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Mastering pandas

Mastering pandas - Second Edition

By : Kumar
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Mastering pandas

Mastering pandas

By: Kumar

Overview of this book

pandas is a popular Python library used by data scientists and analysts worldwide to manipulate and analyze their data. This book presents useful data manipulation techniques in pandas to perform complex data analysis in various domains. An update to our highly successful previous edition with new features, examples, updated code, and more, this book is an in-depth guide to get the most out of pandas for data analysis. Designed for both intermediate users as well as seasoned practitioners, you will learn advanced data manipulation techniques, such as multi-indexing, modifying data structures, and sampling your data, which allow for powerful analysis and help you gain accurate insights from it. With the help of this book, you will apply pandas to different domains, such as Bayesian statistics, predictive analytics, and time series analysis using an example-based approach. And not just that; you will also learn how to prepare powerful, interactive business reports in pandas using the Jupyter notebook. By the end of this book, you will learn how to perform efficient data analysis using pandas on complex data, and become an expert data analyst or data scientist in the process.
Table of Contents (21 chapters)
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1
Section 1: Overview of Data Analysis and pandas
4
Section 2: Data Structures and I/O in pandas
7
Section 3: Mastering Different Data Operations in pandas
12
Section 4: Going a Step Beyond with pandas

Web scraping with Python

Web scraping deals with extracting large amounts of data from websites in either structured or unstructured forms. For example, a website might have some data already present in an HTML table element or as a CSV file. This is an example of structured data on website. But, in most cases, the required information would be scattered across the content of the web page. Web scraping helps collect these data and store it in a structured form. There are different ways to scrape websites such as online services, APIs, or writing your own code.

Here are some important notes about web scraping:

  • Read through the website's terms and conditions to understand how you can legally use the data. Most sites prohibit you from using the data for commercial purposes.
  • Make sure you are not downloading data at a rapid rate because this may break the website. You may...
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Mastering pandas
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