Coding Challenges on Duplicate and Missing Data
Explore how to identify, remove, and impute duplicate and missing data in datasets using Python pandas. This lesson helps you apply practical coding solutions to clean data by deleting duplicates, locating missing values, removing incomplete records, and performing mode imputation for better data quality.
Challenge 1: Find and delete duplicate records
We've already imported the pandas library. Write code to delete duplicate records in the cities.csv dataset. Load the dataset in cities_df DataFrame and then save the unique records in a ...