pythonencodingscikit-learnone-hot-encoding

How to give column names after one-hot encoding with sklearn?

Here is my question, I hope someone can help me to figure it out..

To explain, there are more than 10 categorical columns in my data set and each of them has 200-300 categories. I want to convert them into binary values. For that I used first label encoder to convert string categories into numbers. The Label Encoder code and the output is shown below.

https://i.sstatic.net/MIVHV.png

After Label Encoder, I used One Hot Encoder From scikit-learn again and it is worked. BUT THE PROBLEM IS, I need column names after one hot encoder. For example, column A with categorical values before encoding. A = [1,2,3,4,..]

It should be like that after encoding,

A-1, A-2, A-3

Anyone know how to assign column names to (old column names -value name or number) after one hot encoding. Here is my one hot encoding and it's output;

https://i.sstatic.net/kgrNa.png

I need columns with name because I trained an ANN, but every time data comes up I cannot convert all past data again and again. So, I want to add just new ones every time. Thank anyway..

Solution

  • You can get the column names using .get_feature_names() attribute.

    >>> ohenc.get_feature_names()
>>> x_cat_df.columns = ohenc.get_feature_names()

    Detailed example is here.

    Update

    from Version 1.0, use get_feature_names_out