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