read.table

I have a file with the data c("A","T","B","F") . When I use: read.csv(myfile,header=F,stringsAsFactors=F) R interprets character T as TRUE and F as FALSE Am I doing anything wrong? If all your columns are characters then try this: # replace text = . with your filename read.csv(text="A,B,T,T", header=FALSE, stringsAsFactors=FALSE, colClasses = c("character")) Else, you'll have to pass the type of each column in colClasses as: colClasses = c("numeric", "numeric", "character", ...) I came across to similar problem here is the solution: #dummy data df <- read.csv(text=" A,B,T,T,F T,T,F,T,text1 A,T

I have a file looks like: a 1,2,3,5 b 4,5,6,7 c 5,6,7,8 ... That the separator between 1st and 2nd is '\t', other separators are comma. How can I read this kind of data set as as dataframe having 5 fields. I'd probably do this. read.table(text = gsub(",", "\t", readLines("file.txt"))) V1 V2 V3 V4 V5 1 a 1 2 3 5 2 b 4 5 6 7 3 c 5 6 7 8 Unpacking that just a bit: readLines() reads the file into R as a character vector with one element for each line. gsub(",", "\t", ...) replaces every comma with a tab, so that now we've got lines with just one kind of separating character. The text = argument to

I have 91 files - .log format: rajectory Log File Rock type: 2 (0: Sphere, 1: Cuboid, 2: Rock) Nr of Trajectories: 91 Trajectory-Mode: ON Average Slope (Degrees): 28.05 / 51.99 / 64.83 Filename: test_tschamut_Pos1.xml Z-offset: 1.32000 Rock Position X: 696621.38 Rock Position Y: 167730.02 Rock Position Z: 1679.6400 Friction: Overall Type: Medium t (s) x (m) y (m) z (m) p0 () p1 () p2 () p3 () vx (m s-1) vy (m s-1) vz (m s-1) wx (rot s-1) wy (rot s-1) wz (rot s-1) Etot (kJ) Ekin (kJ) Ekintrans (kJ) Ekinrot (kJ) zt (m) Fv (kN) Fh (kN) Slippage (m) mu_s (N s m-1) v_res (m s-1) w_res (rot s-1)

I have a dataset with about 2 million rows, so without reading the whole dataset I want to read a subset of dataset . My dataset contains a date column in it so I just want to read dataset between a date range without reading whole dataset as it will be time consuming and memory waste. so how to accomplish it can anyone guide me on this ? Olli J Use skip= parameter in read.table read.table("file.txt",skip= ,nrows= ) Both the skip= and nrows= take in row indicator numbers so just add them after the=. The nrows= defines how deep you range when you are importing the file. I suggest reading https:

When reading a file, the read.table function uses type.convert to distinguish between logical, integer, numeric, complex, or factor columns and store them accordingly. I'd like to add dates to the mix, so that columns containing dates can automatically be recognized and parsed into Date objects. Only a few date formats should be recognized, e.g. date.formats <- c("%m/%d/%Y", "%Y/%m/%d") Here is an example: fh <- textConnection( "num char date-format1 date-format2 not-all-dates not-same-formats 10 a 1/1/2013 2013/01/01 2013/01/01 1/1/2013 20 b 2/1/2013 2013/02/01 a 2013/02/01 30 c 3/1/2013 NA b

Is there a way for fread to mimic the behaviour of read.table whereby the class of the variable is set by the data that is read in. I have numeric data with a few comments underneath the main data. When i use fread to read in the data, the columns are converted to character. However, by setting the nrow in read.table` i can stop this behaviour. Is this possible in fread. (I would prefer not to alter the raw data or make an amended copy). Thanks An example d <- data.frame(x=c(1:100, NA, NA, "fff"), y=c(1:100, NA,NA,NA)) write.csv(d, "test.csv", row.names=F) in_d <- read.csv("test.csv", nrow=100

I have a file where the first row is a header. The header can have spaces and the # symbol (there may be other special characters as well). I am trying to read this file using read.csv or read.table but it keeps throwing me errors: undefined columns selected more columns than column names My tab-delimited chromFile file looks like: Chromosome# Chr chr Size UCSC NCBI36/hg18 NCBIBuild36 NCBIBuild37 1 Chr1 chr1 247199719 247249719 247249719 249250621 2 Chr2 chr2 242751149 242951149 242951149 243199373 Command: chromosomes <- read.csv(chromFile, sep="\t",skip =0, header = TRUE, ) I want to first

I want to read a txt in Rmd --- title: "Untitled" output: html_document --- ```{r} country <- read.table("country.txt") country ``` It show error: processing file: Preview-2878539db5c7.Rmd Quitting from lines 6-8 (Preview-2878539db5c7.Rmd) Error in file(file, "rt") : cannot open the connection Calls: <Anonymous> ... withCallingHandlers -> withVisible -> eval -> eval -> read.table - > file Execution halted But I can run code in R console successfully > country <- read.table("country.txt") > country production1 education1 fir1 inflation1 lq1 nonstatein1 patent1 tax1 trade1 2001 52920.47 132649.4