(xfeat:PR#3) Test code and the result

pr3_test_code.out

   col  target
0  Cat       1
1  Dog       1
2  Dog       0
3  Dog       0
4  Fox       0
<class 'cudf.core.dataframe.DataFrame'>
   col  target  col_le
0  Cat       1       0
1  Dog       1       1
2  Dog       0       1
3  Dog       0       1
4  Fox       0       2
<class 'cudf.core.dataframe.DataFrame'>
   col  target
0  Cat       1
1  Dog       1
2  Dog       0
3  Dog       0
4  Fox       0
   col  target  col_te
0  Cat       1     1.0
1  Dog       1     0.0
2  Dog       0     0.5
3  Dog       0     0.5
4  Fox       0     0.0
<class 'cudf.core.dataframe.DataFrame'>

pr3_test_code.py

import pandas as pd
import cudf

from xfeat.cat_encoder import TargetEncoder, LabelEncoder


df_train = cudf.from_pandas(pd.DataFrame({
    "col": ["Cat", "Dog", "Dog", "Dog", "Fox", "Cat", "Rabbit"],
    "target": [1, 1, 0, 0, 0, 1, 1],
}))
print(df_train.head())
print(type(df_train))

encoder = LabelEncoder(input_cols=["col"])
df_train_le = encoder.fit_transform(df_train)
print(df_train_le.head())
print(type(df_train_le))

df_train = cudf.from_pandas(pd.DataFrame({
    "col": ["Cat", "Dog", "Dog", "Dog", "Fox", "Cat", "Rabbit"],
    "target": [1, 1, 0, 0, 0, 1, 1],
}))
print(df_train.head())

target_encoder = TargetEncoder(input_cols=["col"], target_col="target")
df_train_te = target_encoder.fit_transform(df_train)
print(df_train_te.head())
print(type(df_train_te))