info() for column types and nulls in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the info() method in pandas show about a DataFrame?

The info() method shows the number of rows, columns, data types of each column, and how many non-null values each column has.

beginner

How can you tell if a column has missing values using info()?

If the number of non-null values is less than the total number of rows, it means the column has missing (null) values.

beginner

What data types does info() display for DataFrame columns?

info() shows data types like int64, float64, object (for text), bool, and others.

beginner

Why is it useful to check column types and null counts with info() before analysis?

It helps you understand your data structure, find missing data, and decide how to clean or prepare data for analysis.

intermediate

What is the difference between info() and describe() in pandas?

info() shows data types and null counts, while describe() gives summary statistics like mean, min, max for numeric columns.

What does the info() method NOT show about a DataFrame?

A Number of non-null values per column

B Data types of columns

C Summary statistics like mean and median

D Total number of rows and columns

info() does not show summary statistics; that is done by describe().

If a column has 100 rows but info() shows 90 non-null values, what does this mean?

A The column has 10 missing values

B The column has 10 extra values

C The column is fully complete

D The column has 90 missing values

Non-null count less than total rows means missing values exist.

Which data type shown by info() usually means text data?

A bool

B float64

C int64

D object

object type in pandas usually means string or mixed data.

Why is it important to check for null values with info() before analysis?

A To identify missing data that may affect results

B To know the exact number of columns

C To change data types automatically

D To sort the DataFrame

Missing data can cause errors or bias, so identifying it early is important.

What is the default output of df.info()?

A A DataFrame with summary statistics

B A printout showing index range, columns, non-null counts, and data types

C A list of column names only

D A plot of missing values

info() prints a summary including index, columns, non-null counts, and data types.

Explain how you can use info() to find columns with missing data in a DataFrame.

Look at the non-null count vs total rows for each column.

Describe what information about column types and nulls you get from info() and why it matters.

Think about how data types affect operations and how missing data can impact results.