计算EL=PD×LGD×EAD

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
    sc = pd.read_csv(StringIO(____))
    feat = pd.read_csv(StringIO(____))
    woe_cols=[c for c in sc.columns if c.endswith(____)]
    X=sc[woe_cols].fillna(____); y=sc['____']
    X_tr,X_te,y_tr,y_te=train_test_split(____)
    lr=LogisticRegression(____); lr.fit(____)
    pd_prob=lr.predict_proba(____)[:,____]
    te_idx=X_te.index
    ead=feat.loc[te_idx,'____'].values if '____' in feat.columns else pd.Series([____]*len(____)).values
    el=pd_prob*____*ead
    print(pd.Series(____).describe().round(____).to_string())
    print(____)