b5034279b48ae96ffdd4714f96e0f62b0f4807fc,category_encoders/ordinal.py,OrdinalEncoder,ordinal_encoding,#,239
Before Change
categories_dict = {x: i + 1 for i, x in enumerate(categories)}
mapping_out.append({"col": col, "mapping": list(categories_dict.items()) , "data_type": X[col].dtype}, )
return X, mapping_out
After Change
categories = [x for x in pd.unique(X[col].values) if x is not None]
index = []
values = []
for i in range(len(categories)):
index.append(categories[i])
values.append(i + 1)
mapping = pd.Series(data=values, index=index)
mapping_out.append({"col": col, "mapping": mapping, "data_type": X[col].dtype}, )
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 7
Instances Project Name: scikit-learn-contrib/categorical-encoding
Commit Name: b5034279b48ae96ffdd4714f96e0f62b0f4807fc
Time: 2018-10-26
Author: jcastaldo08@gmail.com
File Name: category_encoders/ordinal.py
Class Name: OrdinalEncoder
Method Name: ordinal_encoding
Project Name: pgmpy/pgmpy
Commit Name: ca25da7c55ba436ab557410d5f2e2e9b557d2840
Time: 2015-03-02
Author: abinash.panda.ece10@itbhu.ac.in
File Name: pgmpy/models/MarkovModel.py
Class Name: MarkovModel
Method Name: to_junction_tree
Project Name: fmfn/BayesianOptimization
Commit Name: ad5cab5a112c1f0cc25827f902ab26ad2b25f238
Time: 2017-03-12
Author: aman.bhatia@outlook.com
File Name: bayes_opt/bayesian_optimization.py
Class Name: BayesianOptimization
Method Name: initialize