Python：csv文件操作

Question

遍历第二列并根据其优先级返回行内容，例如，如果找到'high'将其保存到文件，否则查找'intermediate'，如果找到将其保存到文件，否则查找'low'如果找到，请将其保存到文件中，然后转到该列的下一项。

csv 文件：

Details,Item Name,Priority,Feature1,Feature2,FeatureN
Details of A,A,High,some feature,some feature,some featureN
Details of A,A,Intermediate,some feature,some feature,some featureN
Details of A,A,Low,some feature,some feature,some featureN
Details of B,B,Intermediate,some feature,some feature,some featureN
Details of B,B,Low,some feature,some feature,some featureN
Details of C,C,Low,some feature,some feature,some featureN

预期输出：

Details,Item Name,Priority,Feature1,Feature2,FeatureN
Details of A,A,High,some feature,some feature,some featureN
Details of B,B,Intermediate,some feature,some feature,some featureN
Details of C,C,Low,some feature,some feature,some featureN

我是一个初学者，已经走到了这一步

    import sys
    import pandas as pd
    import csv


    df = pd.read_csv('29Test.csv')
    pd.set_option('display.max_columns', None)

    options = ['Intermediate']


    #selecting rows based on condition
    rslt_df = df[(df['Item Name'] == 'A') &
      df['Priority'].isin(options)]

    rslt_df.to_csv('randomfile.csv', index=False)

现在不知道如何制定优先条件并有效地迭代第二列。

Answer 1

使用有序的Categorical，因此可以按DataFrame.sort_values 按两列排序，并按DataFrame.drop_duplicates 获得第一个重复行：

df = pd.read_csv('29Test.csv')

df['Priority'] = pd.Categorical(df['Priority'], 
                                ordered=True, 
                                categories=['High','Intermediate','Low'])

rslt_df= df.sort_values(['Item Name','Priority']).drop_duplicates('Item Name')

print (rslt_df)
        Details Item Name      Priority      Feature1      Feature2  \
0  Details of A         A          High  some feature  some feature   
3  Details of B         B  Intermediate  some feature  some feature   
5  Details of C         C           Low  some feature  some feature   

        FeatureN  
0  some featureN  
3  some featureN  
5  some featureN  

rslt_df.to_csv('randomfile.csv', index=False)