Find duplicate rows

Understanding values · I17 · 8 MIN

Count repeated records without removing anything.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeAdapt a requirement
TransferChoose and combine

Understand the idea

duplicated returns one True/False flag per row. By default it compares every column’s values, ignoring the index; it does not remove rows.

Illustration · not the exercise output

A small example

Suppose the complete rows are A, B, A, A. A occurs three times; B occurs once. Read the flags in the same row order.

Same rows, different keep choices
Row	`"first"`	`"last"`	`False`
A · first	False	True	True
B · unique	False	False	False
A · second	True	True	True
A · third	True	False	True

Follow the code

Apply the idea to the supplied table. Read from top to bottom; the final line displays the result.

df.duplicated().sum()

What each part does

df.duplicated(): Mark later copies of complete rows True; the first copy stays False.
.sum(): Count those True flags to get the number of extra copies.

Other choices for later exercises

keep="last": Exempt the last copy instead of the first.
keep=False: Mark every copy of a repeated row, including the first.
df[mask]: Show the rows whose duplicate flags are True.

Your inputs

The editable setup on the right creates df. Run executes the setup and your work from top to bottom.

Messy café orders · 8 synthetic rows
order	drink	size	price	tip	date
101	" latte "	LARGE	6.20	1	2026-06-01
102	TEA	small	3.10	0.5	2026-06-02
103	" mocha "	LARGE	oops	None	not a date
104	Latte	Small	None	0.8	2026-06-04
104	Latte	Small	None	0.8	2026-06-04
105	"tea "	SMALL	4.20	0.6	2026-06-05
106	ESPRESSO	small	2.50	0.2	2026-06-06
107	" mocha"	large	6.80	1.5	2026-06-07

Your task · Follow

Using df, count extra copies of exact duplicate rows, excluding the first occurrence of each repeated row.
Display one number.
Use duplicated().

Hint

duplicated marks the extra copies only by default, not the first occurrence.

Reveal solution

One way to do it. Keep any supplied setup in the editor and use this in the Your work section.

df.duplicated().sum()

Your task · Follow

Using df, count extra copies of exact duplicate rows, excluding the first occurrence of each repeated row.
Display one number.
Use duplicated().

YOUR PYTHON

Tab: indent · Shift+Tab: outdent · Esc, then Tab: leave editor

# Supplied setup — editable
import pandas as pd

data = {
    "order": [101, 102, 103, 104, 104, 105, 106, 107],
    "drink": [
        " latte ",
        "TEA",
        " mocha ",
        "Latte",
        "Latte",
        "tea ",
        "ESPRESSO",
        " mocha",
    ],
    "size": ["LARGE", "small", "LARGE", "Small", "Small", "SMALL", "small", "large"],
    "price": ["6.20", "3.10", "oops", None, None, "4.20", "2.50", "6.80"],
    "tip": [1, 0.5, None, 0.8, 0.8, 0.6, 0.2, 1.5],
    "date": [
        "2026-06-01",
        "2026-06-02",
        "not a date",
        "2026-06-04",
        "2026-06-04",
        "2026-06-05",
        "2026-06-06",
        "2026-06-07",
    ],
}

df = pd.DataFrame(data)

# Your work
# Build the requested result from the given table
result = ____
result

Each run executes all editor code in a fresh Python session. Display a value by leaving it on the final line.

Python starts when you open a lesson.

Output

Run your code to see what Python returns.