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How to skip lines based on a string in R?
Im attempting to create a df from a tsv file and I need to skip lines after a delimiter string "[data]". So I want to know how many lines I need to skip to grab the header located below the "[data]" string.
In python I would load the file as a string and find the line number. But I can figure it out on R.
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I want to run a binary logistic regression in R but I see this error:
Error in if (!length(fname) || !any(fname == zname)) { :
missing value where TRUE/FALSE needed
It happens because I use variables with $. For example data$HEIGHT.
I use read.table() for importing .txt file.
How can I use HEIGHT instead of data$HEIGHT?
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Unfortunately I have to deal with a data file with .int file format. This has the effect of littering any search results with unrelated information about integers.
I can't figure out how to open this file in R. I have an example with the Julia language, shown below:
filename = "mnist_train.int"
open(filename) do f
...
end
But when I try to search for a similar function in R, I either find results about opening excel files, results for other languages, or results that deal with integers. Could someone please point me to some resources for dealing with this filetype?
Because I am not sure about what the content type, guess you trying to open a binary file format.
You can have a look at ?readBin
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I am trying to write this (SAS) comand in R. x is a variable with this specific format: j61915035t
x1 = trim(upcase(substr(x,1,1)));
I really appreciate what you are doing in this site!
You want to remove leading/trailing blanks from a character string that is the uppercase first letter of the string x. So this should do it.
library(stringr)
x1 = str_trim(str_to_upper(str_sub(x,1,1)))
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I'm working on a project in R, regarding baseball. I have two CSV's that I'm working with. One file, CSV2: "PitchingPost.csv" is all postseason pitching stats, and the column I'm looking at there is the "teamID". I'm trying to evaluate regular season pitching stats in another file, CSV1: "pitching.csv" but only for teams that made the postseason. So I'm trying to remove all of the items in the "teamID" of CSV1 EXCEPT for those occur in CSV2 "teamID".
Help?
To keep only the rows from your first file that share an ID with rows in your second file, you could try something like that:
pitch <- read.csv("pitching.csv")
pitch_post <- read.csv("PitchingPost.csv")
pitch <- pitch[pitch$teamID %in% unique(pitch_post$teamID),]
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I loaded a RDS file. The file contains a numeric field. When I say
class(NEI$Emissions)
it returns
"numeric"
The data is in maximum 3 digits and contains 3 digits of decimal. However, when I issue the command
max(NEI$Emissions)
it returns a huge number.
646952
How can I use the numeric values as it is?
R doesn't lie. One of your data points is not what you expect.
Find which row has the problem with this command:
which.max(NEI$Emissions)
then examine that row of your original data. You will find the errant value.