readr

Writing a data frame with a mix of small integer entries (value less than 1000) and "large" ones (value 1000 or more) into csv file with write_csv() mixes scientific and non-scientific entries. If the first 1000 rows are small values but there is a large value thereafter, read_csv() seems to get confused with this mix and outputs NA for scientific notations: test_write_read <- function(small_value, n_fills, position, large_value) { tib <- tibble(a = rep(small_value, n_fills)) tib$a[position] <- large_value write_csv(tib, "tib.csv") tib <- read_csv("tib.csv") } The following lines do not make

When I try to do something like this: data <- read_csv("blah.csv", + n_max = 100, + col_types = cols_only(list(files = "c")) + ) Error: Some `col_types` are not S3 collector objects: 1 so question is whether it is possible to pass a named list to cols_only() Sure, just use do.call to use the list as the parameters for the function, e.g. library(readr) read_csv(system.file('extdata', 'mtcars.csv', package = 'readr'), # sample data from readr col_types = do.call(cols_only, list(cyl = 'i'))) #> # A tibble: 32 × 1 #> cyl #> <int> #> 1 6 #> 2 6 #> 3 4 #> 4 6 #> 5 8 #> 6 6 #> 7 8 #> 8 4 #> 9 4 #> 10

I would like to parse my columns with the readr package to the right type while reading. Difficulty: the fields are separated by semicolon ( ; ), while comma ( , ) is used as decimal mark. library(readr) # Test data: T <- "Date;Time;Var1;Var2 01.01.2011;11:11;2,4;5,6 02.01.2011;12:11;2,5;5,5 03.01.2011;13:11;2,6;5,4 04:01.2011;14:11;2,7;5,3" read_delim(T, ";") # A tibble: 4 × 4 # Date Time Var1 Var2 # <chr> <time> <dbl> <dbl> # 1 01.01.2011 11:11:00 24 56 # 2 02.01.2011 12:11:00 25 55 # 3 03.01.2011 13:11:00 26 54 # 4 04:01.2011 14:11:00 27 53 So, I thought the parsing thing would work like

I'm trying to import a dataset to RStudio, however I am stuck with Chinese characters, as they become messy codes. Here is the code: library(tidyverse) df <- read_csv("中文,英文\n英文,德文") df # A tibble: 1 x 2 `\xd6\xd0\xce\xc4` `Ӣ\xce\xc4` <chr> <chr> 1 "<U+04E2>\xce\xc4" "<U+00B5>\xc2\xce\xc4" When I use the base function read.csv, it works well. I guess I must do something wrong with encoding. But there are no encoding option in read_csv, how can I do this? This is because that the characters are marked as UTF-8 whereas the actual encoding is the system default (you can get by stringi::stri_enc

I am currently reading in a file using the package readr . The idea is to use read_delim to read in row for row to find the maximum columns in my unstructured data file. The code outputs that there are parsing problems. I know of these and will deal with column type after import. Is there a way to turn off the problems() as the usual options(warn) is not working i=1 max_col <- 0 options(warn = -1) while(i != "stop") { n_col<- ncol(read_delim("file.txt", n_max = 1, skip = i, delim="\t")) if(n_col > max_col) { max_col <- n_col print(max_col) } i <- i+1 if(n_col==0) i<-"stop" } options(warn = 0)

I'm trying to create separate .csv files for each group in a data frame grouped with dplyr's group_by function. So far I have something like by_cyl <- group_by(mtcars, cyl) do(by_cyl, write_csv(., "test.csv")) As expected, this writes a single .csv file with only the data from the last group. How can I modify this to write multiple .csv files, each with filenames that include cyl? You can wrap the csv write process in a custom function as follows. Note that the function has to return a data.frame else it returns an error Error: Results are not data frames at positions This will return 3 csv