import pandas as pd
import numpy as np
from pandas import read_csv
from sklearn.preprocessing import Imputer
import matplotlib.pyplot as plt
import seaborn as sns
import missingno as msno
from pandas import set_option
import xlsxwriter
from missingpy import KNNImputer
from sklearn.model_selection import train_test_split
sns.set()
df = pd.read_csv('retail.csv')
df.head()
print(df)
for K in range(25):
K_value = K+1
imputer = KNNImputer(n_neighbors=K_value,weights="uniform")
x=imputer.fit_transform(df)
X1=pd.DataFrame(x)
print(X1)
export_excel = X1.to_excel (r'C:\\Users\\DELL\\.spyder-py3\\WORK\\DATASET\\retail\knn.xlsx',index = None,header=True) 

我需要用k的值范围在此零售数据集上进行估算。但这是行不通的。有人可以帮忙吗？因此，如果我猜想这段代码在运行时应该使用值k = 1到25进行插补，并且应该生成25个插补数据集？这合乎逻辑吗？