Pattern matching with str.contains in Data Analysis Python - Step-by-Step Execution

Concept Flow - Pattern matching with str.contains

Start with DataFrame

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Call str.contains(pattern)

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Check each string for pattern

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Return Boolean Series

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Use Boolean Series to filter DataFrame

We start with a DataFrame, use str.contains to check each string for a pattern, get a True/False result, then filter rows based on that.

Execution Sample

Data Analysis Python

import pandas as pd

df = pd.DataFrame({'Name': ['Alice', 'Bob', 'Charlie', 'David']})
mask = df['Name'].str.contains('a')
result = df[mask]

This code finds rows where the 'Name' column contains the letter 'a' (case-sensitive) and filters the DataFrame.

Execution Table

Step	Row Index	Name Value	Check 'a' in Name	Boolean Result	Filtered Rows
1	0	Alice	No (uppercase 'A' but no lowercase 'a')	False	Exclude
2	1	Bob	No	False	Exclude
3	2	Charlie	Yes ('a' in 'Charlie')	True	Include
4	3	David	Yes ('a' in 'David')	True	Include
5	-	-	-	-	Filter applied: rows 2,3 included; rows 0,1 excluded

💡 All rows checked; filtering done based on Boolean mask.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	Final
mask	None	False	False	True	True	[False, False, True, True]
result	None	Row 0 excluded	Row 1 excluded	Row 2 included	Row 3 included	Filtered DataFrame with rows 2,3

Key Moments - 3 Insights

Why does 'Alice' return False even though it starts with uppercase 'A'?

str.contains is case-sensitive by default, and 'Alice' has no lowercase 'a' (only uppercase 'A'), so it does not match. See execution_table step 1.

What happens if the pattern is not found in a string?

The Boolean result is False, so that row is excluded from the filtered DataFrame. See execution_table step 2 for 'Bob'.

How does the Boolean mask help filter the DataFrame?

The mask is a list of True/False values for each row. True means include the row, False means exclude. See execution_table final step.

Visual Quiz - 3 Questions

Look at the execution_table, what is the Boolean result for 'Charlie' at step 3?

A True

B Error

C False

D None

💡 Hint

Check the 'Boolean Result' column at step 3 in execution_table.

At which step does the condition 'a' not found in the Name?

A Step 1

B Step 3

C Step 2

D Step 4

💡 Hint

Look for 'False' in the 'Boolean Result' column in execution_table.

If we add case=False to str.contains, what would happen to 'Alice'?

A It would be False

B It would be True

C It would cause an error

D It would be None

💡 Hint

Case-insensitive matching includes uppercase and lowercase letters; see variable_tracker mask values.

Concept Snapshot

Use str.contains('pattern') on a string column to get a Boolean mask.
This mask shows True where the pattern is found, False otherwise.
By default, matching is case-sensitive.
Use the mask to filter rows in a DataFrame.
Add case=False for case-insensitive matching.

Full Transcript

We start with a DataFrame containing names. We use str.contains to check if each name has the letter 'a'. This returns a list of True or False values, one for each row. True means the pattern is found, False means it is not. We then use this list to keep only the rows where the pattern is found. For example, 'Alice' has no lowercase 'a' (only uppercase 'A'), so it returns False. 'Bob' does not have 'a', so it returns False and is excluded. 'Charlie' and 'David' have lowercase 'a', so they return True and are included. This way, we filter the DataFrame to only include names with lowercase 'a'.