Polars: The Super Fast Dataframe Library for Python ... bye bye Pandas?

[@ThePyCoach]

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[@SvenTeresniak]

benchmarking against Pandas1 is not fair. Because Pandas is moving towars Arrow-backend and everyone should use Pandas 2 with Arrow as storage.

[@mikeyimawcw]

I don't see the CSV files you used during the video. Will you also share the Jupyter notebook, please? Thank you for creating and sharing this video.

[@ThePyCoach]

I've just added the link of the files to the description. Since it was a very small tutorial, I didn't upload the code to github, but you can get the same code from my Medium article (link on the description)

[@mikeyimawcw]

@@ThePyCoach Thank you.

[@backnine07]

great explanation! Thanks so much for your efforts.

[@reasonforge9997]

Its weird seeing the use of & in the filter expressions as a logical and rather than a bitwise and. But realized its because python only supports overloading the bitwise operators with __and__, __or__, and __xor__ methods and there is no way to overload the logical and, or and xor operators.

[@tobiewaldeck7105]

I have installed polars but python crashes at import polars as pl when I'm trying to run it with my pysimplegui application.

[@azwan1992]

Almost similar syntaxes like pyspark

[@thanomnoimoh9299]

Great Python clip for me!!!

[@saisushanthvellampalli908]

How to arrange the columns in this new library as per requirement

[@aipy5147]

Simply brilliant! Thank you. Liked & Subd.

[@ularkadutdotnet]

Can I read csv from url using polars?

[@RonaldPostelmans]

nice video, thanks. Any idea. how i can change the datatype of a column which has a datatime in it but is datatype string. I want to change it to datetime

[@JustRollin]

df = df.with_column(pl.col("date").alias("date_string").cast(pl.Object)) df = df.with_column(pl.col("date_string").to_datetime(pl.Date32)) According to chatgpt

[@azhanisyahputra9867]

@@JustRollin thx to be honest ;)

[@marco_gorelli]

@@JustRollin wut? Don't convert to pl.Object. Your code doesn't even work! Just do `df.with_columns(pl.col("date_string").str.to_datetime())`

[@FlannelCamel]

​@@JustRollin boo, don't regurgitate answers you don't understand and are possibly wrong.

[@dfaquino]

Cuando tendrás un curso de Polars en Udemy?

[@andydataguy]

Great video thanks!! ❤

[@fhkk1]

Anyone please suggest how to update null values with some string in Polars.

[@rackstar2]

if the name of your dataframe is 'df' and the name of the column which may contain nulls is called 'col_a' then this is the code : df = df.with_columns( pl.col('col_a').fill_null('your string here'') )

[@beto.004]

Es básicamente spark?

[@RidingWithGerdas]

Reminds me of pyspark

[@iamadataengineer-vb1hi]

Bye bye pandas

[@abdulsametcankaya5915]

I guess this is not informative, it seems like adversiting ;)

[@nikilkvn]

yeah...felt the same..

[@chobblegobbler6671]

reading from s3?