python - 根据记录的大小/数量删除 Pandas 记录的优雅方式

Question

这不是重复的。我没有尝试根据索引删除行

我有一个如下所示的数据框

df = pd.DataFrame({
'subject_id':[1,1,1,1,1,1,1,2,2,2,2,2],
'time_1' :['2173-04-03 12:35:00','2173-04-03 12:50:00','2173-04-05 
12:59:00','2173-05-04 13:14:00','2173-05-05 13:37:00','2173-07-06 
13:39:00','2173-07-08 11:30:00','2173-04-08 16:00:00','2173-04-09 
22:00:00','2173-04-11 04:00:00','2173- 04-13 04:30:00','2173-04-14 
08:00:00'],
'val' :[5,2,3,1,1,6,5,5,8,3,4,6]})
df['time_1'] = pd.to_datetime(df['time_1'])
df['day'] = df['time_1'].dt.day

如果它们的计数是 <=5，我想删除基于 subject_id 的记录。

这是我尝试过的

df1 = df.groupby(['subject_id']).size().reset_index(name='counter')
df1[df1['counter']>5] # this gives the valid subject_id = 1 has count more than 5)

现在使用此 subject_id，我必须获取该 subject_id 的基本数据帧行

可能有一种优雅的方式来做到这一点。

我想得到如下所示的输出。我想要我的基本数据框行

Answer 1

使用:

df[df.groupby('subject_id')['subject_id'].transform('size')>5]

输出:

   subject_id              time_1  val  day
0           1 2173-04-03 12:35:00    5    3
1           1 2173-04-03 12:50:00    2    3
2           1 2173-04-05 12:59:00    3    5
3           1 2173-05-04 13:14:00    1    4
4           1 2173-05-05 13:37:00    1    5
5           1 2173-07-06 13:39:00    6    6
6           1 2173-07-08 11:30:00    5    8