Chapter 2: Exploratory Data Analysis in Python
This chapter focuses on exploratory data analysis (EDA), which is the first step in processing any dataset. The objective of EDA is to load data into data structures most suitable for further analysis to identify and rectify any wrong/bad data and get basic insight into the data—the types of fields there are; whether they are categorical or not; how many missing values there are; how the fields are related; and so on.
These are the main topics discussed in this chapter:
- Introduction to EDA
- Special Python libraries for EDA
The Python code used in this chapter is available in the Chapter02/eda.ipynb notebook in the book's code repository.
Introduction to EDA
EDA is the process ...
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