Extracting with str.extract (regex) in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

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

It extracts groups from strings in a pandas Series or DataFrame column using a regular expression (regex). It returns the matched groups as new columns.

beginner

How do you specify which part of the string to extract using str.extract()?

You use parentheses () in the regex pattern to define capture groups. Only the text matched inside these groups is extracted.

intermediate

What type of object does str.extract() return when extracting one group vs multiple groups?

If one group is extracted, it returns a Series. If multiple groups are extracted, it returns a DataFrame with one column per group.

beginner

Why is it useful to use str.extract() with regex in data cleaning?

It helps pull out specific parts of messy text data, like extracting dates, codes, or names, making the data easier to analyze.

intermediate

Example: What does df['col'].str.extract(r'(\d{3})-(\d{2})') extract?

It extracts two groups of digits separated by a dash: the first group with exactly 3 digits, and the second group with exactly 2 digits, returning them as two columns.

What symbol in regex defines a capture group for str.extract()?

A ()

B []

C {}

D <>

Parentheses () define capture groups in regex, which str.extract() uses to extract parts of strings.

If your regex has two capture groups, what does str.extract() return?

A A Series with one column

B A DataFrame with two columns

C A list of strings

D A single string

Two capture groups produce a DataFrame with one column per group.

Which pandas object can you use str.extract() on?

A DataFrame

B Series

C Both DataFrame and Series

D null

str.extract() is used on pandas Series (single columns). For DataFrames, you apply it on a column (Series).

What happens if the regex pattern does not match any part of the string?

A Returns the original string

B Returns NaN for that row

C Raises an error

D Returns an empty string

If no match is found, str.extract() returns NaN for that row.

Which of these regex patterns extracts a 4-digit year from a string?

A r'(\d{4})'

B r'\d{2}'

C r'(\w{4})'

D r'\d{5}'

The pattern r'(\d{4})' captures exactly 4 digits, suitable for a year.

Explain how you would use str.extract() to pull out an area code from phone numbers in a pandas Series.

Think about the pattern for area codes like three digits inside parentheses or at the start.

Describe the difference in output when extracting one group versus multiple groups with str.extract().

Consider how pandas organizes extracted data based on number of groups.