How to Get a Complete List of Duplicate Items in a Pandas DataFrame?

Get a List of All Duplicate Items in Pandas

In pandas, the duplicated method can be used to identify duplicate rows within a dataset based on specified columns. However, by default, it only returns the first occurrence of each duplicate. To obtain a comprehensive list, consider the following approaches:

Method #1: Filtering with the isin Method

This method involves two steps:

1. Extract the unique IDs from the duplicate rows using:

   <code class="python">ids = df[df.duplicated(cols='ID')]['ID']</code>

2. Utilize the isin method to filter all rows where the ID matches any of the duplicate IDs:

   <code class="python">df[ids.isin(ids[ids.duplicated()])].sort_values("ID")</code>

Method #2: Grouping with groupby

This approach uses the groupby operation to group the rows by the ID column and filter out groups with more than one row:

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

By using these methods, you can efficiently retrieve a complete list of duplicate items in your pandas DataFrame.

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