相关疑难解决方法(0)

我正在尝试使用np.random.shuffle（）方法调整索引，但是我不断收到我不理解的错误。如果有人可以帮助我解决这个问题，我将不胜感激。谢谢！

我一开始就将raw_csv_data变量设为变量时，曾尝试使用delimiter ='，'和delim_whitespace = 0，因为我将其视为另一个问题的解决方案，但它始终抛出相同的错误

    import pandas as pd 
    import numpy as np 
    from sklearn.preprocessing import StandardScaler

    #%%
    raw_csv_data= pd.read_csv('Absenteeism-data.csv')
    print(raw_csv_data)
    #%%
    df= raw_csv_data.copy()
    print(display(df))
    #%%
    pd.options.display.max_columns=None
    pd.options.display.max_rows=None
    print(display(df))
    #%%
    print(df.info())
    #%%
    df=df.drop(['ID'], axis=1)

    #%%
    print(display(df.head()))

    #%%
    #Our goal is to see who is more likely to be absent. Let's define
    #our targets from our dependent variable, Absenteeism Time in Hours
    print(df['Absenteeism Time in Hours'])
    print(df['Absenteeism Time in Hours'].median())
    #%%
    targets= np.where(df['Absenteeism Time in Hours']>df['Absenteeism Time 
    in Hours'].median(),1,0)
    #%%
    print(targets) …

我有这样的数据帧:

 match_id inn1  bat  bowl  runs1 inn2   runs2   is_score_chased
    1     1     KKR  RCB    222  2      82          1
    2     1     CSK  KXIP   240  2      207         1
    8     1     CSK  MI     208  2      202         1
    9     1     DC   RR     214  2      217         1
   33     1     KKR  DC     204  2      181         1

现在我想通过比较runs1和runs2中的值来更改is_score_chased列中的值.如果runs1> runs2,则行中的相应值应为"yes",否则应为no.我尝试了以下代码:

for i in (high_scores1):
  if(high_scores1['runs1']>=high_scores1['runs2']):
      high_scores1['is_score_chased']='yes'
  else:
      high_scores1['is_score_chased']='no' 

但它没有用.如何更改列中的值？