How do I get a list of all the duplicate items using pandas in python?

How to Get a List of All Duplicate Items Using Pandas in Python

Do you have a list of items and suspect there are some duplicates? Do you need to compare these duplicates manually? If you're using pandas in Python, you might have come across the duplicated method, which only returns the first duplicate item. But what if you want to get all the duplicates and not just the first one?

In this guide, we'll explore how to use pandas in Python to get a list of all duplicate items. We'll address the common issue of the duplicated method returning only the first duplicate and provide a easy solution to obtain all the duplicates. So, let's dive in!

The Problem

Let's start by understanding the problem. We have a dataset with multiple columns, and we want to find all the duplicate items in a specific column. For example, let's say we have a dataset that looks like this:

ID,ENROLLMENT_DATE,TRAINER_MANAGING,TRAINER_OPERATOR,FIRST_VISIT_DATE
1536D,12-Feb-12,"06DA1B3-Lebanon NH",,15-Feb-12
F15D,18-May-12,"06405B2-Lebanon NH",,25-Jul-12
8096,8-Aug-12,"0643D38-Hanover NH","0643D38-Hanover NH",25-Jun-12
A036,1-Apr-12,"06CB8CF-Hanover NH","06CB8CF-Hanover NH",9-Aug-12
8944,19-Feb-12,"06D26AD-Hanover NH",,4-Feb-12
1004E,8-Jun-12,"06388B2-Lebanon NH",,24-Dec-11
11795,3-Jul-12,"0649597-White River VT","0649597-White River VT",30-Mar-12
30D7,11-Nov-12,"06D95A3-Hanover NH","06D95A3-Hanover NH",30-Nov-11
3AE2,21-Feb-12,"06405B2-Lebanon NH",,26-Oct-12
B0FE,17-Feb-12,"06D1B9D-Hartland VT",,16-Feb-12
127A1,11-Dec-11,"064456E-Hanover NH","064456E-Hanover NH",11-Nov-12
161FF,20-Feb-12,"0643D38-Hanover NH","0643D38-Hanover NH",3-Jul-12
A036,30-Nov-11,"063B208-Randolph VT","063B208-Randolph VT",
475B,25-Sep-12,"06D26AD-Hanover NH",,5-Nov-12
151A3,7-Mar-12,"06388B2-Lebanon NH",,16-Nov-12
CA62,3-Jan-12,,,
D31B,18-Dec-11,"06405B2-Lebanon NH",,9-Jan-12
20F5,8-Jul-12,"0669C50-Randolph VT",,3-Feb-12
8096,19-Dec-11,"0649597-White River VT","0649597-White River VT",9-Apr-12
14E48,1-Aug-12,"06D3206-Hanover NH",,
177F8,20-Aug-12,"063B208-Randolph VT","063B208-Randolph VT",5-May-12
553E,11-Oct-12,"06D95A3-Hanover NH","06D95A3-Hanover NH",8-Mar-12
12D5F,18-Jul-12,"0649597-White River VT","0649597-White River VT",2-Nov-12
C6DC,13-Apr-12,"06388B2-Lebanon NH",,
11795,27-Feb-12,"0643D38-Hanover NH","0643D38-Hanover NH",19-Jun-12
17B43,11-Aug-12,,,22-Oct-12
A036,11-Aug-12,"06D3206-Hanover NH",,19-Jun-12

Our goal is to identify all the duplicate entries in the ID column.

The Existing Code

To solve this problem, the user originally tried using the following code:

df_bigdata_duplicates = df_bigdata[df_bigdata.duplicated(cols='ID')]

However, this code only returns the first duplicate item. In our dataset example, it would only return the first A036 entry and the first 11795 entry.

The Solution

To obtain all the duplicate items in the ID column, we can use the duplicated method differently. Here's the updated code:

df_bigdata_duplicates = df_bigdata[df_bigdata.duplicated(subset='ID', keep=False)]

Let's break this down:

• subset='ID': This specifies that we only want to consider the ID column for duplicates.

• keep=False: By setting this parameter to False, we keep all duplicate items instead of keeping the first occurrence and marking the rest as duplicates.

With this updated code, we will get all the duplicate entries for the ID column, including the three A036 entries and the two 11795 entries in our dataset example.

Conclusion

Finding duplicate items in a dataset can be essential for data analysis and quality control. Pandas provides a simple yet powerful method, duplicated, to identify duplicates. By understanding the parameters and options of this method, we can easily obtain all the duplicates instead of just the first duplicate item.

Next time you encounter a duplicate item problem while working with pandas in Python, remember to use the duplicated method with the subset and keep parameters to get the complete list of duplicates.

I hope this guide was helpful in solving your duplicate item issue. If you have any questions or other pandas-related problems, feel free to leave a comment below. Let's harness the power of pandas together!

🚀 Happy coding! 🐼💻

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Disclaimer: The dataset used in this example is fictional and for demonstration purposes only.