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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