Python 逻辑回归数据框列名的数量不为'；t匹配来自管道的系数数

我想做一个seaborn条形图，在y轴上有特征系数值，在y轴上有特征名称。然而，系数的数量（38）与特征名称的数量（61）不匹配，我不知道如何修复它。我有以下代码：

import seaborn as sbn

from sklearn.preprocessing import StandardScaler, OneHotEncoder
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.impute import SimpleImputer

numeric_features = X_train.select_dtypes(include = 'float64').columns
numeric_transformer = Pipeline(steps=[('imputer', SimpleImputer(strategy='median')),
                                      ('scaler', StandardScaler())])

categorical_features = X_train.select_dtypes(include = object).columns
categorical_transformer = OneHotEncoder(handle_unknown='ignore')

from sklearn.compose import ColumnTransformer
preprocessor = ColumnTransformer(
    transformers=[
        ('num', numeric_transformer, numeric_features),
        ('cat', categorical_transformer, categorical_features)])

# Append classifier to preprocessing pipeline.
# Now we have a full prediction pipeline.
clf = Pipeline(steps=[('preprocessor', preprocessor),
                      ('classifier', LogisticRegression())])

model = clf.fit(X_train_bal, y_train_bal.values.ravel()) 
X_train_bal.columns.size
61

model.named_steps['classifier'].coef_
array([[ 0.28870311, -0.13493393,  0.47809258,  0.26252795,  0.        ,
         0.        ,  0.26399422,  0.06960872, -0.11635474,  0.70409391,
         0.66109449,  1.54120473,  1.13382411,  1.37477535,  0.01964528,
         0.41846923,  1.67995602,  0.32164349, -0.02979333,  0.02982878,
        -0.35519273,  1.18018633,  0.16830654,  0.08836489, -0.68934245,
        -0.639237  , -0.35329415,  0.33123055,  0.57701572,  0.01364959,
        -0.32165185, -0.00945931, -0.47790595,  0.15139768, -0.89368239,
         0.65439657,  0.52214267,  0.05314618]])

model.named_steps['classifier'].coef_.size
38

# ax = sns.barplot(x="time", y="tip", data=tips,
                 order=["Dinner", "Lunch"])