b5034279b48ae96ffdd4714f96e0f62b0f4807fc,category_encoders/ordinal.py,OrdinalEncoder,ordinal_encoding,#Any#Any#Any#Any#Any#,239
Before Change
for switch in mapping:
categories_dict = dict(switch.get("mapping"))
column = switch.get("col")
transformed_column = X[column].map(lambda x: categories_dict.get(x, np.nan))
try:
transformed_column = transformed_column.astype(int)
except ValueError as e:
After Change
try:
X[column] = X[column].astype(int)
except ValueError as e:
X[column] = X[column].astype(float)
if impute_missing:
if handle_unknown == "impute":
X[column].fillna(0, inplace=True)
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 3
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: erikbern/ann-benchmarks
Commit Name: e192e7c8155546ab549773cdaa2de943b0614038
Time: 2018-09-30
Author: maau@itu.dk
File Name: ann_benchmarks/algorithms/bruteforce.py
Class Name: BruteForceBLAS
Method Name: fit
Project Name: fgnt/pb_bss
Commit Name: 0d14271f97027c458ad7af1c057ff22f2acd2656
Time: 2019-08-01
Author: cbj@mail.uni-paderborn.de
File Name: pb_bss/evaluation/module_mir_eval.py
Class Name:
Method Name: mir_eval_sources