I have a list containing 180.000 elements each represents data about an investor and a specific traded asset.
I want to save all the elements of the list into single dataframes called df into a specific folder "dev/test-data/investors-singleass/" , so that I can later on apply a specific function on all the dfs of the folder
The list of my data has a structure similar to this
list(`4Z627.004125` = structure(list(investor = c("4Z627", "4Z627",
"4Z627"), asset = c("004125", "004125", "004125"), datetime = c("2015-05-12",
"2015-05-28", "2016-08-19"), Avgprice = c(169.4, 168, 162), operation = c(2000,
1000, -3000), portfolio = c(2000, 3000, 0), last_port = c(0,
2000, 3000), marketprice = c(169.4, 166.5, 161.75), portprice = c(169.4,
168.933333333333, 0), G = c(0, 0, 1), gainminus = c(2, 0, 0),
numasset = c(5, 8, 13)), row.names = c(NA, -3L), class = c("tbl_df",
"tbl", "data.frame"))
Basically each elements of the list is an "investor" ID and an "asset" code for which i then have multiple other columns to work with
I would do it like this based on link
df1 <- list(`4Z627.004125` = structure(list(investor = c("4Z627", "4Z627",
"4Z627"), asset = c("004125", "004125", "004125"),
datetime = c("2015-05-12", "2015-05-28", "2016-08-19"),
Avgprice = c(169.4, 168, 162),
operation = c(2000, 1000, -3000), portfolio = c(2000, 3000, 0),
last_port = c(0,2000, 3000), marketprice = c(169.4, 166.5, 161.75),
portprice = c(169.4,
168.933333333333, 0), G = c(0, 0, 1), gainminus = c(2, 0, 0),
numasset = c(5, 8, 13)), row.names = c(NA, -3L),
class = c("tbl_df", "tbl", "data.frame")),
`4Z628.004128` = structure(list(investor = c("4Z627", "4Z627",
"4Z627"), asset = c("004125", "004125", "004125"),
datetime = c("2015-05-12", "2015-05-28", "2016-08-19"),
Avgprice = c(169.4, 168, 162),
operation = c(2000, 1000, -3000), portfolio = c(2000, 3000, 0),
last_port = c(0,2000, 3000), marketprice = c(169.4, 166.5, 161.75),
portprice = c(169.4,
168.933333333333, 0), G = c(0, 0, 1), gainminus = c(2, 0, 0),
numasset = c(5, 8, 13)), row.names = c(NA, -3L),
class = c("tbl_df", "tbl", "data.frame")))
library(purrr)
iwalk(df1, ~saveRDS(.x, paste0("dev/test-data/investors-singleass/", .y, '.RData')))
You can get the data back into R with
library(dplyr)
df <- list.files(path = "dev/test-data/investors-singleass/", pattern = ".RData") %>%
map_dfr(readRDS)