Missing data has a value that is not stored for a variable in a dataset. It is typically encoded as N/A, NaN, or a blank.
This scenario describes solving the problem of missing data. There are four common ways to do this: Request the missing values from the owner of the data; delete the missing columns, rows, or values; create a NaN category; or derive new representative values.
The parameters how and on tell Python which way to join the data and which column to join from. How tells Python which way to join the data, and on tells Python which column to start from.
Non-null count is the total number of data entries for a data column that are not blank.
Fill in the blank: Missing data has a value that is not stored for a _____ in a dataset.
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