Data Cleaning With Python, Data Analysis, Dataframes Python, Marketing Analytics.
Let’s dig deeper. step1. We first isolate the rows of airquality with missing CO2 values in one DataFrame, and complete CO2 values in another. # Isolate missing and complete values aside missing = airquality[airquality['CO2'].isna()] complete = airquality[~airquality['CO2'].isna()] # Describe