分析LR模型系数的业务含义

def solve():
    from pyodide.http import open_url
    from io import StringIO
    loans_clean_csv = open_url(____).read()
    loans_featured_csv = open_url(____).read()
    scorecard_data_csv = open_url(____).read()
    woe_table_csv = open_url(____).read()
    import pandas as pd
    from sklearn.linear_model import LogisticRegression
    from sklearn.model_selection import train_test_split
    from io import StringIO
    df = pd.read_csv(StringIO(____))
    woe_cols=[c for c in df.columns if c.endswith(____)]
    X=df[woe_cols].fillna(____); y=df['____']
    X_tr,X_te,y_tr,y_te=train_test_split(____)
    lr=LogisticRegression(____); lr.fit(____)
    rows=[{'____':c.replace(____),'____':round(____),'____':'____' if lr.coef_[____][i]>____ else '____'} for i,c in enumerate(____)]
    print(pd.DataFrame(____).sort_values(____).to_string(____))