Convert and Encode Data Types

Understand how to convert and encode data types appropriately.

Convert data types

There are four main ways we can convert the data type of DataFrame columns:

  • We can use the astype() function to enforce a pandas dtype.

  • We can use the to_ functions like to_datetime() , to_timedelta(), and to_numeric() for manual dtype conversion.

  • We can use the apply() function to apply the custom Python function to columns.

  • We can use the convert_dtypes() function for automatic dtype inference and conversion.

Lets illustrate these different ways by using a dataset of students’ demographics and academic performance.

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# View students dataset

print(df)



print('='*55)



# Inspect data types

print(df.dtypes)

There are a series of changes we need to make to this dataset:

  • Convert student_id from float to the integer type.

  • Convert gender from object (aka string) to category type.

  • Convert enroll_year from object to integer type.

  • Convert birthdate from object ...

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