How to Use ChatGPT for Data cleaning and Analysis

Published: 10 April 2024
on channel: Cobalt Intelligence
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ChatGPT excels in parsing and cleaning cumbersome datasets. It runs Python code in the background to process the data, ensuring accuracy and efficiency

For example, when faced with a spreadsheet filled with redundant information, ChatGPT can effortlessly remove duplicates without the need for complex scripts or manual labor.

In this video, we tasked ChatGPT with generating a sample CSV file containing unique 1,500 business listings, including names, addresses, and contact details. The process was straightforward and efficient, producing a clean, organized dataset.

From filtering businesses based on location to identifying specific roles within companies, it interprets and executes queries with precision, offering insights that would be time-consuming to obtain manually.

Video Guide:

00:00 - Introduction to ChatGPT for Data Analysis
Jordan Hanson introduces the concept of using ChatGPT for data analysis tasks, highlighting its effectiveness in managing and cleaning large data sets.

00:15 - ChatGPT's Role in Data Scrubbing
The capabilities of ChatGPT in generating and scrubbing data, which is especially useful in fields such as data analytics and underwriting.

00:48 - Tutorial on Using ChatGPT for Business Data
Jordan starts a tutorial on how to use ChatGPT to process business data, showing the audience a sample spreadsheet and explaining the problem with duplicate entries.

01:12 - Generating Sample Data with ChatGPT
Using ChatGPT to generate a sample CSV file with business data, Jordan demonstrates how quickly and efficiently ChatGPT can create a large set of diverse entries.

03:35 - Removing Duplicates with ChatGPT
Jordan explains the process of asking ChatGPT to remove duplicates from the CSV file and create a smaller, cleaned sample for analysis.

02:00 - ChatGPT Writing and Running Python Code
The video shows ChatGPT writing and fixing Python code to clean the data set, emphasizing the reliability of the code execution by ChatGPT.

03:13 - Querying Data with ChatGPT
Jordan uses ChatGPT as a data analyst to query the cleaned data set for specific insights, such as the number of businesses based out of Oklahoma and CFO counts.

04:00 - Creating Charts with ChatGPT
Attempting to use ChatGPT to create a line graph representing the number of businesses by state to highlight ChatGPT's versatility in data visualization.

04:20 - Conclusion on ChatGPT as a Data Analyst Tool
Jordan concludes by reaffirming the utility of ChatGPT as a data analysis tool, while noting that some features like graph generation may still have limitations.

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