Pattern matching with str.contains in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the str.contains() method do in pandas?

It checks if each string in a pandas Series contains a specified pattern or substring, returning a Series of True or False values.

beginner

How can you make str.contains() case insensitive?

By setting the parameter case=False, the method ignores case when searching for the pattern.

intermediate

What happens if str.contains() encounters a missing value (NaN) in the Series?

By default, it returns NaN for that position, but you can set na=False to treat missing values as not matching the pattern.

beginner

How do you use str.contains() to filter rows in a DataFrame where a column contains a specific word?

Use it inside boolean indexing like df[df['column'].str.contains('word', na=False)] to keep rows where 'word' appears in 'column'.

intermediate

Can str.contains() use regular expressions for pattern matching?

Yes, by default it treats the pattern as a regular expression, allowing complex pattern matching. You can disable this with regex=False.

What does str.contains('cat') return when applied to a pandas Series?

A A Series of True/False indicating if 'cat' is in each string

B A list of strings containing 'cat'

C The count of 'cat' occurrences

D The original Series unchanged

It returns a Series of True or False values showing if 'cat' is found in each string.

How do you ignore case when using str.contains()?

A Set <code>case=False</code>

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

C Set <code>case=True</code>

D Use <code>lower()</code> on the Series first

Setting case=False makes the search case insensitive.

What parameter do you use to treat NaN values as False in str.contains()?

A ignore_na=True

B na=True

C fillna=False

D na=False

The na=False parameter treats missing values as not matching the pattern.

By default, does str.contains() treat the pattern as a regular expression?

A Only if the pattern is a string

B No

C Yes

D Only if <code>regex=True</code> is set

By default, str.contains() uses regex for pattern matching.

Which of these filters a DataFrame to rows where 'name' column contains 'John'?

A df[df['name'].contains('John')]

B df[df['name'].str.contains('John', na=False)]

C df[df['name'].str.match('John')]

D df[df['name'].str.find('John')]

Use str.contains() with na=False inside boolean indexing to filter rows.

Explain how to use str.contains() to find rows in a DataFrame where a column includes a certain substring, including how to handle missing values and case sensitivity.

Think about filtering with True/False and controlling how missing data and letter case affect the search.

Describe the role of regular expressions in str.contains() and how to disable them if you want a simple substring search.

Consider how regex allows patterns and how to turn it off for plain text matching.