为什么我不能替换此 excel 表中的 null 值？

Question

在我的代码中，我运行了一个 t 检验，当对两个零值组运行测试时，它有时会产生“NaN”或“nan”。 我尝试过制作新的数据框，尝试替换 using.replace 并尝试过 fillna() 但没有成功。 在尝试定义新的 dataframe 或在添加新计算后再次读取文件时出现错误。

如何替换这些文件中的空值和“nan”：“significant_report2.xls”或“quant_report2.xls”

import json
import os, sys
import numpy as np
import pandas as pd
import scipy.stats 

  output_report = "quant_report2.xls"
    significant_report = "significant_report2.xls"
    output_report_writer = open(output_report, "w")
    significant_writer = open(significant_report, "w")
    
    
    # setup samples grouped by control and treatment
    header = []
    for idx in control_indices:
        header.append(quant_columns[idx])
    for idx in treatment_indices:
        header.append(quant_columns[idx])
        
    output_report_writer.write("Feature\t%s\tP-value\tctrl_means\tctrl_stdDev\ttx_means\ttx_stdDev\n"%"\t".join(header))
    significant_writer.write("Feature\t%s\tP-value\tctrl_means\tctrl_stdDev\ttx_means\ttx_stdDev\n"%"\t".join(header))
    feature_list = list(quantitative_data_frame.index)
    for feature_idx in range(len(feature_list)):
            feature_name = feature_list[feature_idx]
            control_values = quantitative_data_frame.iloc[feature_idx, control_indices]
            treatment_values = quantitative_data_frame.iloc[feature_idx, treatment_indices]
            ttest_stat, ttest_pvalue = scipy.stats.ttest_ind(control_values, treatment_values, equal_var=False)
            ctrl_means = scipy.mean(control_values,0)
            ctrl_stdDev = scipy.stats.tstd(control_values)
            tx_means= scipy.mean(treatment_values,axis=0)
            tx_stdDev1 = scipy.stats.tstd(treatment_values) 
            output_report_writer.write("%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n"%(feature_name,                          
                                            "\t".join([str(x) for x in list(control_values)]),      
                                            "\t".join([str(x) for x in list(treatment_values)]), ttest_pvalue, ctrl_means,ctrl_stdDev,tx_means,tx_stdDev))
            significant_writer.write("%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n"%(feature_name,"\t".join([str(x) for x in list(control_values)]), "\t".join([str(x) for x in list(treatment_values)]),ttest_pvalue,ctrl_means,ctrl_stdDev,tx_means,tx_stdDev))