Here are a few question-based titles that capture the essence of your article: **Short & Punchy:** * **How to Find ALL Duplicate Rows in Pandas?** * **Extracting Every Duplicate in a Pandas Data

How Do I Extract a Comprehensive List of Duplicate Items Utilizing Pandas in Python?

It is possible to encounter a situation where a dataset contains potential export issues, resulting in duplicate items. Identifying these duplicates is crucial for further manual comparison. However, the default pandas duplicated method returns only the first instance of a duplicate.

Method 1: Printing All Rows with Duplicate IDs

Using this method, you can identify and print all rows where the ID matches any of the IDs in the duplicated series.

<code class="python">import pandas as pd

df = pd.read_csv("dup.csv")
ids = df["ID"]
df[ids.isin(ids[ids.duplicated()])].sort_values("ID")</code>

Method 2: Grouping by ID

Alternatively, you can group the dataframe by the ID column and concatenate the groups with more than one row into a new dataframe.

<code class="python">pd.concat(g for _, g in df.groupby("ID") if len(g) > 1)</code>

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