Скачать или смотреть How to Compare Two DataFrames in Python and Extract Row Values

Learn how to compare two pandas DataFrames in Python to extract and append values based on matching criteria, improving your data analysis skills.
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Comparing Two DataFrames in Python and Extracting Values

In the world of data analysis, working with multiple datasets is a common task. Often, you may need to compare two dataframes and extract specific values based on certain criteria. In this guide, we will tackle a specific problem where you need to extract values from one DataFrame based on matches in another.

The Problem

Imagine you have two DataFrames, df1 and df2. The goal is to append values from df2 into df1 based on matching id and name. Here’s the content of the two DataFrames:

DataFrame df1:

idnameprice_1price_2price_3price_41a2bDataFrame df2:

idnameprice_1price_2price_3price_41a101112112b114422553c76564534What you wish to achieve is to obtain a combined DataFrame that only contains rows from df1, enriched with respective prices from df2 where the ids and names match.

The Solution

To accomplish this task efficiently, you will use the merge function provided by the pandas library in Python. The merge function allows you to join two DataFrames based on common columns, which is precisely what we need in this case.

Steps to Follow

Import the necessary library:
First, ensure you have the pandas library imported in your Python environment.

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Create DataFrames:
Simulate your DataFrames df1 and df2 based on the provided example.

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Merge the DataFrames:
Now that you have both DataFrames ready, the next step is to merge df1 with df2 based on the id and name columns.

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View the Combined Output:
The merged DataFrame will contain only the rows from df2 that match id and name in df1.

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Expected Output

The final output will look like this:

idnameprice_1price_2price_3price_41a101112112b11442255This output shows that the rows from df1 are now populated with the corresponding prices from df2, based on the matching id and name.

Conclusion

By using the merge function in pandas, you can easily compare two DataFrames and extract relevant data based on specific criteria. This simple yet essential technique can be a great asset in your data manipulation toolkit. The ability to effectively manage and analyze data sets is crucial for any data-driven role.

Now that you understand how to compare DataFrames in Python with ease, you can apply this method to your own datasets and gain insights needed for your analyses.