Cleaning Data in Python
Data is of very importance. While extracting information from data, unnecessary data has to be cleaned. It is said that data scientist works 80% on cleaning data and 20% on analyzing data.
Different process of cleaning data are:
Dropping unnecessary columns in a DataFrame
Changing the index of a DataFrame
Using .str() methods to clean columns
Using the DataFrame.applymap() function to clean the entire dataset, element-wise
Renaming columns to a more recognizable set of labels
Skipping unnecessary rows in a CSV file
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