crosstab() for cross-tabulation in Pandas - Step-by-Step Execution

Concept Flow - crosstab() for cross-tabulation

Input Data

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Select two categorical variables

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Count occurrences of each combination

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Create frequency table (cross-tabulation)

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Display table showing counts per category pair

The crosstab function takes two categorical variables and counts how often each pair occurs, showing the result as a table.

Execution Sample

Pandas

import pandas as pd

data = {'Gender': ['Male', 'Female', 'Female', 'Male', 'Male'],
        'Preference': ['A', 'B', 'A', 'B', 'A']}
df = pd.DataFrame(data)

result = pd.crosstab(df['Gender'], df['Preference'])
print(result)

This code counts how many males and females prefer categories A or B and shows the counts in a table.

Execution Table

Step	Action	Gender	Preference	Count	Cross-tab Table State
1	Read first row	Male	A	1	{'Male': {'A': 1}}
2	Read second row	Female	B	1	{'Male': {'A': 1}, 'Female': {'B': 1}}
3	Read third row	Female	A	1	{'Male': {'A': 1}, 'Female': {'B': 1, 'A': 1}}
4	Read fourth row	Male	B	1	{'Male': {'A': 1, 'B': 1}, 'Female': {'B': 1, 'A': 1}}
5	Read fifth row	Male	A	2	{'Male': {'A': 2, 'B': 1}, 'Female': {'B': 1, 'A': 1}}
6	Build final table	-	-	-	Preference A B Gender Female 1 1 Male 2 1

💡 All rows processed, cross-tabulation table completed

Variable Tracker

Variable	Start	After 1	After 2	After 3	After 4	After 5	Final
Cross-tab dict	{}	{'Male': {'A': 1}}	{'Male': {'A': 1}, 'Female': {'B': 1}}	{'Male': {'A': 1}, 'Female': {'B': 1, 'A': 1}}	{'Male': {'A': 1, 'B': 1}, 'Female': {'B': 1, 'A': 1}}	{'Male': {'A': 2, 'B': 1}, 'Female': {'B': 1, 'A': 1}}	Final table as shown

Key Moments - 2 Insights

Why does the count for Male and Preference A increase on the last row?

Because the last row has Gender 'Male' and Preference 'A', which already appeared once, so the count increments from 1 to 2 as shown in execution_table row 5.

What happens if a category pair does not appear in the data?

It will not appear in the table or will show zero count. For example, if no Female prefers 'C', that cell is zero or missing in the cross-tab.

Visual Quiz - 3 Questions

Look at the execution table, what is the count for Female and Preference B after step 2?

A 1

B 0

C 2

D Not counted yet

💡 Hint

Check execution_table row 2 where Female and B first appear with count 1.

At which step does the count for Male and Preference B first appear?

A Step 1

B Step 4

C Step 3

D Step 5

💡 Hint

Look at execution_table row 4 where Male and B are first counted.

If a new row with Gender 'Female' and Preference 'A' is added, how will the count change?

A Male and A count becomes 3

B Female and A count becomes 1

C Female and A count becomes 2

D No change

💡 Hint

Refer to variable_tracker showing counts increment when same pair appears again.

Concept Snapshot

pandas.crosstab(index, columns) creates a frequency table.
It counts occurrences of each pair of categories.
Input: two categorical series.
Output: DataFrame with counts.
Useful for quick category relationship summaries.

Full Transcript

The crosstab function in pandas takes two categorical variables and counts how many times each combination occurs. We start with input data containing categories like Gender and Preference. For each row, crosstab counts the pair and updates the frequency table. For example, when it reads a row with Male and Preference A, it adds 1 to that cell. If the same pair appears again, the count increases. After processing all rows, it shows a table with counts for each category pair. This helps us see relationships between categories quickly.