r - 如何删除具有出现在 R 中的多行和多列中的值的行？
问题描述
我有一个包含很多列和行的数据框，其中许多是重复的。我想了解包含特定值的任何行：Playdoh_Butterfly_Natural.mp4 和 Playdoh_Butterfly_Unnatural.mp4。它们都在列 filename_right 和 filename_left 中出现至少 7 次。但是，每当我尝试删除这些值时，它都不起作用。我尝试了几种方法
import <- read.csv("rawData/session_1_anon.csv", na.strings = Playdoh_Butterfly_Natural.mp4 & Playdoh_Butterfly_Unnatural.mp4)
返回
object 'Playdoh_Butterfly_Natural.mp4' not found
import[!(row.names(import) %in% c('Playdoh_Butterfly_Natural.mp4','Playdoh_Butterfly_Unnatural.mp4')), ]
import[!(import$filename_left=="Playdoh_Butterfly_Natural.mp4" &
import$filename_right=="Playdoh_Butterfly_Unnatural.mp4"),]
import <- subset(import, filename_left != "Playdoh_Butterfly_Natural.mp4", filename_right != "Playdoh_Butterfly_Natural.mp4")
我也试过上面的三行。它们都没有返回错误，但它们也不会删除这些值。我感到非常困惑，不知道如何删除这些值/行。任何人都可以帮忙吗？谢谢！
Block_Nr Block_Name Task_Nr Task_Name Trial_Nr Trial_Id ATT_CHECK_1 ATT_CHECK_2 ATT_CHECK_3
1 1 block_1 10 end_of_exp 1 1
2 1 block_1 9 Attention_check 1 3 ANI_left
3 1 block_1 9 Attention_check 2 7
4 1 block_1 9 Attention_check 3 5 ANI_left
5 1 block_1 9 Attention_check 4 1 ANI_left
6 1 block_1 8 Take_a_break 1 1
7 1 block_1 7 Standard_Video_Trials 1 10
8 1 block_1 7 Standard_Video_Trials 2 33
9 1 block_1 7 Standard_Video_Trials 3 14
10 1 block_1 7 Standard_Video_Trials 4 31
11 1 block_1 7 Standard_Video_Trials 5 24
12 1 block_1 7 Standard_Video_Trials 6 16
13 1 block_1 7 Standard_Video_Trials 7 25
14 1 block_1 7 Standard_Video_Trials 8 17
15 1 block_1 7 Standard_Video_Trials 9 4
ATT_CHECK_4 Condition_Id datenschutz deleted_var_ deleted_var__80a0e
1 1 NA NA
2 1 NA NA
3 ANI_left 1 NA NA
4 1 NA NA
5 1 NA NA
6 1 NA NA
7 2 NA NA
8 1 NA NA
9 2 NA NA
10 1 NA NA
11 2 NA NA
12 2 NA NA
13 1 NA NA
14 1 NA NA
15 2 NA NA
deleted_var_copy_of_copy_of_copy_of_SMI_1_side deleted_var_copy_of_copy_of_SMI_1_side
1 NA NA
2 NA NA
3 NA NA
4 NA NA
5 NA NA
6 NA NA
7 NA NA
8 NA NA
9 NA NA
10 NA NA
11 NA NA
12 NA NA
13 NA NA
14 NA NA
15 NA NA
deleted_var_copy_of_SMI_1_side deleted_var_SMI_1_side deleted_var_SMI_3 Drawing_Boat_01 Drawing_Car_01
1 NA NA NA
2 NA NA NA
3 NA NA NA
4 NA NA NA
5 NA NA NA
6 NA NA NA
7 NA NA NA
8 NA NA NA
9 NA NA NA
10 NA NA NA
11 NA NA NA
12 NA NA NA
13 NA NA NA
14 NA NA NA
15 NA NA NA NAT_right
Drawing_Crown_01 Drawing_Dog_01 Drawing_Donkey_01 Drawing_Flower_01 Drawing_House_01 Drawing_PalmTree_01
1
2
3
4
5
6
7 NAT_right
8
9 NAT_right
10
11
12 NAT_right
13
14 NAT_left
15
Drawing_Tree_02 einverstanden ELE_1 ELE_2 ELE_3 ELE_4 factor1_tg1_task3 filename_left
1 NA NA NA NA NA
2 NA NA NA NA NA 2-cat.mp4
3 NA NA NA NA NA 4-hedgehog.mp4
4 NA NA NA NA NA 3-hare.mp4
5 NA NA NA NA NA 1-dog.mp4
6 NA NA NA NA NA
7 NA NA NA NA NA Drawing_Dog_Unnatural.mp4
8 NA NA NA NA NA Playdoh_Winky_Natural.mp4
9 NA NA NA NA NA Drawing_Flower_Unnatural.mp4
10 NA NA NA NA NA Playdoh_Turtle_Natural.mp4
11 NA NA NA NA NA Playdoh_Butterfly_Unnatural.mp4
12 NA NA NA NA NA Drawing_House_Unnatural.mp4
13 NA NA NA NA NA Playdoh_Flower_Natural.mp4
14 NA NA NA NA NA Drawing_PalmTree_Natural.mp4
15 NA NA NA NA NA Drawing_Boat_Unnatural.mp4
filename_right KEB_1 KEB_2 KEB_3 KEB_4 key_press Origami_Airplane_01 Origami_Heart_01
1 NA NA NA NA
2 2-grass.mp4 NA NA NA NA A
3 4-building.mp4 NA NA NA NA A
4 3-daisy.mp4 NA NA NA NA A
5 1-rose.mp4 NA NA NA NA A
6 NA NA NA NA
7 Drawing_Dog_Natural.mp4 NA NA NA NA L
8 Playdoh_Winky_Unnatural.mp4 NA NA NA NA A
9 Drawing_Flower_Natural.mp4 NA NA NA NA L
10 Playdoh_Turtle_Unnatural.mp4 NA NA NA NA A
11 Playdoh_Butterfly_Natural.mp4 NA NA NA NA L
12 Drawing_House_Natural.mp4 NA NA NA NA L
13 Playdoh_Flower_Unnatural.mp4 NA NA NA NA A
14 Drawing_PalmTree_Unnatural.mp4 NA NA NA NA A
15 Drawing_Boat_Natural.mp4 NA NA NA NA L
Playdoh_Butterfly_01 Playdoh_Flower_01 Playdoh_Snail_01 Playdoh_Tree_01 Playdoh_Turtle_01 Playdoh_Winky_01
1
2
3
4
5
6
7
8 NAT_left
9
10 NAT_left
11 NAT_right
12
13 NAT_left
14
15
time.frame completed exp_subject_id group_name rec_session_id Screen_Height Screen_Width session_name
1 NA yes 241482 group_1 261254 900 1440 session_1
2 NA yes 241482 group_1 261254 900 1440 session_1
3 NA yes 241482 group_1 261254 900 1440 session_1
4 NA yes 241482 group_1 261254 900 1440 session_1
5 NA yes 241482 group_1 261254 900 1440 session_1
6 NA yes 241482 group_1 261254 900 1440 session_1
7 NA yes 241482 group_1 261254 900 1440 session_1
8 NA yes 241482 group_1 261254 900 1440 session_1
9 NA yes 241482 group_1 261254 900 1440 session_1
10 NA yes 241482 group_1 261254 900 1440 session_1
11 NA yes 241482 group_1 261254 900 1440 session_1
12 NA yes 241482 group_1 261254 900 1440 session_1
13 NA yes 241482 group_1 261254 900 1440 session_1
14 NA yes 241482 group_1 261254 900 1440 session_1
15 NA yes 241482 group_1 261254 900 1440 session_1
session_nr subj_counter_global time_delay_offset time_measure_std unlocked Window_Height Window_Width
1 1 12 27.2 ms 150.1 ms true 900 1440
2 1 12 27.2 ms 150.1 ms true 900 1440
3 1 12 27.2 ms 150.1 ms true 900 1440
4 1 12 27.2 ms 150.1 ms true 900 1440
5 1 12 27.2 ms 150.1 ms true 900 1440
6 1 12 27.2 ms 150.1 ms true 900 1440
7 1 12 27.2 ms 150.1 ms true 900 1440
8 1 12 27.2 ms 150.1 ms true 900 1440
9 1 12 27.2 ms 150.1 ms true 900 1440
10 1 12 27.2 ms 150.1 ms true 900 1440
11 1 12 27.2 ms 150.1 ms true 900 1440
12 1 12 27.2 ms 150.1 ms true 900 1440
13 1 12 27.2 ms 150.1 ms true 900 1440
14 1 12 27.2 ms 150.1 ms true 900 1440
15 1 12 27.2 ms 150.1 ms true 900 1440
解决方案
不确定我是否完全理解这个问题，但如果这些文件名仅位于这两列中，您可以在导入后取出这些值：
import <- read.csv("rawData/session_1_anon.csv")
import <- import[import$filename_right != "Playdoh_Butterfly_Natural.mp4",]
import <- import[import$filename_left != "Playdoh_Butterfly_Natural.mp4",]
import <- import[import$filename_right != "Playdoh_Butterfly_Unnatural.mp4",]
import <- import[import$filename_left != "Playdoh_Butterfly_Unnatural.mp4",]
不是很优雅，但应该可以
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