def run():
varsY = [
x for x in Y.columns.tolist()
if Y.columns.tolist().index(x) in listboxY.curselection()
]
varsX = [
x for x in X.columns.tolist()
if X.columns.tolist().index(x) in listboxX.curselection()
]
global trainY
global trainX
trainY = Y[~data.isnull().T.any().T]
trainX = X[~data.isnull().T.any().T]
trainX = add_constant(trainX[varsX])
testX = X[data.isnull().T.any().T]
testX = add_constant(testX[varsX])
result0 = DataFrame(columns=varsY)
if (len(varsY) == 0):
messagebox.showinfo('提示', '至少选中一个结果变量！')
return
if (len(varsX) == 0):
messagebox.showinfo('提示', '至少选中一个预测变量！')
return
with ExcelWriter(saveFile, engine="openpyxl") as writer:
for id, varY in enumerate(varsY):
fit = OLS(trainY.iloc[:, id], trainX).fit()
print(fit.summary2().tables)
result0[varY] = fit.predict(testX)
result0.to_excel(writer,
sheet_name="SUMMARY",
header=True,
index=True)
global result1
result1 = fit.get_prediction(testX).summary_frame()
result1.to_excel(writer, sheet_name=varY, header=True, index=True)
global result2
result2 = fit.summary2().tables
result2[0].iloc[:, [0, 1]].to_excel(writer,
sheet_name=varY,
header=False,
index=False,
startrow=result1.shape[0] + 2,
startcol=0)
result2[0].iloc[:, [2, 3]].to_excel(writer,
sheet_name=varY,
header=False,
index=False,
startrow=result1.shape[0] + 2,
startcol=5)
result2[1].to_excel(writer,
sheet_name=varY,
header=True,
index=True,
startrow=result1.shape[0] +
result2[0].shape[0] + 3)
writer.save()
writer.close()
messagebox.showinfo('提示', '执行完成！')
