小编Aca*_*pha的帖子

我正在尝试使用 SKLearn Pipelines 和 ColumnTransformer 编写预处理。然而，变压器返回一个数组（而不是数据帧）这一事实让我有点失望。我希望也能够在已处理的 df 上使用列名称。想象一下以下数据和管道：

import pandas as pd
import numpy as np
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import OneHotEncoder
from sklearn.preprocessing import StandardScaler, MinMaxScaler
from sklearn.pipeline import Pipeline
from sklearn.impute import SimpleImputer

df = pd.DataFrame(np.random.randn(6, 4), columns=list("ABCD"))
df["E"] = pd.Categorical(["test", "train", "test", "train", "test", "train"])
df["F"] = "foo"

num_columns = ['A', 'B', 'C']
num_transformer = Pipeline(
    steps=[
        ('imputer', SimpleImputer(strategy='median')),
        ('scaler', StandardScaler()),
    ]
)
cat_columns = ['E', 'F']
cat_transformer = Pipeline(
    steps = [
        ('imputer', SimpleImputer(strategy='most_frequent')), …