Скачать или смотреть How to Compare Columns from Two Different Data Frames in Python's Pandas

Learn how to effectively compare and merge columns from two Pandas DataFrames, ensuring you retain the values from the first DataFrame where applicable.
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How to Compare Columns from Two Different Data Frames in Python's Pandas

In the world of data manipulation, one of the challenges many users face is merging or comparing data from multiple DataFrames. This guide will address a common problem: How can you compare columns from two different DataFrames and ensure that the values from the first DataFrame are retained?

The Problem at Hand

You may have a scenario where you have two DataFrames with similar columns, and you wish to join them in such a way that the data from the first DataFrame overwrites data in the second DataFrame when the keys (in this case, 'Words') match. However, if a key exists in the second DataFrame but not in the first, it should be kept in the result.

DataFrames Overview

Let's look at our sample DataFrames for this explanation:

DataFrame 1 (df1):

Wordsxyzaardvark0.9990.9990.999abalone0.8880.8880.888abandon0.7770.7770.777DataFrame 2 (df2):

Wordsxyzaaaaahh0.1990.9290.993aardvark0.1110.1110.111abalone0.2220.2220.222abandon0.3330.3330.333zoo0.2320.1120.212zoom0.8420.6200.344zucchini0.9450.2650.745Expected Outcome

Given the above DataFrames, the desired outcome is a new DataFrame (df_res) that looks like this:

Wordsxyzaaaaahh0.1990.9290.993aardvark0.9990.9990.999abalone0.8880.8880.888abandon0.7770.7770.777zoo0.2320.1120.212zoom0.8420.6200.344zucchini0.9450.2650.745The Solution

Fortunately, the Pandas library provides a straightforward way to achieve this through a combination of methods. Follow these steps to arrive at the desired DataFrame:

Step-by-Step Guide

Append the DataFrames: Use the append() method to combine df1 into df2.

Remove Duplicates: Apply drop_duplicates() to keep the last occurrence of each 'Word' entry. The keep='last' argument ensures that the values from df1 are kept whenever there's a match.

Sorting and Resetting the Index: Finally, sort the DataFrame and reset the index for clarity.

Example Code

Here’s how it can be implemented in Python:

[[See Video to Reveal this Text or Code Snippet]]

Output

When you run the above code, you will get the following DataFrame:

Wordsxyzaaaaahh0.1990.9290.993aardvark0.9990.9990.999abalone0.8880.8880.888abandon0.7770.7770.777zoo0.2320.1120.212zoom0.8420.6200.344zucchini0.9450.2650.745Conclusion

By following the above steps, you not only solve the problem of comparing columns from two different DataFrames, but you also ensure that the values from the first DataFrame take precedence wherever applicable. This method is efficient, easy to understand, and utilizes the powerful capabilities of the Pandas library.

Happy data wrangling!