nunique() for unique counts in Pandas - Step-by-Step Execution

Concept Flow - nunique() for unique counts

Start with DataFrame

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Call nunique()

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Count unique values per column or axis

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Return counts as Series or scalar

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End

The nunique() function counts how many unique values exist in each column or row of a DataFrame and returns those counts.

Execution Sample

Pandas

import pandas as pd

df = pd.DataFrame({
  'A': [1, 2, 2, 3],
  'B': ['x', 'y', 'x', 'z']
})

counts = df.nunique()

This code creates a DataFrame and uses nunique() to count unique values in each column.

Execution Table

Step	Action	DataFrame State	nunique() Result
1	Create DataFrame	{'A':[1,2,2,3], 'B':['x','y','x','z']}
2	Call df.nunique()	Same as step 1	Counts unique values per column
3	Count unique in column 'A'	Values: [1,2,2,3]	3 (unique: 1,2,3)
4	Count unique in column 'B'	Values: ['x','y','x','z']	3 (unique: x,y,z)
5	Return result		A: 3, B: 3 (as Series)

💡 All columns processed, unique counts returned as Series.

Variable Tracker

Variable	Start	After nunique()
df	{'A':[1,2,2,3], 'B':['x','y','x','z']}	No change
counts	Not defined	A: 3, B: 3 (Series)

Key Moments - 2 Insights

Why does nunique() count 3 unique values in column 'A' when there are 4 rows?

Because nunique() counts distinct values, and column 'A' has values 1, 2, 2, 3. The value 2 repeats, so unique values are 1, 2, and 3, totaling 3. See execution_table rows 3 and 5.

What does nunique() return when called without arguments?

It returns a Series with the count of unique values for each column. See execution_table row 5.

Visual Quiz - 3 Questions

Look at the execution table, what is the unique count for column 'B' at step 4?

A 2

B 3

C 4

D 1

💡 Hint

Check execution_table row 4 where unique values in column 'B' are counted.

At which step does nunique() return the final counts as a Series?

A Step 5

B Step 2

C Step 3

D Step 4

💡 Hint

Look for the step where the result is returned, see execution_table row 5.

If column 'A' had all unique values, how would the count change in the variable_tracker?

A counts for 'A' would be 1

B counts for 'A' would be 3

C counts for 'A' would be 4

D counts for 'A' would be 0

💡 Hint

Unique count equals number of distinct values, see variable_tracker for current counts.

Concept Snapshot

pandas.DataFrame.nunique()
Counts unique values per column or row.
Returns a Series with counts.
Default axis=0 (columns).
Useful to find distinct values quickly.

Full Transcript

We start with a DataFrame containing columns 'A' and 'B'. Calling df.nunique() counts how many unique values each column has. For column 'A', values are 1, 2, 2, 3, so unique count is 3. For column 'B', values are 'x', 'y', 'x', 'z', so unique count is also 3. The function returns these counts as a Series. This helps us quickly see how many different values each column contains.