Rolling window calculations in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to calculate the rolling mean with a window size of 3.

Data Analysis Python

import pandas as pd

data = pd.Series([1, 2, 3, 4, 5])
rolling_mean = data.[1](3).mean()
print(rolling_mean)

Drag options to blanks, or click blank then click option'

Arolling_window

Brolling_mean

Crolling

Dwindow

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'rolling_mean' instead of 'rolling' causes an AttributeError.

Using 'window' or 'rolling_window' are not valid pandas methods.

The rolling method creates a rolling window object to perform calculations like mean.

2fill in blank

medium

Complete the code to calculate the rolling sum with a window size of 4.

Data Analysis Python

import pandas as pd

data = pd.Series([10, 20, 30, 40, 50])
rolling_sum = data.rolling([1]).sum()
print(rolling_sum)

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A4

B3

C2

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Using a window size smaller or larger than 4 changes the result.

Passing the window size as a string instead of an integer.

The window size is 4, so we pass 4 to the rolling method.

3fill in blank

hard

Fix the error in the code to calculate the rolling median with a window size of 3.

Data Analysis Python

import pandas as pd

data = pd.Series([5, 3, 8, 7, 10])
rolling_median = data.rolling(3).[1]()
print(rolling_median)

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Amedian

Bmean

Csum

Dmode

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'mean' calculates the average, not the median.

Using 'sum' adds values instead of finding the median.

Using 'mode' is not supported directly on rolling objects.

The median method calculates the median of values in the rolling window.

4fill in blank

hard

Fill both blanks to create a rolling window of size 2 and calculate the maximum value in each window.

Data Analysis Python

import pandas as pd

data = pd.Series([4, 7, 1, 8, 5])
rolling_max = data.[1]([2]).max()
print(rolling_max)

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Arolling

B3

C2

Dwindow

Attempts:

3 left

💡 Hint

Common Mistakes

Using window size 3 instead of 2 changes the output.

Using 'window' instead of 'rolling' causes an error.

Use rolling to create the window and pass 2 as the window size to calculate max over 2 elements.

5fill in blank

hard

Fill all three blanks to create a rolling window of size 3, calculate the minimum value, and assign it to a new variable.

Data Analysis Python

import pandas as pd

data = pd.Series([9, 2, 6, 3, 7])
rolling_min = data.[1]([2]).[3]()
print(rolling_min)

Drag options to blanks, or click blank then click option'

Arolling

B3

Cmin

Dmax

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'max' instead of 'min' returns the maximum values.

Using wrong window size changes the results.

Use rolling with window size 3 and call min() to get the minimum in each window.