這是我的Python代碼：在下面的輸出中samplefile1已傳入所有 3 行，因此 newcolumn{"filestatus" : "passed"}為"InputFile":"samplefile1"因?yàn)閑xample它有一個(gè)pass又一個(gè)fail如此新的{"filestatus":"failed"}欄目{"inputfile":"example"}import jsondf = pd.DataFrame([ ['samlefile1','user1@gmail.com', 'xyz' ,'pass'], ['samlefile1','user5@gmail.com', 'xyz' ,'pass'], ['samlefile1','user6@gmail.com', 'xyz' ,'pass'], ['testfile','user2@gmail.com', 'abc' ,'pass'], ['example','user3@gmail.com', 'xyz' ,'pass'], ['example','user3@gmail.com', 'xyz' ,'fail']],columns = ['InputFile','UserId', 'UserGroup' ,'status'] )#Count no of status per filenameInput_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' columnFinalDF = pd.merge(df, Input_status_count,on = "InputFile" )JSON_String = FinalDF.to_json(orient='records')JSON_Stringoutput:[ {"InputFile":"samlefile1","UserId":"user1@gmail.com","UserGroup":"xyz","status":"pass","success_count":3,"fail_count":0, "filestatus":"passed"}, {"InputFile":"samlefile1","UserId":"user5@gmail.com","UserGroup":"xyz","status":"pass","success_count":3,"fail_count":0, "filestaus":"passed"}, {"InputFile":"samlefile1","UserId":"user6@gmail.com","UserGroup":"xyz","status":"pass","success_count":3,"fail_count":0, "filestatus":"passed"}, {"InputFile":"testfile","UserId":"user2@gmail.com","UserGroup":"abc","status":"","success_count":1,"fail_count":0, "filestatus":"not ran"}, {"InputFile":"example","UserId":"user3@gmail.com","UserGroup":"xyz","status":"pass","success_count":1,"fail_count":1,"filestatus":"failed"}, {"InputFile":"example","UserId":"user3@gmail.com","UserGroup":"xyz","status":"fail","success_count":1,"fail_count":1, "filestatus": "failed"}]
2 回答
紅糖糍粑
TA貢獻(xiàn)1815條經(jīng)驗(yàn) 獲得超6個(gè)贊
是的，你可以這樣做：
import numpy as np
#Count no of status per filename
Input_status_count = df.groupby(['InputFile']).agg([('filestatus', lambda x: 'passed' if x[x['status'] == 'fail'].count() == 0 else 'failed')])
Lambda 函數(shù)基本上檢查我們是否獲得狀態(tài)為失敗的零行計(jì)數(shù)，然后文件狀態(tài)將被傳遞，否則失敗。
白衣非少年
TA貢獻(xiàn)1155條經(jīng)驗(yàn) 獲得超0個(gè)贊
您可以使用 pd.crosstab （而不是復(fù)雜的 agg）將通過(guò)和失敗制成表格，并且當(dāng)沒(méi)有失敗時(shí)狀態(tài)列將通過(guò)：
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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