Скачать или смотреть Concatenating Pandas Columns Without Duplicates

Learn how to combine multiple columns in a Pandas DataFrame while avoiding duplicates. Follow our clear instructions and examples!
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Concatenating Pandas Columns Without Duplicates: A Step-by-Step Guide

When working with data in Pandas, you may encounter the need to concatenate multiple columns into one. This is particularly the case when you want a clean, consolidated view of your data. However, ensuring that you don't include duplicate entries from these columns can be tricky. In this guide, we'll walk through a scenario where you want to combine multiple columns while avoiding duplicates efficiently. Let’s dive right in!

Problem Statement

Imagine you have a dataset structured as follows:

col1col2col3PYTHON RDAPT 3NaNSTACK AVE APT 2-3APT 2-3NaNOVER ST 1/2UNIT 1/2UNIT 1/2FLOW RDNaNNaNYour goal is to create a new column, COMBINED, that combines values from col1, col2, and col3, omitting any duplicates. The expected output would look like this:

col1col2col3COMBINEDPYTHON RDAPT 3NaNPYTHON RD APT 3STACK AVE APT 2-3APT 2-3NaNSTACK AVE APT 2-3OVER ST 1/2UNIT 1/2UNIT 1/2OVER ST 1/2 UNIT 1/2FLOW RDNaNNaNFLOW RDSolution Overview

To solve this problem, we will use the apply method along with a custom function in Pandas. Here’s how to do it step-by-step.

Step 1: Initial Data Setup

First, let’s ensure we have our sample data in a DataFrame.

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Step 2: Define the Combine Function

To combine the values from the specified columns without duplicating entries, we will define a custom function. This function will help us check each word against the list of combined words to ensure there are no duplicates.

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Step 3: Applying the Function to the DataFrame

Now we will specify the columns we want to combine and apply our custom function using apply().

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Step 4: Final Output

Once you run the above code, your DataFrame will have the COMBINED column with the unique concatenated values:

col1col2col3COMBINEDPYTHON RDAPT 3PYTHON RD APT 3STACK AVE APT 2-3APT 2-3STACK AVE APT 2-3OVER ST 1/2UNIT 1/2UNIT 1/2OVER ST 1/2 UNIT 1/2FLOW RDFLOW RDConclusion

Successfully concatenating multiple columns in a Pandas DataFrame without duplicating entries is achievable with the right approach. In this guide, we outlined the steps to create a COMBINED column while maintaining uniqueness. This method is not only effective but also easily adjustable for datasets of varying sizes or structures.

We hope this guide proves useful in your data manipulation journey! Happy coding!