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Learn how to concatenate multiple DataFrames in Python using their string names with the help of Pandas. This guide provides clear instructions and examples.
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How to Concat Multiple DataFrames Using Their Names in Python

When working with data in Python, particularly in data analysis with Pandas, you may encounter situations where you have several DataFrames that you want to combine into one. In a typical scenario, you would use the DataFrame objects directly within the pd.concat() function. However, what if you have a list of DataFrame names in string format and want to use those names to concatenate the DataFrames? This can seem a bit tricky at first, but it's definitely possible! Let's explore how you can achieve this.

The Challenge

As an example, consider you have two DataFrames defined as follows:

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

You may have a list of strings representing the names of these DataFrames:

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

If you attempt to concatenate the DataFrames by passing the list of strings directly to pd.concat() like this:

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

This will not work, since pd.concat() expects actual DataFrame objects, not strings. Fortunately, there’s a straightforward solution to this problem.

The Solution

To concatenate DataFrames by their string names, you can use the locals() function. This function returns a dictionary containing the current local symbol table. You can access variables defined in the local scope using their names as strings.

Here’s How to Do It

Follow this step-by-step process to concatenate DataFrames using their names in string format:

Define the DataFrames: Make sure your DataFrames are set up in your local environment.

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

Create a List of DataFrame Names: Prepare a list with the names of the DataFrames as strings.

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

Use locals() to Access the DataFrames: You can now concatenate the DataFrames by iterating over your list and using locals() to retrieve each DataFrame object.

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

Example Code

Here’s the complete code for clarity:

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

Output

The output will be a single DataFrame that combines the data from both df1 and df2:

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

Conclusion

In this guide, we explored how to concatenate multiple DataFrames using their string names in Python with Pandas. By utilizing the locals() function, we can dynamically access variables in our local scope, enabling us to concatenate DataFrames when their names are provided as strings. This approach not only increases the flexibility of your data manipulation tasks but also enhances your workflow efficiency. Happy coding!