這種情況下最好的熊貓應用/循環方法是什麼？

Question

我正在改變一些申請人的交易數據，我需要創建一個新的標誌列（在我的例子中標記爲「DESIRED FLAG」）。但是，我無法弄清楚正確的循環/應用方法，因爲在下面的邏輯中可能有很多不同的變化。

在一個完美的世界裏，連續申請過程中的歷史是這樣的，所有的「狀態」的設置爲「已完成」：

• 現場採訪開球 - >安排面試 - >決策; OR
• 電話採訪開球 - >安排面試 - >決策

當然，申請人可以順利通過很多電話面試和站點在他們的申請過程。

如下面的例子所示，有時會有「Schedule Interviews」被取消。在這些情況下，我需要刪除該步驟以及與此相關的後續步驟。其中包括「時間表訪談」，「決定」和「現場訪談開始」或「電話採訪開始」。另外，有時還會有其他「事件」，就像我們看到的手動跳過的那樣。

我還有其他類型的，我需要爲標誌的情況，所以我需要保持原有的數據框只新列。

import pandas as pd 

data = {'Employee ID': ["100","100", "100", "100","100","100","100","100","100","100","200", "200", "200","200","200","200","200","300","300", "300", "300","300","300","300"], 
     'Completed On Date': ["2009-01-01","2010-01-01","2011-06-05","2012-07-01","2013-01-01","2014-01-01","2015-01-01","2016-01-01","2017-01-01","2018-01-01","2010-01-01","2011-06-05","2012-07-01","2012-08-15","2013-01-01","2014-01-01","2015-01-01","2009-01-01","2010-01-01","2011-06-05","2012-07-01","2013-01-01","2014-01-01","2015-01-01"], 
     'Event': ["Decision","On-Site Interview Kick Off","Schedule Interviews","Decision","On-Site Interview Kick Off","Schedule Interviews","Decision","Phone Interview Kick Off","Schedule Interviews","Decision","On-Site Interview Kick Off","Schedule Interviews","Decision","Decision","Phone Interview Kick Off","Schedule Interviews","Decision","Job Apply","Phone Interview Kick Off","Schedule Interviews","Decision","On-Site Interview Kick Off","Schedule Interviews","Decision"], 
     'Event Status': ["Completed","Completed","CANCELED","Completed","Completed","Completed","Completed","Completed","Completed","Completed","Completed","CANCELED","Manually Skipped","Completed","Completed","Completed","Completed","Completed","Completed","CANCELED","Completed","Completed","Completed","Completed"], 
     'DESIRED FLAG': ["Keep","Keep","Remove","Remove","Remove","Keep","Keep","Keep","Keep","Keep","Keep","Remove","Remove","Remove","Remove","Keep","Keep","Keep","Keep","Remove","Remove","Remove","Keep","Keep"]} 
df = pd.DataFrame(data, columns=['Employee ID','Completed On Date','Event','Event Status','DESIRED FLAG']) 
df = df.sort_values(by=(['Employee ID','Completed On Date'])) 

df 

Answer 1

我認爲下面的代碼解決您的問題

import pandas as pd 

data = {'Employee ID': ["100","100", "100", "100","100","100","100","100","100","100","200", "200", "200","200","200","200","200","300","300", "300", "300","300","300","300"], 
     'Completed On Date': ["2009-01-01","2010-01-01","2011-06-05","2012-07-01","2013-01-01","2014-01-01","2015-01-01","2016-01-01","2017-01-01","2018-01-01","2010-01-01","2011-06-05","2012-07-01","2012-08-15","2013-01-01","2014-01-01","2015-01-01","2009-01-01","2010-01-01","2011-06-05","2012-07-01","2013-01-01","2014-01-01","2015-01-01"], 
     'Event': ["Decision","On-Site Interview Kick Off","Schedule Interviews","Decision","On-Site Interview Kick Off","Schedule Interviews","Decision","Phone Interview Kick Off","Schedule Interviews","Decision","On-Site Interview Kick Off","Schedule Interviews","Decision","Decision","Phone Interview Kick Off","Schedule Interviews","Decision","Job Apply","Phone Interview Kick Off","Schedule Interviews","Decision","On-Site Interview Kick Off","Schedule Interviews","Decision"], 
     'Event Status': ["Completed","Completed","CANCELED","Completed","Completed","Completed","Completed","Completed","Completed","Completed","Completed","CANCELED","Manually Skipped","Completed","Completed","Completed","Completed","Completed","Completed","CANCELED","Completed","Completed","Completed","Completed"], 
     'DESIRED FLAG': ["Keep","Keep","Remove","Remove","Remove","Keep","Keep","Keep","Keep","Keep","Keep","Remove","Remove","Remove","Remove","Keep","Keep","Keep","Keep","Remove","Remove","Remove","Keep","Keep"]} 
df = pd.DataFrame(data, columns=['Employee ID','Completed On Date','Event','Event Status','DESIRED FLAG']) 
df = df.sort_values(by=(['Employee ID','Completed On Date'])) 


index_list_delete = [] 
start_deleting = False 
for i in range(0, len(df)): 
    if start_deleting == False: 
     # whenever I see a "CANCELED", i know some following rows need to be deleted 
     if df.iloc[i]['Event Status'] == 'CANCELED': 
      index_list_delete += [i] 
      start_deleting = True 
    else: 
     # whenever i see a "Schedule Interviews", i need to stop deleting. 
     # otherwise keep track of the rows that need to be deleted 
     if df.iloc[i]['Event'] == 'Schedule Interviews': 
      start_deleting = False 
     else: 
      index_list_delete += [i] 

# deleting rows 
df = df.drop(df.index[index_list_delete]) 
# reseting index 
df = df.reset_index(drop = True) 

你會得到以下結果

Employee ID Completed On Date      Event Event Status DESIRED FLAG 
0   100  2009-01-01     Decision Completed   Keep 
1   100  2010-01-01 On-Site Interview Kick Off Completed   Keep 
2   100  2014-01-01   Schedule Interviews Completed   Keep 
3   100  2015-01-01     Decision Completed   Keep 
4   100  2016-01-01 Phone Interview Kick Off Completed   Keep 
5   100  2017-01-01   Schedule Interviews Completed   Keep 
6   100  2018-01-01     Decision Completed   Keep 
7   200  2010-01-01 On-Site Interview Kick Off Completed   Keep 
8   200  2014-01-01   Schedule Interviews Completed   Keep 
9   200  2015-01-01     Decision Completed   Keep 
10   300  2009-01-01     Job Apply Completed   Keep 
11   300  2010-01-01 Phone Interview Kick Off Completed   Keep 
12   300  2014-01-01   Schedule Interviews Completed   Keep 
13   300  2015-01-01     Decision Completed   Keep