How to Create Bins and Buckets with Pandas

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In this video, I'm going to show you how to create bin data using pandas and this is a great technique to create categories out of continuous data. Hopefully. you'll enjoy the video and learn how to create bins by grouping continuous data so let's see the entire video.

Binning or discretization is the process of transforming numerical variables into categorical counterparts. Numerical variables are usually discretized in the modeling methods based on frequency tables. Statistical data binning is a way to group numbers of more or less continuous values into a smaller number of "bins".

We will use the Pandas CUT function. This method basically means that cut divide up the underlying data into equal-sized. or categorical bins. The function defines the bins using percentiles based on the distribution of the data, not the actual numeric edges of the bins.

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Showed me exactly what I needed (manually specifying the labels argument). Thanks a lot!

lbbrfarangkiinok
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Thank you my friend
this was a blessing

wallstreetoftexas
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Thank you for these videos!! Learning a lot!

TauTauTau
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I have a column of discrete values, I want all of it be considered categorical. This code should work for all datasets. How do I approach this?

mirroring_
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Hi, well-explained video! I learnt a lot! Maybe next time you can share on how to evaluate the bins, i.e how to know the number of category we allocated is the best? Thanks!

shakilarosli
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hello, i have a question sir. does binning data like this causes loss of information? should we stay with continuous instead of categorical. sorry for bad english

alfathterry
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good content, but boring explanation.. liked the video thou

datastako