Effortlessly Concatenate Rows of Two DataFrames with Different Shapes in Python

Learn how to seamlessly `combine DataFrames` of different shapes using Python's pandas library, and achieve the desired results with ease!
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Effortlessly Concatenate Rows of Two DataFrames with Different Shapes in Python

When working with data in Python, especially with the pandas library, you might find yourself in a situation where you need to combine two DataFrames of different shapes. This can be a bit tricky, but with the right approach, it can be done smoothly and efficiently. In this post, we'll explore a specific example: concatenating rows of two DataFrames based on certain conditions.

The Problem

Let's say you have two DataFrames that look like this:

DataFrame 1 (df1)

This DataFrame holds values for different currencies:

USDCAD014125236[[See Video to Reveal this Text or Code Snippet]]

DataFrame 2 (df2)

This DataFrame contains the currency types and their balances:

currencybalance0USD21CAD3[[See Video to Reveal this Text or Code Snippet]]

Your goal is to prepend a new row to df1 at index 0 that includes the balances from df2, resulting in a DataFrame that looks like this:

USDCAD023114225336The Solution

Combining the DataFrames

Here's a step-by-step breakdown of how to do it:

Set the Index: First, we need to set the index of df2 to the currency column and transpose it, as we want the currencies to be in the correct position.

Reset the Index: Finally, we'll reset the index to ensure our new DataFrame has the correct format.

The Code

Here's the complete code snippet that accomplishes this:

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

Result

After executing the above code, you will get:

USDCAD023114225336Conclusion

Combining rows from two DataFrames with different shapes is a common task in data manipulation. With the powerful flexibility of pandas, you can achieve this effortlessly using simple functions. Whether you're working with financial data, survey results, or any other type of structured data, understanding how to concatenate DataFrames can enhance your data processing capabilities significantly.

We hope this post has clarified how to combine DataFrames in a Pythonic way. If you have any questions or need further clarification, feel free to reach out.