我试图将两个 csv 文件导入df1和df2. 将它们连接起来制作df3. 我试图打电话给mutual_info_regression他们，但我得到一个值错误ValueError: Found array with 0 sample(s) (shape=(0, 1)) while a minimum of 1 is required。我检查了X、y和的尺寸discrete_features。他们似乎都还好。

由于代码适用于其他csv文件（我已经测试过），我认为问题出在我的csv文件而不是代码上。

import numpy as np
import pandas as pd

df1 = pd.read_csv("WT_MDE.csv", index_col=0)
df1["Interact"] = 1

df2 = pd.read_csv("M_MDE.csv", index_col=0)
df2["Interact"] = 0

data = pd.concat([df1, df2])

X = data.copy()
y = X.pop("Interact")
discrete_features = X.dtypes == float

from sklearn.feature_selection import mutual_info_regression

def make_mi_scores(X, y, discrete_features):
    mi_scores = mutual_info_regression(X, y, discrete_features = discrete_features)
    mi_scores = pd.Series(mi_scores, name="MI Scores", index=X.columns)
    mi_scores = mi_scores.sort_values(ascending=False)
    return mi_scores

mi_scores = make_mi_scores(X, y, discrete_features)

CSV 文件的 Google Drive 链接

如果有人可以提供帮助，我将不胜感激。