Solving DataFrame Interpolation with Custom Functions in Python

Learn how to apply a custom interpolation function to a `Pandas` DataFrame when working with variable values. Get a step-by-step guide on how to implement it successfully!
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Solving DataFrame Interpolation with Custom Functions in Python

When dealing with data in Pandas, a common challenge arises when you want to interpolate values based on certain conditions. In this post, we’ll explore how to define a custom interpolation function, apply it to a DataFrame, and efficiently extract variable values using existing identifiers. Our example focuses on interpolating wind values based on their corresponding geographic coordinates.

Understanding the Problem

You have a dataset consisting of wind speed measurements connected to certain geographical coordinates. Your goal is to interpolate values with constant coordinates while incorporating wind speed values from a text file stored in a Pandas DataFrame.

Inputs Needed

Geographic Coordinates (constant values that determine the area of interest)

Wind Speed Values (variable values extracted from the DataFrame)

Desired Outcome

You want to create a new column in your DataFrame that reflects interpolated wind speed values based on coordinates and fixed input values.

Defining the Interpolation Function

We will start by defining a barycentric interpolation function called bary_interpol. This function will compute interpolated values using three points in a two-dimensional plane.

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

Setting Up Your DataFrame

Next, let’s ensure we have the relevant wind data stored in a DataFrame, from which we will draw values based on location identifiers (STN values). Here's a sample of how this can be set up:

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

Extracting Wind Speed Values

Using the identifiers, we will extract the wind speed values based on STN values.

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

Applying the Interpolation

Now, we will create a new DataFrame to store our interpolated values, and apply the bary_interpol function to compute these new values.

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

Conclusion

By following the steps outlined in this post, you can effectively create a new column within your DataFrame that contains interpolated values using both fixed coordinates and the variable wind speed values. Experiment with the constants and observe how they affect your interpolated results. This method can be adapted further for different contexts and types of data interpolation.

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