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I need to subset a df to include certain strings. Some of these are full column names, and the following works fine:
testData[,c("FullColName1","FullColName2","FullColName3")]
My problem is that I need to expand this to also include column names that contain specific strings that may partially match to some other column names. These strings include letters and symbols:
"PartString1()","PartString2()"
I tried putting wildcards around these. (I've indicated this below with the prefix "star" because the "*" symbol didn't render correctly.)
testData[ ,c("FullColName1","FullColName2","FullColName3",
"starPartString1()star","starPartString2()star")]
But I'm getting an error message: undefined columns selected. I can't figure out if or how I need grep to make this work.
716
How to subset the data frame (DataFrame) by column value and name in R? By using R base df[] notation, or subset() you can easily subset the R Data Frame (data. frame) by column value or by column name.
To select a column in R you can use brackets e.g., YourDataFrame['Column'] will take the column named “Column”. Furthermore, we can also use dplyr and the select() function to get columns by name or index. For instance, select(YourDataFrame, c('A', 'B') will take the columns named “A” and “B” from the dataframe.
To do a Partial String Matching in R, use the charmatch() function. The charmatch() function accepts three arguments and returns the integer vector of the same length as input.
To create a subset data set, specify the name of the subset data set on the DATA statement, bring in the full data set with a SET statement, and specify the subsetting criteria with either subsetting IF statements or WHERE statements.
You mentioned you may be looking for symbols, so for this particular example we can use [[:punct:]] as our regular expression. This will find all the strings with punctuation symbols in the column names.
d <- data.frame(1:3, 3:1, 11:13, 13:11, rep(1, 3))
names(d) <- c("FullColName1", "FullColName2", "FullColName3",
"PartString1()","PartString2()")
d[grepl("[[:punct:]]", names(d))]
# PartString1() PartString2()
# 1 13 1
# 2 12 1
# 3 11 1
This last part just illustrates another way to do this with other string processing functions from stringr
library(stringr)
d[str_detect(names(d), "[[:punct:]]")]
# PartString1() PartString2()
# 1 13 1
# 2 12 1
# 3 11 1
ADD per OPs comment
d[grepl("ring[12()]", names(d))]
to get either of the substrings ring1() or ring2() from the names vector
76
You can use grep to find indices of column names with partial match to a particular pattern
require(PerformanceAnalytics)
data(managers)
colnames(managers)
#[1] "HAM1" "HAM2" "HAM3" "HAM4" "HAM5"
#[6] "HAM6" "EDHEC LS EQ" "SP500 TR" "US 10Y TR" "US 3m TR"
suppose the pattern you want to match is "HAM", along with some fixed column names ("SP500 TR" "US 10Y TR" "US 3m TR")
head(managers[,c("SP500 TR","US 10Y TR","US 3m TR",colnames(managers)[grep("HAM",colnames(managers))])])
# SP500 TR US 10Y TR US 3m TR HAM1 HAM2 HAM3 HAM4 HAM5 HAM6
#1996-01-31 0.0340 0.00380 0.00456 0.0074 NA 0.0349 0.0222 NA NA
#1996-02-29 0.0093 -0.03532 0.00398 0.0193 NA 0.0351 0.0195 NA NA
#1996-03-31 0.0096 -0.01057 0.00371 0.0155 NA 0.0258 -0.0098 NA NA
#1996-04-30 0.0147 -0.01739 0.00428 -0.0091 NA 0.0449 0.0236 NA NA
#1996-05-31 0.0258 -0.00543 0.00443 0.0076 NA 0.0353 0.0028 NA NA
#1996-06-30 0.0038 0.01507 0.00412 -0.0039 NA -0.0303 -0.0019 NA NA
you can specify multiple patterns using, grep("pattern1 | pattern2 ", colnames(data))
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