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    Home»Artificial Intelligence»Exploring the Power of Natural Language Data Manipulation with PandasAI | by Mia Dwyer | Apr, 2024
    Artificial Intelligence

    Exploring the Power of Natural Language Data Manipulation with PandasAI | by Mia Dwyer | Apr, 2024

    Jupiter NewsBy Jupiter NewsApril 15, 20242 Mins Read
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    How generative AI supercharges Pandas capabilities

    Towards Data Science

    I lately found a really intriguing new instrument that marries my curiosity in information science and generative AI, which lets you leverage ChatGPT to “discuss” to your information immediately in pure language whereas in a Jupyter pocket book.

    Enter PandasAI 🐼✨ a free, open supply Python library.*

    Picture created by me, utilizing DALL-E

    Datacamp describes PandasAI as “a Python library that makes use of genAI fashions to supercharge pandas capabilities. It was created to enhance the pandas library, a widely-used instrument for information evaluation and manipulation.” [1]

    Beneath is an instance of how one can leverage the spectacular capabilities of PandasAI, even with restricted data of Python and Pandas:

    Picture created by the creator, in Jupyter Lab, utilizing pandasai to “discuss” to a transactions dataset.

    This half does require signing up for an OpenAI developer account, however worry not! OpenAI makes this step fairly simple, it primarily simply requires producing a token that you’ll want to incorporate in your pocket book.

    You’ll must navigate to the “API Keys” web page → https://platform.openai.com/api-keys

    Screenshot of https://platform.openai.com/ by the creator.
    Screenshot of https://platform.openai.com/api-keys by the creator.

    First we have to import the related packages and no matter dataset we’re eager to “converse” with. For this instance, I’m utilizing a designer dummy dataset that I simply created with Generative AI — to learn to do this — check out my other article!

    import pandas as pd
    from pandasai import SmartDataframe

    dataframe = pd.read_csv('transactions.csv')

    # hook up with OpenAI dev with the API token we simply created :) 
    from pandasai.llm.openai…



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