Creating new columns in Pandas - Visual Walkthrough

Concept Flow - Creating new columns

Start with DataFrame

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Define new column values

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Assign new column to DataFrame

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DataFrame updated with new column

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End

We start with a DataFrame, define values for a new column, assign it, and update the DataFrame.

Execution Sample

Pandas

import pandas as pd

df = pd.DataFrame({'A': [1, 2, 3]})
df['B'] = df['A'] * 2
print(df)

This code creates a new column 'B' by doubling the values in column 'A'.

Execution Table

Step	Action	DataFrame State	New Column 'B' Values
1	Create DataFrame with column 'A'	{'A': [1, 2, 3]}	N/A
2	Calculate new column 'B' as df['A'] * 2	Same as step 1	[2, 4, 6]
3	Assign new column 'B' to DataFrame	{'A': [1, 2, 3], 'B': [2, 4, 6]}	[2, 4, 6]
4	Print DataFrame	Displays both columns	[2, 4, 6]

💡 New column 'B' added successfully; execution ends after printing DataFrame.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
df	undefined	{'A': [1, 2, 3]}	{'A': [1, 2, 3]}	{'A': [1, 2, 3], 'B': [2, 4, 6]}	{'A': [1, 2, 3], 'B': [2, 4, 6]}
df['B']	undefined	undefined	[2, 4, 6]	[2, 4, 6]	[2, 4, 6]

Key Moments - 2 Insights

Why does the new column 'B' appear only after assignment and not before?

Because calculating df['A'] * 2 creates a Series but does not add it to df until we assign it as df['B'] (see execution_table step 2 vs 3).

Can we create a new column using a list of values directly?

Yes, as long as the list length matches the DataFrame rows. Assignment like df['B'] = [2,4,6] works (similar to step 3).

Visual Quiz - 3 Questions

Look at the execution table at step 2, what are the values calculated for the new column 'B'?

A N/A

B [1, 2, 3]

C [2, 4, 6]

D [3, 6, 9]

💡 Hint

Check the 'New Column 'B' Values' column in execution_table row for step 2.

At which step does the DataFrame actually get updated with the new column 'B'?

A Step 1

B Step 3

C Step 2

D Step 4

💡 Hint

Look at the 'DataFrame State' column in execution_table to see when 'B' appears.

If we assign df['B'] = [10, 20], what will happen?

A Error due to length mismatch

B New column 'B' with values [10, 20] added

C Column 'B' will have NaN for missing rows

D Column 'B' will be empty

💡 Hint

Recall that the list length must match DataFrame rows (see key_moments about list length).

Concept Snapshot

Creating new columns in pandas:
- Use df['new_col'] = values
- Values can be Series, list, or calculations
- Length of values must match DataFrame rows
- New column appears after assignment
- Useful for adding derived data

Full Transcript

We start with a DataFrame having one column 'A'. We calculate new values by doubling 'A' and store them temporarily. Only after assigning these values to df['B'] does the DataFrame update to include the new column. Printing shows both columns. Beginners often wonder why the new column isn't visible before assignment and must ensure the new column values match the DataFrame length. This process allows adding new data columns easily.