Selecting data frame rows based on partial string match in a column

Question

I notice that you mention a function %like% in your current approach. I don't know if that's a reference to the %like% from "data.table", but if it is, you can definitely use it as follows.

Note that the object does not have to be a data.table (but also remember that subsetting approaches for data.frames and data.tables are not identical):

library(data.table)
mtcars[rownames(mtcars) %like% "Merc", ]
iris[iris$Species %like% "osa", ]

If that is what you had, then perhaps you had just mixed up row and column positions for subsetting data.

---

If you don't want to load a package, you can try using grep() to search for the string you're matching. Here's an example with the mtcars dataset, where we are matching all rows where the row names includes "Merc":

mtcars[grep("Merc", rownames(mtcars)), ]
             mpg cyl  disp  hp drat   wt qsec vs am gear carb
# Merc 240D   24.4   4 146.7  62 3.69 3.19 20.0  1  0    4    2
# Merc 230    22.8   4 140.8  95 3.92 3.15 22.9  1  0    4    2
# Merc 280    19.2   6 167.6 123 3.92 3.44 18.3  1  0    4    4
# Merc 280C   17.8   6 167.6 123 3.92 3.44 18.9  1  0    4    4
# Merc 450SE  16.4   8 275.8 180 3.07 4.07 17.4  0  0    3    3
# Merc 450SL  17.3   8 275.8 180 3.07 3.73 17.6  0  0    3    3
# Merc 450SLC 15.2   8 275.8 180 3.07 3.78 18.0  0  0    3    3

And, another example, using the iris dataset searching for the string osa:

irisSubset <- iris[grep("osa", iris$Species), ]
head(irisSubset)
#   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
# 1          5.1         3.5          1.4         0.2  setosa
# 2          4.9         3.0          1.4         0.2  setosa
# 3          4.7         3.2          1.3         0.2  setosa
# 4          4.6         3.1          1.5         0.2  setosa
# 5          5.0         3.6          1.4         0.2  setosa
# 6          5.4         3.9          1.7         0.4  setosa

For your problem try:

selectedRows <- conservedData[grep("hsa-", conservedData$miRNA), ]

Try str_detect() from the stringr package, which detects the presence or absence of a pattern in a string.

Here is an approach that also incorporates the %>% pipe and filter() from the dplyr package:

library(stringr)
library(dplyr)

CO2 %>%
  filter(str_detect(Treatment, "non"))

   Plant        Type  Treatment conc uptake
1    Qn1      Quebec nonchilled   95   16.0
2    Qn1      Quebec nonchilled  175   30.4
3    Qn1      Quebec nonchilled  250   34.8
4    Qn1      Quebec nonchilled  350   37.2
5    Qn1      Quebec nonchilled  500   35.3
...

This filters the sample CO2 data set (that comes with R) for rows where the Treatment variable contains the substring "non". You can adjust whether str_detect finds fixed matches or uses a regex - see the documentation for the stringr package.

LIKE should work in sqlite:

require(sqldf)
df <- data.frame(name = c('bob','robert','peter'),id=c(1,2,3))
sqldf("select * from df where name LIKE '%er%'")
    name id
1 robert  2
2  peter  3

Another option would be to simply use grepl function:

df[grepl('er', df$name), ]
CO2[grepl('non', CO2$Treatment), ]

df <- data.frame(name = c('bob','robert','peter'),
                 id = c(1,2,3)
                 )

# name id
# 2 robert  2
# 3  peter  3