Resampling time series data in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is resampling in time series data?

Resampling means changing the frequency of your time series data. You can make data points more spread out (downsampling) or more frequent (upsampling).

beginner

What does df.resample('M').mean() do in pandas?

It groups the data by each month ('M') and calculates the average value for each month.

beginner

What is the difference between downsampling and upsampling?

Downsampling reduces data frequency (e.g., daily to monthly). Upsampling increases frequency (e.g., monthly to daily) and may need filling missing values.

intermediate

Why do we need to use a method like ffill() or bfill() after upsampling?

Because upsampling creates new time points with missing values. Forward fill (ffill()) or backward fill (bfill()) fills those gaps with nearby data.

beginner

What does the string 'W' mean in df.resample('W')?

'W' means resampling the data by week. It groups data into weekly bins.

Which pandas function is used to change the frequency of time series data?

A resample()

B groupby()

C pivot()

D merge()

The resample() function changes the frequency of time series data.

What happens when you downsample time series data?

A You delete the data

B You increase the number of data points

C You keep the same number of data points

D You reduce the number of data points

Downsampling reduces the number of data points by grouping them into larger time bins.

After upsampling, which method can fill missing values by copying the last known value forward?

A mean()

B ffill()

C dropna()

D sum()

ffill() fills missing values by carrying forward the last valid observation.

What does the frequency string 'D' stand for in pandas resampling?

A Daily

B Decade

C Data

D Downsample

'D' means daily frequency in pandas resampling.

Which aggregation function would you use to get the total sum after resampling?

A mean()

B count()

C sum()

D max()

sum() adds all values in each resampled group.

Explain how to resample a daily time series to monthly frequency and calculate the average for each month using pandas.

Think about grouping data by month and then averaging.

Describe the difference between downsampling and upsampling in time series data and why filling missing values is important after upsampling.

Consider what happens to data points when changing frequency.