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Please make it available on Polars as well Pandas 2.x #8

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jnhyeon opened this issue Feb 19, 2024 · 3 comments
Open

Please make it available on Polars as well Pandas 2.x #8

jnhyeon opened this issue Feb 19, 2024 · 3 comments

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@jnhyeon
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jnhyeon commented Feb 19, 2024

First of all, thank you for creating such a wonderful package.

I was able to quickly understand the characteristics of the data using skim in R, and thank you for making it possible in Python as well.

Polars in the DataFrame package has been growing rapidly in popularity recently.
You can use the skim function in Polars using the to_pandas() function.
However, it would be better if polars was supported directly in pyskim.
Also, Pandas has been updated to version 2.x, but if you install pyskim, the Pandas version will be downgraded. It would be nice if Pandas were also updated to support 2.x.

Thank you

@kpj
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kpj commented Feb 19, 2024

Very happy to hear the package was useful to you, and thanks a lot for the comment.

I pushed a new package version with updated dependencies.

Supporting Polars would indeed be a great addition! Unfortunately, I don't have the capacity to implement these changes right now. Will certainly consider doing so in the future. In the meantime, I am of course happy to accept PRs.

@jnhyeon
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jnhyeon commented Feb 19, 2024

Thank you for your quick reply.

I think supporting Polars dataframes is simple.
You can convert to Pandas using Polars' to_pandas() function.
(You can use the skim function to convert the polars data frame to to_pandas().)
I think I can change the source to use the to_pandas() function in the case of the polars data frame within the skim function.

Thank you

@kpj
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kpj commented Feb 20, 2024

You can use the skim function to convert the polars data frame to to_pandas()

That's definitely a good intermediate solution. Later on, polars dataframes should also be supported natively (better performance, etc).

I think I can change the source to use the to_pandas() function in the case of the polars data frame within the skim function.

Sounds very good! Happy to review the PR.

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