python - 按最小值分组并使用另一列第 2 部分中的值填充 NA

Question

这是原来的问题: Group by min and fill NAs with value from another column

我有这个数据框:

mydf = pd.DataFrame (data = {'uid': [1,1,1,2,2,3,4,4,4,4], 'pagename':
['home', 'blah', 
'blah', 'home', 'blah', 'blah','blah','home','blah','blah'], 'startpage': 
[np.nan, np.nan, np.nan, 'home', 
'home', 'blah',np.nan,np.nan,np.nan,np.nan], 'date_time': 
[0,1,2,5,9,1,1,2,3,4], 'page_event': [0,0,0,0,0,0,10,0,0,10]})

我想获取这个数据框:

endingdf = pd.DataFrame (data = {'uid': [1,1,1,2,2,3,4,4,4,4], 'pagename':
['home', 'blah', 'blah', 'home', 'blah','blah','blah','home','blah','blah'], 
'startpage': [np.nan, np.nan, np.nan, 'home', 
'home','blah',np.nan,np.nan,np.nan,np.nan],
'date_time': [0,1,2,5,9,1,1,2,3,4], 'page_event': [0,0,0,0,0,0,10,0,0,10],
'new_start_page':['home', 'home', 'home', 'home', 'home', 'blah', 'home', 
'home', 'home', 'home']})

我想要做的是按UID分组，如果startpage为NULL，则使用第一个pagename访问的时间(最短日期时间)，但仅当 page_event = 0 时。因此，如果第一个 pagename 具有 page_event = 10，则跳过它，直到 page_event = 0。

Answer 1

e = mydf.page_event
p = mydf.pagename
s = mydf.startpage
u = mydf.uid
m = e.mask(e == 10).groupby(u).apply(pd.Series.first_valid_index)

s.fillna(u.map(m).map(p), inplace=True)

print(mydf)

   date_time  page_event pagename startpage  uid
0          0           0     home      home    1
1          1           0     blah      home    1
2          2           0     blah      home    1
3          5           0     home      home    2
4          9           0     blah      home    2
5          1           0     blah      blah    3
6          1          10     blah      home    4
7          2           0     home      home    4
8          3           0     blah      home    4
9          4          10     blah      home    4