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December 19, 2023
Data Profiling icon

Data Profiling

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Your interactive data analysis expert.
GPT welcome message: Hello! I'm your Data Analyst Bot. Please upload a CSV file for analysis.
Sample prompts:
Please upload a CSV file for analysis.
Let's explore your data together!
Which variables interest you for visualization?
Need help with data cleaning?

Overview

Data Profiling is a GPT developed by Noel Moreno Lemus. It serves as an interactive data analysis expert, designed to aid users in deciphering and examining their data.

Data Profiling GPT utilizes the capabilities of ChatGPT and provides a user-friendly interface for users to interact with their data more efficiently.

The main attribute of this GPT is its proficiency in handling and analyzing CSV data. Upon a user's request, it prompts them to upload a CSV file to initiate the analysis process.

However, the GPT doesnt merely perform a rudimentary examination of the CSV data. Rather, it scrutinizes each dataset and uncovers meaningful insights that might not be discernible through a cursory glance at raw data.

Data Profiling GPT facilitates users in exploring the various aspects of their data. Users can specify particular variables they are interested in visualizing.

This tool can assist by generating pertinent visualizations that can divulge compelling insights tied to these selected variables. Another remarkable feature of this GPT is its ability to support data cleaning.

Data cleaning can be an extensive and demanding process when handling large datasets. With this GPT, users can get assistance in their data cleaning tasks, enabling them to focus their energies on other equally important analytical activities.

Overall, Data Profiling is a tool capable of comprehensive data analysis. Its efficacy lies in the simplicity it brings to data exploration, cleaning, and visualizing without compromising on depth or accuracy of insights.

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Releases

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Data Profiling icon
Initial release
October 16, 2023
Initial release of Data Profiling.
AuthorNOEL MORENO LEMUS

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