pivot_table() for summarization in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of the pivot_table() function in pandas?

The pivot_table() function is used to summarize and aggregate data in a DataFrame by creating a new table that groups data by one or more keys and applies aggregation functions like sum, mean, or count.

beginner

Which parameters are commonly used in pivot_table()?

• data: The DataFrame to summarize.
• index: Column(s) to group by on rows.
• columns: Column(s) to group by on columns.
• values: Column(s) to aggregate.
• aggfunc: Aggregation function like sum, mean, or count.

intermediate

How does pivot_table() handle missing values by default?

By default, pivot_table() fills missing values with NaN. You can change this behavior using the fill_value parameter to replace missing values with a specific value like 0.

intermediate

What is the difference between pivot() and pivot_table()?

pivot() reshapes data without aggregation and requires unique index/column pairs. pivot_table() allows aggregation and can handle duplicate entries by applying aggregation functions.

beginner

Write a simple example of using pivot_table() to find the average sales per product category.

Example:<br><pre>import pandas as pd

data = {'Category': ['A', 'A', 'B', 'B'], 'Sales': [100, 150, 200, 250]}
df = pd.DataFrame(data)

pivot = df.pivot_table(index='Category', values='Sales', aggfunc='mean')
print(pivot)</pre>

What does the aggfunc parameter in pivot_table() specify?

A The columns to use as column labels

B The columns to use as row labels

C The aggregation function to apply to grouped data

D The DataFrame to summarize

The aggfunc parameter tells pivot_table() how to combine data, like using sum, mean, or count.

Which parameter in pivot_table() controls the rows of the new table?

A index

B values

C columns

D aggfunc

The index parameter sets which column(s) become the rows in the pivot table.

If your data has duplicate entries for the same index and column, which function should you use to summarize it?

A pivot()

B groupby()

C merge()

D pivot_table()

pivot_table() can handle duplicates by aggregating them, unlike pivot().

What will pivot_table() fill missing values with by default?

A NaN

B Empty string

C 0

D Mean of the column

By default, missing values are shown as NaN unless fill_value is set.

Which of these is NOT a valid aggregation function for aggfunc?

A mean

B sort

C count

D sum

sort is not an aggregation function; it is used for ordering data.

Explain how you would use pivot_table() to summarize sales data by region and product.

Think about grouping rows by region and columns by product, then summarizing sales.

Describe the difference between pivot() and pivot_table() and when to use each.

Consider if your data has duplicates or needs aggregation.