apply() on rows (axis=1) in Pandas - Step-by-Step Execution

Concept Flow - apply() on rows (axis=1)

Start with DataFrame

↓

Define function to apply

↓

Call apply() with axis=1

↓

Function runs on each row

↓

Collect results into Series or DataFrame

↓

Use or assign results

This flow shows how apply() runs a function on each row of a DataFrame when axis=1 is set.

Execution Sample

Pandas

import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6]
})

result = df.apply(lambda row: row['A'] + row['B'], axis=1)

This code adds values in columns A and B for each row using apply() with axis=1.

Execution Table

Step	Row Index	Row Data	Function Applied	Result
1	0	{'A': 1, 'B': 4}	1 + 4	5
2	1	{'A': 2, 'B': 5}	2 + 5	7
3	2	{'A': 3, 'B': 6}	3 + 6	9
4	-	-	All rows processed	Series([5, 7, 9])

💡 All rows processed, apply() returns a Series with results.

Variable Tracker

Variable	Start	After 1	After 2	After 3	Final
row	None	A 1 B 4 Name: 0, dtype: int64	A 2 B 5 Name: 1, dtype: int64	A 3 B 6 Name: 2, dtype: int64	None
result	Empty	5	7	9	Series([5, 7, 9])

Key Moments - 3 Insights

Why do we use axis=1 in apply()?

axis=1 tells apply() to run the function on each row, not on each column. See execution_table steps 1-3 where each row is processed.

What type of object is passed to the function inside apply()?

Each row is passed as a Series object representing that row's data, as shown in execution_table column 'Row Data'.

What does apply() return when used with axis=1?

It returns a Series with the function results for each row, as shown in execution_table step 4.

Visual Quiz - 3 Questions

Look at the execution_table, what is the result of the function applied on row index 1?

A 5

B 9

C 7

D 6

💡 Hint

Check the 'Result' column for row index 1 in execution_table step 2.

At which step does apply() finish processing all rows?

A Step 3

B Step 4

C Step 2

D Step 1

💡 Hint

Look at the exit_note and the last row in execution_table.

If axis=0 was used instead of axis=1, how would the function be applied?

A On each column

B On the entire DataFrame at once

C On each row

D It would cause an error

💡 Hint

axis=0 means apply function on columns, not rows.

Concept Snapshot

apply() with axis=1 runs a function on each row of a DataFrame.
The function receives a row as a Series.
Results are collected into a Series or DataFrame.
Use axis=1 to operate row-wise, axis=0 for column-wise.
Common for row-based calculations or transformations.

Full Transcript

We start with a DataFrame containing columns A and B. We define a function that adds the values in columns A and B for each row. Using apply() with axis=1, the function runs on each row one by one. For row 0, values 1 and 4 are added to get 5. For row 1, 2 and 5 sum to 7. For row 2, 3 and 6 sum to 9. The results are collected into a Series with values 5, 7, and 9. The key is axis=1 tells apply() to work row-wise. Each row is passed as a Series to the function. The final output is a Series with the function results for each row.