Selecting columns by name in Pandas - Step-by-Step Execution

Concept Flow - Selecting columns by name

Start with DataFrame

↓

Specify column name(s)

↓

Access columns using df[column_name

↓

Return selected column(s) as Series or DataFrame

↓

Use or display selected data

Start with a DataFrame, specify the column name(s) you want, access them using the DataFrame syntax, and get the selected data back.

Execution Sample

Pandas

import pandas as pd

df = pd.DataFrame({
  'Name': ['Alice', 'Bob'],
  'Age': [25, 30],
  'City': ['NY', 'LA']
})

selected = df['Age']

This code creates a DataFrame and selects the 'Age' column by its name.

Execution Table

Step	Action	Code	Result Type	Output
1	Create DataFrame	df = pd.DataFrame({...})	DataFrame	{'Name': ['Alice', 'Bob'], 'Age': [25, 30], 'City': ['NY', 'LA']}
2	Select single column by name	selected = df['Age']	Series	[25, 30]
3	Select multiple columns by list	selected = df[['Name', 'City']]	DataFrame	{'Name': ['Alice', 'Bob'], 'City': ['NY', 'LA']}
4	Attempt select non-existing column	selected = df['Salary']	KeyError	Error: 'Salary' not found in columns
5	End	-	-	Selection complete or error raised

💡 Selection stops after returning the requested column(s) or raising an error if column not found.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	Final
df	undefined	{Name, Age, City}	{Name, Age, City}	{Name, Age, City}	{Name, Age, City}	{Name, Age, City}
selected	undefined	undefined	[25, 30]	{Name: ['Alice', 'Bob'], City: ['NY', 'LA']}	KeyError	KeyError or selected data

Key Moments - 2 Insights

Why does selecting a single column return a Series but selecting multiple columns returns a DataFrame?

Selecting one column like df['Age'] returns a Series because it's a single column of data. Selecting multiple columns with a list like df[['Name', 'City']] returns a DataFrame because it contains multiple columns. See execution_table rows 2 and 3.

What happens if you try to select a column name that does not exist?

Pandas raises a KeyError because the column is not found in the DataFrame. This is shown in execution_table row 4.

Visual Quiz - 3 Questions

Look at the execution table, what is the type of 'selected' after step 2?

A Series

B List

C DataFrame

D Dictionary

💡 Hint

Check the 'Result Type' column in execution_table row 2.

At which step does the code raise an error for selecting a non-existing column?

A Step 2

B Step 3

C Step 4

D Step 5

💡 Hint

Look for 'KeyError' in the 'Result Type' column in execution_table.

If you want to select columns 'Name' and 'Age' together, which code would you use?

A df['Name', 'Age']

B df[['Name', 'Age']]

C df['Name' & 'Age']

D df['Name'] + df['Age']

💡 Hint

See execution_table row 3 for selecting multiple columns.

Concept Snapshot

Selecting columns by name in pandas:
- Use df['col'] for single column (returns Series)
- Use df[['col1', 'col2']] for multiple columns (returns DataFrame)
- Column names must exist or KeyError occurs
- Useful to focus on specific data in DataFrame

Full Transcript

This visual execution shows how to select columns by name in pandas. We start with a DataFrame containing columns 'Name', 'Age', and 'City'. Selecting a single column like 'Age' returns a Series with that column's data. Selecting multiple columns using a list returns a DataFrame with those columns. If a column name does not exist, pandas raises a KeyError. The variable tracker shows how 'df' stays the same while 'selected' changes depending on the selection. Key moments clarify why single vs multiple column selection returns different types and what happens on errors. The quiz tests understanding of these steps and correct syntax for multiple column selection.