How to subset a sapply function output [duplicate] - r

This question already has answers here:
Extracting nth element from a nested list following strsplit - R
(4 answers)
Closed 5 years ago.
Given a dataframe, I would like to use strsplit on one of my columns, and return the first element of the vector. Here is the example:
testdf<- data.frame(col1= c('string1.string2', 'string3.string4'),
col2= c('somevalue', 'someothervalue'),
stringsAsFactors = FALSE)
I want to generate a new column such as
testdf$col3 <- c('string1', 'string3')
I tried the following:
testdf$col3<- strsplit(testdf$col1, split = '\\.')[[1]])[1]
which, of course, doesn't work. It returns just the first element of the output ('string1') and writes it for the whole column.
One solution would be to write a custom function:
customfx<- function(ind_cell){
my_out<- strsplit(ind_cell, split = '\\.')[[1]][1]
return(my_out)}
Then use it with sapply. I was wondering if there is an alternative to this. The talking stick is yours :)

You can use sub (which is vectorized) with regex for this:
testdf$col3 <- sub("^([^.]+).*", "\\1", testdf$col1)
testdf
# col1 col2 col3
#1 string1.string2 somevalue string1
#2 string3.string4 someothervalue string3
Here use ^([^.]+).* to match the whole string and capture the substring from the beginning until a dot is met, then replace the whole string with the captured group using back reference.

Related

Changing a full last name to just the first letter of the name in R [duplicate]

This question already has answers here:
Getting and removing the first character of a string
(7 answers)
Extract the first (or last) n characters of a string
(5 answers)
Closed 2 years ago.
I'm working in R. I have a dataset with people first and last names. There is a column called "First" and another column called "Last".
I want to change "Bodie" to just "B" and do the same for all the observations in the "Last" column.
I'm newer to programming so I don't even know where to start. I have looked at some of the string packages in R and can't quite figure out what to do. Thanks for the help.
We can use substr to extract the first letter of the 'Last' column
df1$Last <- substr(df1$Last, 1, 1)
Or sub to remove all the characters other than the first
df1$Last <- sub("^(.).*", "\\1", df1$Last)
Or another option is to split the characters, select the first element
df1$Last <- sapply(strsplit(df1$Last, ""), `[`, 1)
Just a variation on the #akrun answer which uses sub sans a capture group:
df1$Last <- sub("(?<=.).*$", "", df1$Last, perl=TRUE)

Filter row based on a string condition, dplyr filter, contains [duplicate]

This question already has answers here:
Selecting data frame rows based on partial string match in a column
(4 answers)
Closed 1 year ago.
I want to filter a dataframe using dplyr contains() and filter. Must be simple, right? The examples I've seen use base R grepl which sort of defeats the object. Here's a simple dataframe:
site_type <- c('Urban','Rural','Rural Background','Urban Background','Roadside','Kerbside')
df <- data.frame(row_id, site_type)
df <- as.tibble(df)
df
Now I want to filter the dataframe by all rows where site.type contains the string background.
I can find the string directly if I know the unique values of site_type:
filtered_df <- filter(df, site_type == 'Urban Background')
But I want to do something like:
filtered_df <- filter(df, site_type(contains('background', match_case = False)))
Any ideas how to do that? Can dplyr helper contains only be used with columns and not rows?
The contains function in dplyr is a select helper. It's purpose is to help when using the select function, and the select function is focused on selecting columns not rows. See documentation here.
filter is the intended mechanism for selecting rows. The function you are probably looking for is grepl which does pattern matching for text.
So the solution you are looking for is probably:
filtered_df <- filter(df, grepl("background", site_type, ignore.case = TRUE))
I suspect that contains is mostly a wrapper applying grepl to the column names. So the logic is very similar.
References:
grep R documentation
high rated question applying exactly this technique

Passing a vector through a select statement [duplicate]

This question already has answers here:
grep using a character vector with multiple patterns
(11 answers)
Closed 3 years ago.
Looking for help to find a way to pass a vector of strings into a select statement. I want to subset a data frame to only output variables that contain the same string as my vector. I don't want it to match exactly and hence need to pass a function like contains as there are some text in the data frame variables that I do not have in my vector.
here is an example of the vector I want to pass into my select statement.
c("clrs_name", "_clrs_sitedetails_value", "_clrs_targetlicence_value",
"clrs_licenceclass", "clrs_licenceownership", "clrs_type", "statuscode")
For example, I want to extract the variable "odate_value_clrs_name" from my data frame and the string "clrs_name" in vector should extract that, but I am not sure how to incorporate contains and a vector into a select statement.
We can use matches in select after collapseing the pattern vector with | by either paste from base R or str_c (str_c would also return NA if there are any NAs). This would not return any error or warning if one of the pattern is missing or doesn't have any match with the column names
library(dplyr)
library(stringr)
df1 %>%
select(matches(str_c(v1, collapse = "|")))
where
v1 <- c("clrs_name", "_clrs_sitedetails_value", "_clrs_targetlicence_value",
"clrs_licenceclass", "clrs_licenceownership", "clrs_type", "statuscode")

Loop Through Column Names with Similar Structure [duplicate]

This question already has answers here:
How to extract columns with same name but different identifiers in R
(3 answers)
Closed 3 years ago.
I have a very large dataset. Of those, a small subset have the same column name with an indexing value that is numeric (unlike the post "How to extract columns with same name but different identifiers in R" where the indexing value is a string). For example
Q_1_1, Q_1_2, Q_1_3, ...
I am looking for a way to either loop through just those columns using the indices or to subset them all at once.
I have tried to use paste() to write their column names but have had no luck. See sample code below
Define Dataframe
df = data.frame("Q_1_1" = rep(1,5),"Q_1_2" = rep(2,5),"Q_1_3" = rep(3,5))
Define the Column Name Using Paste
cn <- as.symbol(paste("Q_1_",1, sep=""))
cn
df$cn
df$Q_1_1
I want df$cn to return the same thing as df$Q_1_1, but df$cn returns NULL.
If you are just trying to subset your data frame by column name, you could use dplyr for subseting all your indexed columns at once and a regex to match all column names with a certain pattern:
library(dplyr)
df = data.frame("Q_1_1" = rep(1,5),"Q_1_2" = rep(2,5),"Q_1_3" = rep(3,5), "A_1" = rep(4,5))
newdf <- df %>%
dplyr::select(matches("Q_[0-9]_[0-9]"))
the [0-9] in the regex matches any digit between the _. Depending on what variable you're trying to match you might have to change the regular expression.
The problem with your solution was that you only saved the name of your columns but did not actually assign it back to the data frame / to a column.
I hope this helps!

! grep in R - finding items that do not match [duplicate]

This question already has answers here:
Using grep in R to delete rows from a data.frame
(5 answers)
Closed 8 years ago.
I want to find rows in a dataframe that do not match a pattern.
Key = c(1,2,3,4,5)
Code = c("X348","I605","B777","I609","F123")
df1 <- data.frame(Key, Code)
I can find items beginning with I60 using:
df2 <- subset (df1, grepl("^I60", df1$Code))
But I want to be able to find all the other rows (that is, those NOT beginning with I60). The invert argument does not work with grepl. grep on its own does not find all rows, nor can it pass the results to the subset command. Grateful for help.
You could use the [ operator and do
df1[!grepl("I60", Code),]
(Suggested clarification from #Hugh:) Another way would be
df1[!grepl("I60",df1$Code),]
Here is the reference manual on array indexing, which is done with [:
http://cran.r-project.org/doc/manuals/R-intro.html#Array-indexing
Also, you can try this:
Key = c(1,2,3,4,5)
Code = c("X348","I605","B777","I609","F123")
df1 <- data.frame(Key, Code)
toRemove<-grep("^I60", df1$Code)
df2 <- df1[-toRemove,]

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