Microsoft Windows. In this book, we will frequently use SciPy, NumPy, Pandas, scikit-learn, statsmodels, matplotlib, and seaborn. Chapter 1, Getting Started with Python Libraries, provides instructions for the installation and advanced tips so that you can work smoothly. Also, the process of installing specific and additional libraries is explained in the respective chapters. Installation of Bokeh is explained in Chapter 5, Data Visualization. Similarly, the installation of NLTK and SpaCy is explained in Chapter 12, Analyzing Textual Data.

We can also install any library or package that you want to explore using the pip command. We need to run the following command with admin privileges:

$ pip install <library name>

We can also install it from our Jupyter Notebook with ! (exclamation mark) before the pip command:

!pip install <library name>

To uninstall a Python library or package installed with pip, use the following command:

$ pip uninstall <library name>

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

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Authors (2)

Navlani

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.

See other products by Navlani

Ivan Idris

Ivan 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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