How to Calculate the Median Across Rows for Specific Columns in Pandas

Описание: Learn how to efficiently compute the median of specific columns in a Pandas DataFrame by sub-selecting relevant columns.
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How to Calculate the Median Across Rows for Specific Columns in Pandas

When working with data in Python, particularly using the Pandas library, you may find yourself in a situation where you need to compute the median of specific columns across the rows of a DataFrame. This is a common requirement in data analysis, especially when dealing with financial data, survey results, or any dataset with grouped numeric data. In this guide, we will guide you through the process of calculating the median for columns that contain a specific substring in their names, such as total.

The Problem

Imagine you have the following DataFrame containing different totals for each entry:

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You want to create a new DataFrame that includes the median of all columns containing the substring total, calculated row-wise. The expected output should contain a new column with the median values, resulting in something like this:

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To achieve this, you’ll need to filter the necessary columns and apply the median function across the rows.

The Solution

Here’s a step-by-step breakdown of how to compute the median for the specified columns effectively:

Step 1: Import the Required Libraries

First, ensure that you have imported the Pandas library correctly. If you haven't done so yet, you can install it via pip:

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Then, import it in your script:

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Step 2: Create Your DataFrame

Next, create your DataFrame with the required data, as shown below:

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Step 3: Filter Columns and Calculate Median

To filter the DataFrame for columns that contain the substring total, you can use the filter() function combined with apply() to compute the median. Here’s how you do it:

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Breaking this down further:

filter(like='total'): This filters the DataFrame to include only columns with total in their names.

apply(lambda x: x.median(), axis=1): This applies the median function across the selected columns for each row (axis=1 indicates row-wise operation).

Step 4: View the Updated DataFrame

Finally, you can display or use your newly created DataFrame with the median column included:

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After executing the above code, your DataFrame will look like this:

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Conclusion

Calculating the median across specific columns in a Pandas DataFrame is straightforward and can be accomplished with just a few lines of code. By using the filter() method along with the apply() function, you can dynamically select and compute values based on column names. This method is flexible and can adapt to varying numbers of columns based on your data needs.

Now you have the tools to efficiently analyze similar datasets and derive important statistical insights across your columns.