Get the feature names output by a ColumnTransformer

Need to get the feature names output by a ColumnTransformer?
Use get_feature_names(), which now works with "passthrough" columns (new in version 0.23)!
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[@dataschool]

Thanks for watching! 🙌 If you're new to ColumnTransformer, I recommend checking out tip #1: ruclips.net/video/NGq8wnH5VSo/видео.html

[@Dara-lj8rk]

If I may suggest, it would be interesting to see the difference between pipeline inside a column transformer vs. a column transformer inside a pipeline. I personally always put CT inside a pipeline, so keen to know a use case for the other one.

[@dataschool]

You would put a Pipeline inside a ColumnTransformer any time you need to perform a sequence of transformations to the same column. Hope that helps!

[@haitingyou6041]

Hello, I want get the whole set of columns name including numerical, but with your method, it returned "Transformer num (type Pipeline) does not provide get_feature_names." Do you have any other suggestions?

[@zeinat2233]

this just saved me from a big headache

[@dataschool]

Great to hear!

[@eatbreathedatascience9593]

oh, I didn't know that you can get the features names from the output. What's the different then if I were to do a df.columns of the output dataframe ?
I still cannot get the idea of doing OHE and then do PCA on the output in a pipeline. Have you done a video on that already ? If not, could give some tips how to transform the output from the previous steps, like in the scenario I've described ? Thanks very much in advance.

[@dataschool]

The output of any scikit-learn transformer is not a DataFrame, so it doesn't have a columns attribute. Hope that helps!

[@python2381]

hey i want one question and i want solution from you i have one arry like string ["4599"],["6625"],["7777"],["12345"],[7070] but i want print only this out put like this ["4599"],["6625"],["7777"] means i want print that string which string have same string last two or 1st and next if are same and or whole are same like in this arry ["7777"] how will sove this question

[@dataschool]

I'm not sure, sorry!