Pandas Data Types and Missing Values — Master Data Analysis with Python Chapter 3

This is the third chapter from the book Master Data Analysis with Python, a comprehensive guide to mastering pandas that will help you produce trusted data analysis results in a professional environment. There are 80 chapters, 500+ exercises with detailed solutions, videos, and multiple certification exams available. Get access to the first 100 pages of the book for free here.

Chapter 3 — Data Types an Missing Values

One of the most important pieces of information you can have about your DataFrame is the data type of each column. pandas stores its data such that each column is exactly one data type. A large number of data types are available for pandas DataFrame columns. This chapter focuses only on the most common data types and provides a brief summary of each one. For extensive coverage of each and every data type, see part 05. Data Types.

Common data types

The following are the most common data types that appear frequently in DataFrames.

• boolean — Only two possible values, True and False
• integer — Whole numbers without decimals
• float — Numbers with decimals
• object — Almost always strings…