GOAL: A frequent situation I encounter is when I have a number of dataframes (resulting from some analysis) in my environment and want to convert in .csv files to save or share - while retaining the same name(s). Below are a few different ways to do it.
# Explore R default datasets
# data()
# I save them as DFs in my env
mtcars <- as.data.frame(mtcars)
iris <- as.data.frame(iris)
orange <- as.data.frame(Orange)
titanic <- as.data.frame(Titanic)
Orange <- as.data.frame(Orange)
OrchardSprays <- as.data.frame(OrchardSprays)
airquality <- as.data.frame(airquality)
airmiles <- as.data.frame(airmiles)
### 1.a) Create a list of n data frames
list_dfs <- list(mtcars, iris , orange, titanic)
list_dfs[1]
### 1.b) Give names the data frames
names(list_dfs) <- c("mtcars","iris", "orange" , "titanic")
### 2) Create a list of n data frames & GIVE thema name
list_dfs_N <- list(mtcars = mtcars, iris = iris,
orange = orange, titanic = titanic )
list_dfs_N[[1]]
# Create Output Dir... remember final"/"
Outdf2csv <- file.path(".", "_posts","2018-09-28-dirs-files2", "df2csv/")
dir.create(Outdf2csv)
# Dir_pcr <- file.path(".", "_posts","2018-09-28-dirs-files2","pcr/")
# dir.create(Dir_pcr)
NOTE length(list_loop_DF) # = to the
length of the list -> WRONG! (I need apply to all elements)
seq_along(list_loop_DF) # generates a sequence long as the
list -> OK!
# Create a list of NAMED dataframes
list_loop_DF <- list(airquality = airquality, airmiles = airmiles)
# Write a .csv file with each
for (i in seq_along(list_loop_DF)) { # generate a sequence along with
# returns list of same length as x
# Outdf2csv <- if (!dir.exists("./zzz_purrr/Output/")){
# dir.create(file.path("./zzz_purrr/Output/"))
#}
# else {print("Dir already exists!")}
write.csv(x = list_loop_DF[[i]],
file = paste0(Outdf2csv, names(list_loop_DF[i]) , ".csv") )
# OutDir <- if (!dir.exists("./zzz_purrr/Output/")){
# dir.create(file.path("./zzz_purrr/Output/"))
# }
# else {print("Dir already exists!")}
write.csv(x = list_loop_DF[[i]],
file = paste0(Outdf2csv, names(list_loop_DF[i]) , ".csv") )
}
In simple form, this is what I am going to do:
`MyFunc <- function (list, OutputDir) { `
` OutputDir <- ..set dir location.`
` lapply(X = forall(list), FUN, ...)`
` }`# Create a list of NAMED dataframes
list_lapply_DF <- list(mtcars = mtcars, titanic = titanic ) #
# Output... remember final"/"
# Outdf2csv <- file.path(".", "content","post", "df2csv/")
# dir.create(Outdf2csv)
# Write the function with arguments (DFlist, OutputDir)
Func_list_lapply <- function(list_lapply_DF) { # optional arg2 (Outdf2csv)
# Outdf2csv <- if (!dir.exists("./zzz_purrr/Output/")){
# dir.create(file.path("./zzz_purrr/Output/"))
# }
# else {print("Dir already exists!")}
lapply(1:length(list_lapply_DF), # from 1 to n = lenght of "x"
function(i) write.csv(list_lapply_DF[[i]], # after applying a "function"
file = paste0(Outdf2csv,
names(list_lapply_DF[i]),
".csv"),
row.names = FALSE))
}
# Call the function
Func_list_lapply(list_lapply_DF)
NOTE Writing a file to a disk is considered to be a
side-effect: we are not interested in changing our data, so should use
walk instead of map.
Using walk2(.x, .y, .f, ... where .x and
.y are vectors of the same length .f is a
2-argument function
# Create a list of NAMED dataframes
list_purrr_DF <- list(Orange = Orange, OrchardSprays = OrchardSprays ) #
# Set the Output Dir to an object
# Outdf2csv <- file.path(".", "content","post", "df2csv/")
# dir.create(Outdf2csv)
path <- file.path(paste0(Outdf2csv, names(list_purrr_DF), ".csv"))
walk2(list_purrr_DF, path, write.csv)
Intructions found in I need to get back to this …
# Data
# unzip(zipfile = "pcr.zip", exdir = "./content/post/pcr")
# will create a data/pcr subfolder and extract the files
pcr_files <- list.files(
file.path("_posts","2018-09-28-dirs-files2","pcr"), full.names = TRUE)
#=== map() will name each output element asin the input vector.
list.files(file.path(
"_posts","2018-09-28-dirs-files2","pcr"), full.names = TRUE) %>%
set_names() %>% # Use set_names() to keep this information.
map(read_delim, delim = " ") %>%
names()
#=== remove the path and extension from the filename using basename() and tools::file_path_sans_ext()
list.files(file.path("_posts","2018-09-28-dirs-files2", "pcr"),
full.names = TRUE) %>%
set_names(nm = (basename(.) %>% # remove PATH
tools::file_path_sans_ext())) %>% # remove .ext
map(read_delim, delim = " ") %>%
names()
# Getting a single tibble out of all files would be much handier.---> map_df
list.files(file.path(
"_posts","2018-09-28-dirs-files2", "pcr"), full.names = TRUE) %>%
set_names(nm = (basename(.) %>% # remove PATH
tools::file_path_sans_ext())) %>% # remove .ext
map_df(read_delim, delim = " ", .id = "filename")
# ====Rearrange the data and save multiple files
dir.create(file.path(
"_posts","2018-09-28-dirs-files2", "by_gene"), showWarnings = FALSE)
# Method 1: using walk2 but inside a mutate call
list.files(file.path(
"_posts","2018-09-28-dirs-files2", "pcr"), full.names = TRUE) %>%
set_names(nm = (basename(.) %>% tools::file_path_sans_ext())) %>%
map_df(read_delim, delim = " ", .id = "filename") %>%
group_by(gene) %>%
nest() %>%
mutate(file_out = paste0(gene, ".csv"),
file_out_path = file.path(
"_posts","2018-09-28-dirs-files2", "by_gene", file_out),
data = walk2(data, file_out_path, write_csv))
# Method 2: using walk on the transposed tibble with an anonymous function
list.files(file.path(
"_posts","2018-09-28-dirs-files2", "pcr"), full.names = TRUE) %>%
set_names(nm = (basename(.) %>% tools::file_path_sans_ext())) %>%
map_df(read_delim, delim = " ", .id = "filename") %>%
group_by(gene) %>%
nest() %>%
mutate(file_out = paste0(gene, ".csv"),
file_out_path = file.path(
"_posts","2018-09-28-dirs-files2", "by_gene", file_out)) %>%
transpose() %>%
walk(~write_csv(.$data, .$file_out_path))
In this case, the five new files (one for each bat family) will end up in the working directory, but if we want to do this with more files and dedicated directories then using the here and glue packages is probably a good idea. Useful link
# read csv from web
batRecs <- utils::read.csv(
"https://raw.githubusercontent.com/luisDVA/codeluis/master/batRecords.csv",
stringsAsFactors = FALSE)
# drop na, split, remove duplicates, write to disk
batRecs %>% na.omit() %>%
# split to create a list of data frames for each group,
split(.$family) %>%
# then map to apply functions to each list element. I
map(~distinct(.x,
decimal_latitude,
decimal_longitude,
.keep_all=TRUE)) %>%
# walk because write.csv returns nothing and creates the csv file as a side effect
walk(~.x %>% write.csv(file = paste0(Outdf2csv, "nov1_", unique(.x$family),
".csv"),
row.names = FALSE)
)