Скачать или смотреть How to Search for String in DataFrame Column Using Pandas in Python

In this guide, learn how to efficiently search for a string in a DataFrame column using Pandas in Python and create a new column based on the search results.
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This video is based on the question https://stackoverflow.com/q/62282667/ asked by the user 'Ben H' ( https://stackoverflow.com/u/13713369/ ) and on the answer https://stackoverflow.com/a/62282782/ provided by the user 'Patrick Artner' ( https://stackoverflow.com/u/7505395/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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How to Search for String in DataFrame Column Using Pandas in Python

In data analysis, you'll often find situations where you need to check if a specific string exists within a column of a DataFrame. This can be particularly useful when categorizing data based on certain keywords. In this guide, we will address a common problem: creating a new column in a Pandas DataFrame based on whether an existing column contains a specific string. We will use a simple example to illustrate the solution effectively.

Problem Overview

Imagine you have a DataFrame containing information about financial instruments, such as options. The first column holds the name of the options (e.g., "USDCAD exotic option" or "USDSGD vanilla option"), and you want to categorize these options into two types: Vanilla or Exotic. This categorization can be determined by the presence of the word "vanilla" or "exotic" in the first column.

Here is a quick look at our DataFrame:

OptionsValueUSDCAD exotic option-100USDSGD vanilla option-20The objective is to create a third column that clearly states whether the option is "Vanilla" or "Exotic" based on the string found in the first column.

Solution Explanation

To achieve this, we can leverage Pandas along with regular expression pattern matching. Below is the complete step-by-step guide to implement this.

Step 1: Import Pandas

First, you need to import the Pandas library. If you haven't installed it yet, you can do so using pip:

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Once installed, import it into your Python script:

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Step 2: Create the DataFrame

Next, let's create our DataFrame using the provided data:

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

Step 3: Use Regular Expressions to Extract the Option Type

Now that we have our DataFrame, we can create a new column by searching for the presence of specific keywords ("vanilla" or "exotic"). We'll use the .str.extract() method combined with a regular expression:

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

Step 4: View the Output

Finally, let's print the updated DataFrame to see the results of our categorization:

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

Expected Output:

After running the code, we should see the following output:

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

Summary

In this guide, we explored how to search for a specific string in a DataFrame column using Pandas. By applying regular expressions, we were able to categorize financial options into "Vanilla" and "Exotic" simply and efficiently. The main steps included importing Pandas, constructing the DataFrame, and utilizing the .str.extract() function to derive our new column.

By following these steps, you can easily adapt this approach to your own data analysis challenges, making your data manipulation tasks even more streamlined. Happy coding!