Filtering your DataFrame

In the previous exercise, you have subset the data using select() operator which is mainly used to subset the DataFrame column-wise. What if you want to subset the DataFrame based on a condition (for example, select all rows where the sex is Female). In this exercise, you will filter the rows in the people_df DataFrame in which 'sex' is female and male and create two different datasets. Finally, you'll count the number of rows in each of those datasets.

Remember, you already have a SparkSession spark and a DataFrame people_df available in your workspace.

Filter the people_df DataFrame to select all rows where sex is female into people_df_female DataFrame.
Filter the people_df DataFrame to select all rows where sex is male into people_df_male DataFrame.
Count the number of rows in people_df_female and people_df_male DataFrames.

Exercise

Filtering your DataFrame

Instructions