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Dealing with missing data

After looking at the output on the Console, how would you get rid of the NaN values?

You can use the console to further inspect df.

50 XP

Use forward-fill to replace missing values.

Drop rows with missing values, since only one column has a higher frequency than the others.

There are too many missing values, analysis does not make sense.

Either answer A or B. We don't have enough context to decide between the two.

None of the above.