Answer by Amirtaha Ehsaei for How to perform OneHotEncoding in Sklearn,...
to make the long story short, if you are looking to dummify your df, use dummy=pd.get_dummies as:dummy=pd.get_dummies(df['str'])df=pd.concat([df,dummy], axis=1)print(Data)
View ArticleAnswer by Thom Ives for How to perform OneHotEncoding in Sklearn, getting...
You can go directly to OneHotEncoding now without using the LabelEncoder, and as we move toward version 0.22 many might want to do things this way to avoid warnings and potential errors (see DOCS and...
View ArticleAnswer by Ken Syme for How to perform OneHotEncoding in Sklearn, getting...
An alternative if you do want to encode multiple categorical features is to use a Pipeline with a FeatureUnion and a couple custom Transformers.First need two transformers - one for selecting a single...
View ArticleAnswer by Arunesh Singh for How to perform OneHotEncoding in Sklearn, getting...
Below implementation should work well. Note that the input of onehotencoder fit_transform must not be 1-rank array and also output is sparse and we have used to_array() to expand it. import pandas as...
View ArticleHow to perform OneHotEncoding in Sklearn, getting value error
I just started learning machine learning, when practicing one of the task, I am getting value error, but I followed the same steps as the instructor does.I am getting value error, please help.dff...
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