从长格式数据中获取非 na 数据

Question

username,Phase,compound,Time,agegroup
000000ceans,6,0.1531,0.85,YA
000000ceans,1,,0,
000000ceans,2,,0.17,
000000ceans,3,,0.34,
000000ceans,4,,0.51,
000000ceans,5,,0.68,
000000ceans,7,,1.02,
00000codename,5,0.4588,0.68,YA
00000codename,1,,0,
00000codename,2,,0.17,
00000codename,3,,0.34,
00000codename,4,,0.51,
00000codename,6,,0.85,
00000codename,7,,1.02,
0000lailai,6,-0.2023,0.85,YA
0000lailai,1,,0,
0000lailai,2,,0.17,
0000lailai,3,,0.34,
0000lailai,4,,0.51,
0000lailai,5,,0.68,
0000lailai,7,,1.02,

I have a data frame like this (~ a million row), each username has 7 rows (0-6Nas in the compound). I hope to have a data frame with all the users who have 0-2Nas (<=2) in the compound.

The output will be something like this

username   phase      compound      agegroup   Time
a           1            0.1          YA       assigned according to phase
a           2            0.2          YA       assigned according to phase
a           3            0.3          YA       assigned according to phase
a           4            0.4          YA       assigned according to phase
a           5            0.5          YA       assigned according to phase
a           6            NA           YA       assigned according to phase
a           7            Na           YA       assigned according to phase
b
b
b

Answer 1

df %>%
  group_by(username)%>%
  filter(sum(is.na(compound))<=2)