我们可以通过使用熊猫在状态列上添加逻辑来再添加一个列“ filestatus”吗？

debugcn 发表于 Dev

克里斯娜·柴坦亚·里亚里

这是我的python代码：

在下面的输出samplefile1中的所有已通过了3行，以便newcolumn{"filestatus" : "passed"}为"InputFile":"samplefile1"

因为example它有一个pass和一个fail因此{"filestatus":"failed"}所有的新列{"inputfile":"example"}

import json

df = pd.DataFrame([
            ['samlefile1','[email protected]', 'xyz' ,'pass'],
            ['samlefile1','[email protected]', 'xyz' ,'pass'],
            ['samlefile1','[email protected]', 'xyz' ,'pass'],
            ['testfile','[email protected]', 'abc' ,'pass'],
            ['example','[email protected]', 'xyz' ,'pass'],
            ['example','[email protected]', 'xyz' ,'fail']],columns = ['InputFile','UserId', 'UserGroup' ,'status']
    )
#Count no of status per filename
Input_status_count = df.groupby(['InputFile']).agg(success_count=('status', lambda x: x[x == 'pass'].count()),
                                                           fail_count=('status', lambda x: x[x == 'fail'].count()))
        
#Merge the 2 files on 'InputFile' column
FinalDF = pd.merge(df, Input_status_count,on = "InputFile" )
JSON_String = FinalDF.to_json(orient='records')
JSON_String


output:
[    
{"InputFile":"samlefile1","UserId":"[email protected]","UserGroup":"xyz","status":"pass","success_count":3,"fail_count":0, "filestatus":"passed"},
    {"InputFile":"samlefile1","UserId":"[email protected]","UserGroup":"xyz","status":"pass","success_count":3,"fail_count":0, "filestaus":"passed"},
    {"InputFile":"samlefile1","UserId":"[email protected]","UserGroup":"xyz","status":"pass","success_count":3,"fail_count":0, "filestatus":"passed"},
    {"InputFile":"testfile","UserId":"[email protected]","UserGroup":"abc","status":"","success_count":1,"fail_count":0, "filestatus":"not ran"},
    {"InputFile":"example","UserId":"[email protected]","UserGroup":"xyz","status":"pass","success_count":1,"fail_count":1,"filestatus":"failed"},
    {"InputFile":"example","UserId":"[email protected]","UserGroup":"xyz","status":"fail","success_count":1,"fail_count":1, "filestatus": "failed"}
]

笨狼

您可以使用pd.crosstab（而不是复杂的agg）将通过和失败列表化，并且在没有失败的情况下通过status列：

Input_status_count = pd.crosstab(df['InputFile'],df['status']).reset_index()
Input_status_count['filestatus'] = ["passed" if i==0 else "failed" for i in Input_status_count['fail']]

Input_status_count

status   InputFile  fail  pass filestatus
0          example     1     1     failed
1       samlefile1     0     3     passed
2         testfile     0     1     passed

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