【发布时间】：2020-03-25 06:54:02
【问题描述】：
这似乎很简单，但无法弄清楚。我想在 df2 (impute_id) 中创建一个新列，用于标识值 (measurement) 是否是估算的，或者它是否是来自 df1。如果行匹配，则在 df2 的新列中，impute_id，分配字符串observed，如果行不匹配，则分配字符串imputed。如果可能的话，我想使用dplyr 来做到这一点。还要注意的是，即使在示例中，数据框中的行的顺序也可能不同。
示例
原始数据
df1
time protocol measurement_type sample measurement
1 0 HPLC cis,cis-Muconic acid a 0.57561
2 0 HPLC D-Glucose a NA
3 0 HPLC cis,cis-Muconic acid a NA
4 0 HPLC D-Glucose b NA
5 0 OD600 Optical Density b 0.14430
6 22 HPLC cis,cis-Muconic acid b NA
7 22 HPLC D-Glucose a NA
8 22 OD600 Optical Density a NA
9 24 HPLC cis,cis-Muconic acid a NA
10 24 HPLC D-Glucose b 33.95529
估算数据
df2
time protocol measurement_type sample measurement
1 0 HPLC cis,cis-Muconic acid a 0.57561
2 0 HPLC D-Glucose a 33.95529
3 0 HPLC cis,cis-Muconic acid a 0.57561
4 0 HPLC D-Glucose b 33.95529
5 0 OD600 Optical Density b 0.14430
6 22 HPLC cis,cis-Muconic acid b 0.57561
7 22 HPLC D-Glucose a 33.95529
8 22 OD600 Optical Density a 0.14430
9 24 HPLC cis,cis-Muconic acid a 0.57561
10 24 HPLC D-Glucose b 33.95529
期望的输出
df2
time protocol measurement_type sample measurement impute_id
1 0 HPLC cis,cis-Muconic acid a 0.57561 observed
2 0 HPLC D-Glucose a 33.95529 imputed
3 0 HPLC cis,cis-Muconic acid a 0.57561 imputed
4 0 HPLC D-Glucose b 33.95529 imputed
5 0 OD600 Optical Density b 0.14430 observed
6 22 HPLC cis,cis-Muconic acid b 0.57561 imputed
7 22 HPLC D-Glucose a 33.95529 imputed
8 22 OD600 Optical Density a 0.14430 imputed
9 24 HPLC cis,cis-Muconic acid a 0.57561 imputed
10 24 HPLC D-Glucose b 33.95529 observed
可重现的数据
原始数据
df1 <- structure(list(time = c(0L, 0L, 0L, 0L, 0L, 22L, 22L, 22L, 24L,
24L), protocol = structure(c(1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L,
1L, 1L), .Label = c("HPLC", "OD600"), class = "factor"), measurement_type = structure(c(1L,
2L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L), .Label = c("cis,cis-Muconic acid",
"D-Glucose", "Optical Density"), class = "factor"), sample = c("a",
"a", "a", "b", "b", "b", "a", "a", "a", "b"), measurement = c(0.57561,
NA, NA, NA, 0.1443, NA, NA, NA, NA, 33.95529)), row.names = c(NA,
-10L), class = "data.frame")
估算数据
df2 <- structure(list(time = c(0L, 0L, 0L, 0L, 0L, 22L, 22L, 22L, 24L,
24L), protocol = structure(c(1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L,
1L, 1L), .Label = c("HPLC", "OD600"), class = "factor"), measurement_type = structure(c(1L,
2L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L), .Label = c("cis,cis-Muconic acid",
"D-Glucose", "Optical Density"), class = "factor"), sample = c("a",
"a", "a", "b", "b", "b", "a", "a", "a", "b"), measurement = c(0.57561,
33.95529, 0.57561, 33.95529, 0.1443, 0.57561, 33.95529, 0.1443,
0.57561, 33.95529)), row.names = c(NA, -10L), class = "data.frame")
【问题讨论】：
标签： r dataframe conditional-statements dplyr