How to Easily Retrieve id Values from a DataFrame Nested Dictionary in Python

Discover a simple method to retrieve the `id` value from a nested dictionary in a Python DataFrame. This guide will guide you step-by-step to make data extraction easier! --- This video is based on the question https://stackoverflow.com/q/73255401/ asked by the user 'PaulyboyUK' ( https://stackoverflow.com/u/5674971/ ) and on the answer https://stackoverflow.com/a/73255887/ provided by the user 'Barry the Platipus' ( https://stackoverflow.com/u/19475185/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions. Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Dataframe Nested Dict inside List - retrieve 'id' value Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l... The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license. If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com. --- How to Easily Retrieve id Values from a DataFrame Nested Dictionary in Python When working with data in Python, especially within a DataFrame using libraries like Pandas, you may often encounter challenging situations, such as extracting specific values from nested dictionaries. If you've ever found yourself pulling your hair out trying to access nested data in a list, you're not alone! In this post, we're going to look closely at a common problem: how to retrieve id values from a nested dictionary structure in a list format. The Problem We have a list of JSON-like strings representing data for contracts. The data includes attributes like title, AnnualValue, and an id. Here's a quick look at the data we're working with: [[See Video to Reveal this Text or Code Snippet]] We need to extract just the id values, but with the data being nested inside dictionaries, that might not be straightforward. The Solution Step-by-Step Guide Import Necessary Libraries: Start by importing the pandas and json libraries to help handle the data seamlessly. [[See Video to Reveal this Text or Code Snippet]] Prepare the Data: We already have our list of strings. Next, we'll create an empty list that will hold our transformed data. [[See Video to Reveal this Text or Code Snippet]] Extract Data Using a Loop: We'll loop through each item in the data_list, parse it with json.loads(), and extract the relevant values including the id. Append this information as tuples to new_data_list. [[See Video to Reveal this Text or Code Snippet]] Create a DataFrame: Finally, we can convert our extracted data into a Pandas DataFrame to get a more structured view. [[See Video to Reveal this Text or Code Snippet]] Output Explanation Running the above code will yield a DataFrame like this: IdTypeTitleAnnual Value01contractContract 1012contractContract 2023contractContract 30Now we have neatly organized the id values and their associated data. Conclusion In summary, extracting nested id values from a DataFrame can be achieved using Python's powerful libraries like Pandas and json. Following the outlined steps will help streamline your data extraction process and save you hours of frustration. So next time you're faced with nested data, remember this guide will be your trusty roadmap! Happy coding!