Aggregation functions (sum, mean, count) in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

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What does the sum aggregation function do in data analysis?

The sum function adds up all the values in a column or list to give a total amount.

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How would you describe the mean aggregation function?

The mean function calculates the average value by adding all numbers and dividing by how many numbers there are.

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What does the count aggregation function measure?

The count function counts how many items or rows are in a dataset or column, ignoring empty or missing values.

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In Python's pandas library, which method would you use to get the sum of a DataFrame column named 'sales'?

You would use df['sales'].sum() to get the total sales amount.

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Why are aggregation functions useful in data analysis?

They help summarize large data sets into simple numbers like totals, averages, or counts, making it easier to understand the data.

Which aggregation function would you use to find the average value of a column?

A mean

B sum

C count

D max

The mean function calculates the average by dividing the sum of values by the number of values.

What does the count function do when applied to a data column?

A Adds all values

B Finds the highest value

C Calculates the average

D Counts the number of non-empty entries

Count returns how many non-empty entries are in the column.

If you want to know the total sales from a list of sales numbers, which function should you use?

A mean

B count

C sum

D min

Sum adds all sales numbers to give the total.

In pandas, how do you get the count of rows in a DataFrame column 'age'?

A df['age'].count()

B df['age'].sum()

C df['age'].mean()

D df['age'].max()

The count() method counts non-missing values in the 'age' column.

Which aggregation function ignores missing or empty values when calculating?

A mean

B All of the above

C count

D sum

Sum, mean, and count in pandas all ignore missing values by default.

Explain in your own words what the sum, mean, and count aggregation functions do and give a simple example for each.

Think about adding numbers, finding average, and counting items.

Describe how aggregation functions help when working with large datasets.

Imagine you have a big list of numbers and want just one number to describe it.