drop_duplicates() for removal in Pandas - Step-by-Step Execution

Concept Flow - drop_duplicates() for removal

Start with DataFrame

↓

Call drop_duplicates()

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Check each row for duplicates

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Keep first occurrence, remove others

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Return new DataFrame without duplicates

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End

The function scans the DataFrame rows, keeps the first occurrence of duplicates, removes the rest, and returns a new DataFrame.

Execution Sample

Pandas

import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 2, 3],
    'B': ['x', 'y', 'y', 'z']
})

result = df.drop_duplicates()

This code creates a DataFrame with duplicate rows and removes duplicates using drop_duplicates().

Execution Table

Step	Row Index	Row Data	Is Duplicate?	Action	Resulting DataFrame Rows
1	0	{'A': 1, 'B': 'x'}	No	Keep	[0]
2	1	{'A': 2, 'B': 'y'}	No	Keep	[0, 1]
3	2	{'A': 2, 'B': 'y'}	Yes (duplicate of index 1)	Remove	[0, 1]
4	3	{'A': 3, 'B': 'z'}	No	Keep	[0, 1, 3]
5	-	-	-	-	Duplicates removed, final rows: [0, 1, 3]

💡 All rows checked; duplicates removed; final DataFrame has rows with indices 0, 1, and 3.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	Final
df	Original DataFrame with 4 rows	Same	Same	Same	Same	Same
result	Undefined	Undefined	Undefined	Undefined	Undefined	DataFrame with rows 0,1,3

Key Moments - 2 Insights

Why does drop_duplicates() keep the first occurrence and remove later ones?

drop_duplicates() by default keeps the first occurrence to preserve the original order and remove repeated rows seen later, as shown in execution_table rows 2 and 3.

Does drop_duplicates() modify the original DataFrame?

No, drop_duplicates() returns a new DataFrame without duplicates. The original DataFrame 'df' remains unchanged, as shown in variable_tracker.

Visual Quiz - 3 Questions

Look at the execution table, which row is identified as a duplicate and removed?

A Row index 3

B Row index 1

C Row index 2

D Row index 0

💡 Hint

Check the 'Is Duplicate?' column in execution_table row 3.

At which step does the resulting DataFrame first exclude a duplicate row?

A Step 2

B Step 3

C Step 4

D Step 1

💡 Hint

Look at the 'Action' column in execution_table rows to see when 'Remove' happens.

If drop_duplicates() was called with keep='last', which row would be removed instead?

A Row index 1

B Row index 0

C Row index 2

D Row index 3

💡 Hint

With keep='last', the first duplicate is removed, so check which row is the first duplicate in execution_table.

Concept Snapshot

drop_duplicates() removes duplicate rows from a DataFrame.
By default, it keeps the first occurrence and removes later duplicates.
It returns a new DataFrame; original stays unchanged.
You can specify columns or keep='last' to change behavior.
Useful to clean repeated data easily.

Full Transcript

We start with a DataFrame containing some duplicate rows. When we call drop_duplicates(), it checks each row in order. If a row is the first time it appears, it keeps it. If it finds a row that matches a previous one, it marks it as duplicate and removes it. The function returns a new DataFrame without those duplicates. The original DataFrame remains unchanged. This process helps clean data by removing repeated rows while keeping the first instance. You can also change which duplicates to keep by parameters, but by default, it keeps the first. This is shown step-by-step in the execution table where row index 2 is removed because it duplicates row index 1.