我有一个像这样的df
Category <- c('D_L','D_R','FA1','LBP0W','L-010','L-020','LW_-010','LWA_PT_035','LWA_PT_055','RBP0W','RET_MAG','R-010','R-000','RWA_PT_035','RWA_PT_055','TPH')
ID <- c(111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126)
df <- data.frame(ID,Category)
df
ID Category
1 111 D_L
2 112 D_R
3 113 FA1
4 114 LBP0W
5 115 L-010
6 116 L-020
7 117 LW_-010
8 118 LWA_PT_035
9 119 LWA_PT_055
10 120 RBP0W
11 121 RET_MAG
12 122 R-010
13 123 R-000
14 124 RWA_PT_035
15 125 RWA_PT_055
16 126 TPH
我使用sqldf将我的数据集过滤成2类。
df_R <- sqldf("SELECT * FROM df
WHERE Category NOT LIKE '%_L'
AND Category NOT LIKE 'LW_%'
AND category NOT LIKE 'L-%'
AND category NOT LIKE 'LB%'")
df_L <- sqldf("SELECT * FROM df
WHERE Category NOT LIKE '%_R'
AND Category NOT LIKE 'RW_%'
AND category NOT LIKE 'R-%'
AND category NOT LIKE 'RB%'")
这里我得到了两个数据帧。挑战是:
1)对于df_R -我需要返回"RWA_PT_035“而不是"RWA_PT_055”类别2)的df_L -我需要返回"LWA_PT_035“而不是"LWA_PT_055”类别
所以当我尝试这样做的时候
df_R <- sqldf("SELECT * FROM df
WHERE Category NOT LIKE '%_L'
AND Category NOT LIKE 'LW_%'
AND Category NOT LIKE 'L-%'
AND Category NOT LIKE 'LB%'
AND Category LIKE 'RWA_PT_035'")
它只返回一个观测值,即df_R的“df_R”,但我想要的输出是
ID Category
1 112 D_R
2 113 FA1
3 120 RBP0W
4 121 RET_MAG
5 122 R-010
6 123 R-000
7 124 RWA_PT_035
8 126 TPH
对于df_L
ID Category
1 111 D_L
2 113 FA1
3 114 LBP0W
4 115 L-010
5 116 L-020
6 117 LW_-010
7 118 LWA_PT_035
8 121 RET_MAG
9 126 TPH
我想知道我是否可以在查询中同时使用“喜欢”和“不喜欢”,就像上面这样?或者有其他方法可以做到吗?
我还可以使用其他方法,如data.table或dplyr,而不是sqldf。
发布于 2015-09-22 12:54:30
我从大卫·阿伦堡那里得到了答案
df[!grepl("_R|RWA_|R-|RB|_PT_055", df$Category),]
发布于 2015-09-22 13:18:59
使用sqldf
复制@DavidArenburg解决方案
#Using @DavidArenburg solution:
res1 <- df[!grepl("_R|RWA_|R-|RB|_PT_055", df$Category),]
#Using sqldf
library(sqldf)
res2 <- sqldf("SELECT * FROM df
WHERE Category NOT LIKE '%_R' AND
Category NOT LIKE 'RWA_%' AND
Category NOT LIKE 'R-%' AND
Category NOT LIKE 'RB%' AND
Category NOT LIKE '%_PT_055'")
# res1 == res2
# ID Category
# 1 TRUE TRUE
# 3 TRUE TRUE
# 4 TRUE TRUE
# 5 TRUE TRUE
# 6 TRUE TRUE
# 7 TRUE TRUE
# 8 TRUE TRUE
# 11 TRUE TRUE
# 16 TRUE TRUE
https://stackoverflow.com/questions/32704666
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