Aggregation functions (sum, mean, count) in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to calculate the total sales using sum.

Data Analysis Python

total_sales = df['sales'].[1]()

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

Amean

Bsum

Ccount

Dmax

Attempts:

3 left

💡 Hint

Common Mistakes

Using mean() instead of sum() which calculates average.

Using count() which counts entries, not sums values.

The sum() function adds all values in the 'sales' column to get the total sales.

2fill in blank

medium

Complete the code to find the average age using mean.

Data Analysis Python

average_age = df['age'].[1]()

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

Amin

Bsum

Ccount

Dmean

Attempts:

3 left

💡 Hint

Common Mistakes

Using sum() which adds values instead of averaging.

Using count() which counts entries, not averages.

The mean() function calculates the average of the 'age' column.

3fill in blank

hard

Fix the error in the code to count the number of entries in the 'product' column.

Data Analysis Python

product_count = df['product'].[1]()

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

Acount

Bsum

Cmean

Dmax

Attempts:

3 left

💡 Hint

Common Mistakes

Using sum() which adds values instead of counting.

Using mean() which calculates average, not count.

The count() function counts the number of non-missing entries in the 'product' column.

4fill in blank

hard

Fill both blanks to create a dictionary with total and average sales.

Data Analysis Python

sales_summary = {'total': df['sales'].[1](), 'average': df['sales'].[2]()}

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

Asum

Bmean

Ccount

Dmax

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up sum and mean functions.

Using count instead of sum or mean.

Use sum() to get total sales and mean() to get average sales.

5fill in blank

hard

Fill all three blanks to create a dictionary with count, total, and average of 'quantity'.

Data Analysis Python

quantity_stats = {'count': df['quantity'].[1](), 'total': df['quantity'].[2](), 'average': df['quantity'].[3]()}

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

Amean

Bsum

Ccount

Dmin

Attempts:

3 left

💡 Hint

Common Mistakes

Using mean for count or sum.

Mixing order of functions.

Use count() to count entries, sum() for total quantity, and mean() for average quantity.