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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

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781789955248
Length 478 pages
Edition 3rd Edition
Languages
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Authors (2):
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 Navlani Navlani
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Navlani
Ivan Idris Ivan Idris
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Ivan Idris
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Table of Contents (20) Chapters Close

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

Where to find help and references to Python data analysis libraries

The following table lists the documentation websites for the Python data analysis libraries we have discussed in this chapter:

Packages/Software

Description

NumPy

https://numpy.org/doc/

SciPy

https://docs.scipy.org/doc/

Pandas

https://pandas.pydata.org/docs/

Matplotlib

https://matplotlib.org/3.2.1/contents.html

Seaborn

https://seaborn.pydata.org/

Scikit-learn

https://scikit-learn.org/stable/

Anaconda

https://www.anaconda.com/distribution/

 

You can also find answers to various Python programming questions related to NumPy, SciPy, Pandas, Matplotlib, Seaborn, and Scikit-learn on the StackOverflow platform. You can also raise issues related to the aforementioned libraries on GitHub.

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