Cleaning DataLesson 9Free preview

Cleaning Data

This lesson is part of Pandas · All levels

Summary

Real data almost always has problems like empty values, wrong formatting, or duplicate data. Data cleaning is the process of detecting and correcting such problems so that the analysis can yield valid conclusions. Pandas provide a special function to address each type of common problem.

Key points

Data clearing deals with empty values, wrong formatting, and duplicates
It's not detecting the missing values.
Dropna and fillna are used to handle empty values
Drop_duplicates delete the twin rows

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