Скачать или смотреть How to Search Values in a DataFrame Cell List and Add a New Column in Python with Pandas

Learn how to compare lists within a DataFrame cell in Pandas and add a new column with results. This step-by-step guide makes it easy to handle non-matching values!
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Searching Values from a List in a DataFrame Cell List and Adding Another Column

When working with data in Python, especially using the Pandas library, you may encounter scenarios where you need to compare lists within your DataFrame and add new columns based on those comparisons.

In this guide, we'll explore a common problem: how to compare a DataFrame cell list with an external list, identify non-matching values, and add those results as a new column. Let’s break down the entire process step by step.

Understanding the Problem

Let’s say you have a DataFrame that contains a column with lists of values. For example:

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

And you also have an external list of values that you want to compare against the list in the DataFrame:

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

Your goal is to create a new column, C, that contains values from findKBs that do not exist in the list within the DataFrame under column A. For our example, the desired output should look like this:

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

Solution Breakdown

Step 1: Compare Lists

To achieve this, you will need to loop through the findKBs list and check which values are absent from the list in the DataFrame column A:

Access the List: The list in column A is accessed using df['A'][0], which refers to the first (and only) row in column A.

List Comprehension: You can use a Python list comprehension to iterate through each value in findKBs and check if it is not present in the DataFrame list.

Step 2: Implement the Code

Here's the concise line of code that accomplishes this task:

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

Step 3: Review the Output

After running the above code, your DataFrame will be updated with the new column C reflecting any non-matching values from the findKBs list:

The output will look like this:

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

Key Takeaways

You can easily compare lists within a DataFrame cell and generate new columns based on conditions using list comprehensions.

Understanding how to access nested lists in Pandas is crucial for effective data manipulation.

This approach is efficient and flexible for various use cases involving data comparison.

By following the steps outlined in this guide, you should now have a clear understanding of how to search values from a list and add a new column in a Pandas DataFrame. Happy coding!