Python 为什么不'；桌子上的数字不是变了吗？

导入matplotlib.pyplot作为plt
将statsmodels.api作为sm导入
将statsmodels.formula.api作为sm1导入
开始=0
结束=60
timeseries={“期间”：[]，
“A”：[…]，
“B”：[…]，
“C”：[…]，
“R2”：[]}
当结束时
import matplotlib.pyplot as plt
import statsmodels.api as sm
import statsmodels.formula.api as sm1


start = 0
end = 60
timeseries = {"period":[],
              "A": [], 
              "B":[],
              "C":[],
              "R2":[]} 


while end <= len(d):
    df = d.iloc[start:end]
    period = str(df.index[0].to_timestamp().to_period('M')) + " to " + str(df.index[-1].to_timestamp().to_period('M'))
    model= sm1.ols(formula = 'Q("KS11") ~ Q("000001.SS") +Q("GSPC") ',data= d).fit()
    model_result = model.summary()
    
    x = df['000001.SS','GSPC']
    y = df['KS11']
    x = sm.add_constant(x)
    model = sm.OLS(y,x).fit()
    model_result = model.summary()
    
    
    timeseries["period"].append(period)
    timeseries["R2"].append(model.rsquared)
    results_as_html = model_result.tables[1].as_html()
    timeseries["A"].append(pd.read_html(results_as_html, header=0, index_col=0)[0]["coef"][0]) 
    timeseries["B"].append(pd.read_html(results_as_html, header=0, index_col=0)[0]["coef"][1]) 
    timeseries["C"].append(pd.read_html(results_as_html, header=0, index_col=0)[0]["coef"][2]) 
    start+=1  
    end+=1
    
timeseries_result = pd.DataFrame.from_dict(timeseries)

    start = 0
end = 120
timeseries = {"period":[],
              "alpha": [], 
              "beta":[],
              "r_sqrd":[]} 

while end <= len(monthly_asset_rre_df):
    df = monthly_asset_rre_df.iloc[start:end]
    period = str(df.index[0].to_timestamp().to_period('M')) + " to " + str(df.index[-1].to_timestamp().to_period('M'))
    x = df['F']
    y = df['M']
    x = sm.add_constant(x) #adds a constant term to the linear equation it is fitting
    model = sm.OLS(y,x).fit()
    model_result = model.summary()
    
    timeseries["period"].append(period)
    timeseries["r_sqrd"].append(model.rsquared)
    results_as_html = model_result.tables[1].as_html()
    timeseries["alpha"].append(pd.read_html(results_as_html, header=0, index_col=0)[0]["coef"][0]) #intercept
    timeseries["beta"].append(pd.read_html(results_as_html, header=0, index_col=0)[0]["coef"][1]) #coef
    start+=1  #start = start + 1
    end+=1    #end = end + 1
    
timeseries_result = pd.DataFrame.from_dict(timeseries)