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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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