info() for column types in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the info() method show about a DataFrame's columns?

The info() method shows the number of non-null values, the data type of each column, and the memory usage of the DataFrame.

beginner

How can info() help you understand missing data in your dataset?

By showing the count of non-null values per column, info() helps identify columns with missing data because the count will be less than the total rows.

beginner

What are some common data types you might see in the output of info()?

Common data types include int64 for integers, float64 for decimals, object for text or mixed types, and bool for True/False values.

intermediate

Why is it useful to check the memory usage shown by info()?

Checking memory usage helps you understand how much RAM your DataFrame uses, which is important for working efficiently with large datasets.

beginner

How do you call info() on a DataFrame named df?

You call it by typing df.info(). This will print the summary of the DataFrame's columns, types, and memory.

What does df.info() NOT show?

A Statistical summary like mean or median

B Data types of columns

C Memory usage of the DataFrame

D Number of non-null values per column

info() does not show statistics like mean or median; it shows data types, non-null counts, and memory usage.

If a column has fewer non-null values than total rows, what does it mean?

A The column has no missing values

B The column is numeric

C The column has missing values

D The column is categorical

Fewer non-null values than total rows means some data is missing in that column.

Which data type in info() output usually represents text data?

A int64

B float64

C bool

D object

The object type usually means text or mixed types in pandas.

How do you get more detailed memory usage info from info()?

A Use <code>df.describe()</code>

B Use <code>df.info(memory_usage='deep')</code>

C Use <code>df.head()</code>

D Use <code>df.memory()</code>

Passing memory_usage='deep' to info() gives a more accurate memory usage.

What is the main purpose of using info() on a DataFrame?

A To get a quick overview of data types and missing values

B To plot graphs

C To sort the data

D To change column names

info() is used to quickly see data types, non-null counts, and memory usage.

Explain how the info() method helps you understand the structure of a DataFrame.

Think about what you want to know before analyzing data.

Describe how you can identify missing data in a DataFrame using info().

Missing data means some entries are empty or null.