Forward fill and backward fill in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is forward fill in pandas?

Forward fill is a method to fill missing values by copying the last known non-missing value forward until a new non-missing value appears.

beginner

What does backward fill do in pandas?

Backward fill fills missing values by copying the next known non-missing value backward until a previous non-missing value appears.

beginner

How do you apply forward fill on a pandas DataFrame column named 'A'?

Use df['A'].fillna(method='ffill') to fill missing values in column 'A' by forward filling.

beginner

What is the difference between forward fill and backward fill?

Forward fill uses previous values to fill missing data, while backward fill uses future values to fill missing data.

intermediate

Can forward fill and backward fill be used together?

Yes, you can first apply forward fill to fill missing values, then apply backward fill to fill any remaining missing values.

Which pandas method fills missing values by copying the previous non-missing value?

A fillna(method='ffill')

B fillna(method='bfill')

C dropna()

D interpolate()

fillna(method='ffill') copies the last known value forward to fill missing data.

What does fillna(method='bfill') do?

A Fills missing values with the previous value

B Fills missing values with the next value

C Drops missing values

D Replaces missing values with zero

fillna(method='bfill') fills missing values by copying the next known value backward.

If a DataFrame has missing values at the start, which fill method will fill them?

A Neither

B Forward fill

C Backward fill

D Both

Backward fill fills missing values at the start by using the next available value.

Which method can you use to fill missing values first forward then backward?

A fillna(method='ffill').fillna(method='bfill')

B fillna(method='bfill').fillna(method='ffill')

C dropna()

D interpolate()

Applying forward fill first then backward fill fills missing values from both directions.

What happens if you apply forward fill on a column with no previous non-missing values?

A They get filled with zeros

B An error occurs

C They get filled with the next non-missing value

D Missing values remain unchanged

Forward fill cannot fill missing values if there is no previous non-missing value, so they stay missing.

Explain how forward fill and backward fill work to handle missing data in pandas.

Think about filling missing spots by looking backward or forward in the data.

Describe a situation where you would use both forward fill and backward fill together.

Consider missing data at the beginning and middle of a dataset.