Filling missing values (fillna) in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the fillna() function do in data analysis?

The fillna() function replaces missing values (NaN) in a dataset with a specified value or method.

beginner

How can you fill missing values with the mean of a column using fillna()?

Calculate the mean of the column and pass it to fillna(). For example: df['col'].fillna(df['col'].mean())

intermediate

What is the difference between filling missing values with a constant and using a method like 'ffill' in fillna()?

Filling with a constant replaces all missing values with the same value. Using method='ffill' fills missing values with the last known non-missing value above it.

beginner

Can fillna() be used to fill missing values in both Series and DataFrames?

Yes, fillna() works on both pandas Series and DataFrames to fill missing values.

intermediate

What happens if you use fillna() without assigning the result back to the DataFrame or using inplace=True?

The original DataFrame remains unchanged because fillna() returns a new object by default unless inplace=True is set.

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

A method='ffill'

B method='bfill'

C value=0

D dropna()

method='ffill' means forward fill, which copies the last valid value downwards to fill missing spots.

What does df['age'].fillna(df['age'].mean()) do?

A Drops rows where 'age' is missing

B Fills missing 'age' values with the average age

C Fills missing 'age' values with zero

D Leaves missing values unchanged

This replaces missing values in the 'age' column with the column's mean value.

If you want to fill missing values with a fixed number, which parameter do you use in fillna()?

A value

B method

C inplace

D axis

The value parameter specifies the constant to fill missing values with.

What is the default behavior of fillna() regarding modifying the original DataFrame?

A Modifies original DataFrame by default

B Raises an error if missing values exist

C Returns a new DataFrame with filled values

D Deletes rows with missing values

By default, fillna() returns a new object and does not change the original unless inplace=True is set.

Which of these is NOT a valid way to fill missing values using fillna()?

A Using a constant value

B Using forward fill method

C Using backward fill method

D Using <code>dropna()</code> inside <code>fillna()</code>

dropna() is a separate function and cannot be used inside fillna().

Explain how you would handle missing values in a dataset using the fillna() function.

Think about replacing NaN with a value or copying nearby values.

Describe the difference between using method='ffill' and filling with a constant value in fillna().

Consider how missing data is replaced in each case.