Interpolation for missing values in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is interpolation in the context of missing values in pandas?

Interpolation is a method to fill missing values by estimating them based on other existing data points, often using linear or other mathematical approaches.

beginner

Which pandas function is commonly used to perform interpolation on missing data?

The DataFrame.interpolate() function is used to fill missing values by interpolation.

beginner

What does the method='linear' option do in pandas interpolation?

It fills missing values by drawing a straight line between known data points and estimating the missing values along that line.

beginner

Can pandas interpolate work on non-numeric data?

No, interpolation works only on numeric data because it estimates values mathematically.

intermediate

What is the difference between forward fill and interpolation for missing values?

Forward fill copies the last known value forward to fill missing spots, while interpolation estimates missing values based on surrounding data points.

Which pandas method fills missing values by estimating between existing points?

A interpolate()

B fillna(method='ffill')

C dropna()

D replace()

The interpolate() method estimates missing values based on other data points.

What type of data can pandas interpolation handle?

A Boolean data only

B Text data only

C Both numeric and text data

D Numeric data only

Interpolation requires numeric data to calculate estimated values.

What does method='linear' do in pandas interpolate()?

A Estimates missing values by connecting points with straight lines

B Fills missing values with zeros

C Copies previous value forward

D Drops rows with missing values

Linear method estimates missing values by drawing straight lines between known points.

Which method copies the last known value forward to fill missing data?

A dropna()

B interpolate()

C fillna(method='ffill')

D replace()

Forward fill (ffill) copies the last known value forward.

If you want to fill missing values based on time index, which interpolate option is useful?

A method='nearest'

B method='time'

C method='pad'

D method='bfill'

method='time' uses the time index to interpolate missing values.

Explain how pandas interpolate() can help fill missing numeric data in a DataFrame.

Think about how missing numbers can be guessed using nearby numbers.

Describe the difference between forward fill and interpolation for handling missing values.

One copies, the other calculates.