我试图在顶部用NaT值对pandas数据帧进行排序。我正在使用df.sort_values函数：
df=df.sort_values(by='date_of_last_hoorah_given')
它工作正常，我在底部
得到一个带有NaT值的排序数据框 date_of_last_hoorah_given email first_name \
16 2016-12-19 07:36:08.000000 mindy.lyndi@hoorah.io Mindy
29 2016-12-19 07:36:08.000000 judi.seward@hoorah.io Judi
7 2016-12-19 07:36:08.000000 chao.an@hoorah.io Chao
21 2016-12-19 07:36:08.000000 bala.harish@hoorah.io Bala
12 2016-12-19 07:36:08.000000 pushpa.swaran@hoorah.io Pushpa
30 2016-12-22 07:36:08.000000 sparrow.freespirit@hoorah.io Sparrow
28 2016-12-22 07:36:08.000000 sanjeev.prasanna@hoorah.io Sanjeev
27 2016-12-22 07:36:08.000000 twinklenose.snowleaf@hoorah.io Twinklenose
25 2016-12-22 07:36:08.000000 sweetgaze.sugarshy@hoorah.io Sweetgaze
23 2016-12-22 07:36:08.000000 shreya.sarika@hoorah.io Shreya
19 2016-12-22 07:36:08.000000 jiahao.dong@hoorah.io Jiahao
15 2016-12-22 07:36:08.000000 jannine.tyson@hoorah.io Janine
14 2016-12-22 07:36:08.000000 arlo.reed@hoorah.io Arlo
0 2016-12-22 07:36:08.000000 aditya.hariharan@hoorah.io Aditya
11 2016-12-22 07:36:08.000000 shirley.madalitso@hoorah.io Shirley
2 2016-12-22 07:36:08.000000 minerva.jena@hoorah.io Minerva
3 2016-12-22 07:36:08.000000 colby.brandi@hoorah.io Colby
13 2016-12-22 07:36:08.000000 beverly.cohen@hoorah.io Beverly
6 2016-12-22 07:36:08.000000 guanting.jun@hoorah.io Guanting
5 2016-12-22 07:36:08.000000 chen.tu@hoorah.io Chen
18 2016-12-22 10:55:03.474683 fen.lin@hoorah.io Fen
9 2016-12-23 07:36:08.000000 kourtney.pam@hoorah.io Kourtney
10 2016-12-23 14:30:55.206581 kailee.alfie@hoorah.io Kailee
4 2016-12-24 07:36:08.000000 jing.chao@hoorah.io Jing
31 2016-12-24 16:02:28.945809 rich.oswin@hoorah.io Rich
24 2016-12-25 07:36:08.000000 ganesh.vasanta@hoorah.io Ganesh
8 2016-12-26 07:36:08.000000 xia.yaling@hoorah.io Xia
20 2016-12-27 07:36:08.000000 kinley.joan@hoorah.io Kinley
22 2016-12-28 07:36:08.000000 honeygleam.dazzlesmile@hoorah.io Honeygleam
26 2016-12-28 15:29:48.629929 indira.padma@hoorah.io Indira
17 2016-12-29 02:27:11.125078 ileen.gaynor@hoorah.io Ileen
32 2016-12-29 15:38:02.335296 ragnar.lestat@hoorah.io Ragnar
1 NaT flitterbeam.clovergaze@hoorah.com Flitterbeam
但是当我尝试使用以下代码将其放在首位时：
df=df.sort_values(by='date_of_last_hoorah_given',ascending=[1,0])
我得到一个valueError：升序的长度（2）！= by的长度（1） 完整堆栈跟踪如下：
ValueError Traceback (most recent call last)
<ipython-input-107-948a8354aeeb> in <module>()
1 cd = ClientData(1)
----> 2 cd.get_inactive_users()
<ipython-input-106-ed230054ea86> in get_inactive_users(self)
346 inactive_users_result.append(user_dict)
347 df=pd.DataFrame(inactive_users_result)
--> 348 df=df.sort_values(by='date_of_last_hoorah_given',ascending=[1,0])
349 print(df)
C:\Users\aditya\Anaconda3\lib\site-packages\pandas\core\frame.py in sort_values(self, by, axis, ascending, inplace, kind, na_position)
3126 if com.is_sequence(ascending) and len(by) != len(ascending):
3127 raise ValueError('Length of ascending (%d) != length of by (%d)' %
-> 3128 (len(ascending), len(by)))
3129 if len(by) > 1:
3130 from pandas.core.groupby import _lexsort_indexer
ValueError: Length of ascending (2) != length of by (1)
答案 0 :(得分：4)
问题是NaT在排序时是最大的，因此总是最后的。为了在将np.lexsort放在前面或顶部时按升序排序，您需要按两个条件排序。
np.argsort将按任意数量的条件对数组进行排序，并返回类似于notnull的排序切片
另请注意，我会将np.lexsort条件放在传递给np.lexsort的条件数组的最后。 df.date_of_last_hoorah_given.notnull()首先对最后的元素进行排序......我不知道为什么，但这就是它的原因。
因此我们应首先按True排序，因为那些不为null的值的值False大于排序上下文中的dates = df.date_of_last_hoorah_given
sort_slice = np.lexsort([dates.values, dates.notnull().values])
df.iloc[sort_slice]
。然后我们可以按其余的日期排序。
df.sort_values('date_of_last_hoorah_given', na_position='first')
date_of_last_hoorah_given email first_name
1 NaT flitterbeam.clovergaze@hoorah.com Flitterbeam
16 2016-12-19 07:36:08.000000 mindy.lyndi@hoorah.io Mindy
29 2016-12-19 07:36:08.000000 judi.seward@hoorah.io Judi
7 2016-12-19 07:36:08.000000 chao.an@hoorah.io Chao
21 2016-12-19 07:36:08.000000 bala.harish@hoorah.io Bala
12 2016-12-19 07:36:08.000000 pushpa.swaran@hoorah.io Pushpa
30 2016-12-22 07:36:08.000000 sparrow.freespirit@hoorah.io Sparrow
28 2016-12-22 07:36:08.000000 sanjeev.prasanna@hoorah.io Sanjeev
27 2016-12-22 07:36:08.000000 twinklenose.snowleaf@hoorah.io Twinklenose
25 2016-12-22 07:36:08.000000 sweetgaze.sugarshy@hoorah.io Sweetgaze
23 2016-12-22 07:36:08.000000 shreya.sarika@hoorah.io Shreya
19 2016-12-22 07:36:08.000000 jiahao.dong@hoorah.io Jiahao
15 2016-12-22 07:36:08.000000 jannine.tyson@hoorah.io Janine
14 2016-12-22 07:36:08.000000 arlo.reed@hoorah.io Arlo
0 2016-12-22 07:36:08.000000 aditya.hariharan@hoorah.io Aditya
11 2016-12-22 07:36:08.000000 shirley.madalitso@hoorah.io Shirley
2 2016-12-22 07:36:08.000000 minerva.jena@hoorah.io Minerva
3 2016-12-22 07:36:08.000000 colby.brandi@hoorah.io Colby
13 2016-12-22 07:36:08.000000 beverly.cohen@hoorah.io Beverly
6 2016-12-22 07:36:08.000000 guanting.jun@hoorah.io Guanting
5 2016-12-22 07:36:08.000000 chen.tu@hoorah.io Chen
18 2016-12-22 10:55:03.474683 fen.lin@hoorah.io Fen
9 2016-12-23 07:36:08.000000 kourtney.pam@hoorah.io Kourtney
10 2016-12-23 14:30:55.206581 kailee.alfie@hoorah.io Kailee
4 2016-12-24 07:36:08.000000 jing.chao@hoorah.io Jing
31 2016-12-24 16:02:28.945809 rich.oswin@hoorah.io Rich
24 2016-12-25 07:36:08.000000 ganesh.vasanta@hoorah.io Ganesh
8 2016-12-26 07:36:08.000000 xia.yaling@hoorah.io Xia
20 2016-12-27 07:36:08.000000 kinley.joan@hoorah.io Kinley
22 2016-12-28 07:36:08.000000 honeygleam.dazzlesmile@hoorah.io Honeygleam
26 2016-12-28 15:29:48.629929 indira.padma@hoorah.io Indira
17 2016-12-29 02:27:11.125078 ileen.gaynor@hoorah.io Ileen
32 2016-12-29 15:38:02.335296 ragnar.lestat@hoorah.io Ragnar
OR！正如OP在评论中所说，这给出了同样的东西，而且更直接
"image" => "nullable|required_without:content|image",
"content" => "nullable|required_without:image"
答案 1 :(得分：3)
您不能在ascending=[1,0]中使用2个值，因为只排序一列：
如果需要降序使用False，默认情况下为True：
df=df.sort_values(by='date_of_last_hoorah_given',ascending=False)
print (df)
date_of_last_hoorah_given email first_name
1 NaT flitterbeam.clovergaze@hoorah.com Flitterbeam
32 2016-12-29 15:38:02.335296 ragnar.lestat@hoorah.io Ragnar
17 2016-12-29 02:27:11.125078 ileen.gaynor@hoorah.io Ileen
26 2016-12-28 15:29:48.629929 indira.padma@hoorah.io Indira
22 2016-12-28 07:36:08.000000 honeygleam.dazzlesmile@hoorah.io Honeygleam
20 2016-12-27 07:36:08.000000 kinley.joan@hoorah.io Kinley
8 2016-12-26 07:36:08.000000 xia.yaling@hoorah.io Xia
24 2016-12-25 07:36:08.000000 ganesh.vasanta@hoorah.io Ganesh
31 2016-12-24 16:02:28.945809 rich.oswin@hoorah.io Rich
4 2016-12-24 07:36:08.000000 jing.chao@hoorah.io Jing
10 2016-12-23 14:30:55.206581 kailee.alfie@hoorah.io Kailee
9 2016-12-23 07:36:08.000000 kourtney.pam@hoorah.io Kourtney
18 2016-12-22 10:55:03.474683 fen.lin@hoorah.io Fen
3 2016-12-22 07:36:08.000000 colby.brandi@hoorah.io Colby
5 2016-12-22 07:36:08.000000 chen.tu@hoorah.io Chen
6 2016-12-22 07:36:08.000000 guanting.jun@hoorah.io Guanting
13 2016-12-22 07:36:08.000000 beverly.cohen@hoorah.io Beverly
2 2016-12-22 07:36:08.000000 minerva.jena@hoorah.io Minerva
11 2016-12-22 07:36:08.000000 shirley.madalitso@hoorah.io Shirley
0 2016-12-22 07:36:08.000000 aditya.hariharan@hoorah.io Aditya
14 2016-12-22 07:36:08.000000 arlo.reed@hoorah.io Arlo
15 2016-12-22 07:36:08.000000 jannine.tyson@hoorah.io Janine
...
...
如果需要按2列排序，首先是升序，第二次是降序：
df=df.sort_values(by=['date_of_last_hoorah_given', 'email'],ascending=[True, False])
如果需要使用NaN升级排序，首先可能的解决方案是concat已拆分的DataFrame：
df.date_of_last_hoorah_given = pd.to_datetime(df.date_of_last_hoorah_given)
df=df.sort_values(by='date_of_last_hoorah_given')
mask = df.date_of_last_hoorah_given.isnull()
print (pd.concat([df[mask], df[~mask]]))
date_of_last_hoorah_given email first_name
1 NaT flitterbeam.clovergaze@hoorah.com Flitterbeam
16 2016-12-19 07:36:08.000000 mindy.lyndi@hoorah.io Mindy
29 2016-12-19 07:36:08.000000 judi.seward@hoorah.io Judi
7 2016-12-19 07:36:08.000000 chao.an@hoorah.io Chao
21 2016-12-19 07:36:08.000000 bala.harish@hoorah.io Bala
12 2016-12-19 07:36:08.000000 pushpa.swaran@hoorah.io Pushpa
5 2016-12-22 07:36:08.000000 chen.tu@hoorah.io Chen
6 2016-12-22 07:36:08.000000 guanting.jun@hoorah.io Guanting
13 2016-12-22 07:36:08.000000 beverly.cohen@hoorah.io Beverly
3 2016-12-22 07:36:08.000000 colby.brandi@hoorah.io Colby
11 2016-12-22 07:36:08.000000 shirley.madalitso@hoorah.io Shirley
0 2016-12-22 07:36:08.000000 aditya.hariharan@hoorah.io Aditya
14 2016-12-22 07:36:08.000000 arlo.reed@hoorah.io Arlo
2 2016-12-22 07:36:08.000000 minerva.jena@hoorah.io Minerva
19 2016-12-22 07:36:08.000000 jiahao.dong@hoorah.io Jiahao
23 2016-12-22 07:36:08.000000 shreya.sarika@hoorah.io Shreya
15 2016-12-22 07:36:08.000000 jannine.tyson@hoorah.io Janine
25 2016-12-22 07:36:08.000000 sweetgaze.sugarshy@hoorah.io Sweetgaze
27 2016-12-22 07:36:08.000000 twinklenose.snowleaf@hoorah.io Twinklenose
28 2016-12-22 07:36:08.000000 sanjeev.prasanna@hoorah.io Sanjeev
30 2016-12-22 07:36:08.000000 sparrow.freespirit@hoorah.io Sparrow
18 2016-12-22 10:55:03.474683 fen.lin@hoorah.io Fen
9 2016-12-23 07:36:08.000000 kourtney.pam@hoorah.io Kourtney
10 2016-12-23 14:30:55.206581 kailee.alfie@hoorah.io Kailee
4 2016-12-24 07:36:08.000000 jing.chao@hoorah.io Jing
...
...