nunique() for unique counts in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the pandas method nunique() do?

It counts the number of unique (different) values in a Series or DataFrame column.

beginner

How do you count unique values in each column of a DataFrame using nunique()?

Use df.nunique(). It returns a Series with the count of unique values for each column.

intermediate

What parameter can you use with nunique() to include or exclude missing values?

The parameter dropna. By default, dropna=True excludes missing values from the count. Set dropna=False to include them.

beginner

How to count unique values in a single pandas Series?

Call nunique() directly on the Series, like series.nunique().

beginner

Why is nunique() useful in data analysis?

It helps quickly understand how many different values exist in data columns, which is useful for data cleaning and exploration.

What does df.nunique() return?

A Number of rows in the DataFrame

B Count of unique values per column

C Sum of all values in the DataFrame

D Mean of each column

df.nunique() returns the count of unique values for each column in the DataFrame.

How do you include missing values in the unique count using nunique()?

A Use <code>include_na=True</code>

B Set <code>dropna=True</code>

C Set <code>dropna=False</code>

D Missing values are always included

Use dropna=False to include missing values in the unique count.

Which pandas object can you call nunique() on?

A Both Series and DataFrames

B Only Series

C Only DataFrames

D Only numpy arrays

nunique() works on both pandas Series and DataFrames.

What is the default behavior of nunique() regarding missing values?

A Includes missing values in count

B Replaces missing values with zero

C Raises an error if missing values exist

D Excludes missing values from count

By default, nunique() excludes missing values (dropna=True).

If a column has values [1, 2, 2, 3, NaN], what does nunique() return by default?

A 3

B 2

C 5

D 4

By default, missing values are excluded, so unique values are 1, 2, and 3 → count is 3.

Explain how to use nunique() to find unique counts in a DataFrame and how to handle missing values.

Think about the default behavior and how to change it.

Describe a real-life example where counting unique values with nunique() helps in data analysis.

Consider something like counting unique customers or product categories.