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It'd be amazing if we could have a rich and adaptable viewer for dataframes since they are so ubiquitous.
(not as heavyweight as DataWrangler though - it disrupts the context too much and changes VSCode layout).
The very particular pain I'm very frequently running into:
I get the dataframe in the output of a cell - I want to look at the data to either explore it or to make sure it has the right values and columns.
the frame is too large to fit, so some columns and rows are elided ...
now I have to go back and either add df.head() to reduce number of rows or df.columns to see all the columns, or do df.head().T to see all columns in a list with some values.
Even cooler would be to also have an easy way to reference the dataframes in notebook as context to Copilot Chat for "how do I join/pivot/aggregate/visualise?" types of questions.
Even cooler would be to also have an easy way to reference the dataframes in notebook as context to Copilot Chat for "how do I join/pivot/aggregate/visualise?" types of questions.
Currently we embed the variable summaries in the chat context so you can ask such questions, say you have a data frame df, you can ask how do I join/pivot/aggregate/visualise the data frame and Copilot is able to generate code with the right data frame reference. Let me know if it works as expected for you.
When inspecting data frames, the output is not rendered in a scrollable region, making the whole notebook hard to navigate
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