if I print to console
AirPassengers
I is nicely formated with header and row names, why following code is not also siniliary formated?
as.ts(
read.zoo(
data.frame(
date = seq(Sys.Date()-365, Sys.Date(), by = "day"),
value = seq(1, 366)
)
)
)
When you use the read.zoo function, it resturns a zoo object, which is a type of character.
If you get rid of the function you get:
as.ts(
data.frame(
date = seq(Sys.Date()-365, Sys.Date(), by = "day"),
value = seq(1, 366)
)
)
You should get a time series object that is a matrix format
If you must use read.zoo
ts <- as.ts(
zoo::read.zoo(df)
) |> data.frame() |> setNames(names(df[2]))
)
Related
My initial data is in %y-%m-%d format...
using the code
returnsgamma <- read.zoo(returns, header = TRUE, sep = ",", FUN = as.chron)
the zoo file is returning values in the order %m/%d/%y
is there anyway to read.zoo and have the order of dates stay as %y/%m/%d or %d/%m/%y?
Assuming the input shown in the Note at the end we can use the default Date class whose output when rendering defaults to yyyy-mm-dd or use chron with chron(..., out.format="y-m-d") which produces yy-mm-dd.
library(zoo)
read.csv.zoo(text = Lines, format = "%y-%m-%d")
## 2022-12-01
## 34
library(chron)
toChron <- function(x) as.chron(x, out.format = "y-m-d")
read.csv.zoo(text = Lines, FUN = toChron)
## 22-12-01
## 34
Note
Lines <- "date,value
22-12-01,34"
I have runtime data for various devices that can be widely different, ranging from a few minutes to several months that I would like to display in a datatable. So I thought the seconds_to_period function from lubridate provides a neat format to print this data. However, I seem unable to display it within a datatable from DT, which is what I want to do (within a shiny App).
Some example data:
library(lubridate)
library(DT)
names <- c("A","B","C","D","E","F")
timevec <- c(225,2250,22500,225000,2250000,22500000)
timevec <- seconds_to_period(timevec)
Writing this into a datatable without any formatting does not work as it only displays the seconds without considering the minutes/hours etc.:
##### This cuts off at the seconds -> useless
table <- data.frame(name = names, time = timevec)
my_table <- datatable(table)
Formatting the time column with formatDate also doesn't work since it is not a date or POSIXct object. I can print the desired format by typecasting it as a string, but then the sorting of the column doesn't work as it is sorted alphabetically:
##### This prints the period format, but sorting does not work
table <- data.frame(name = names, time = as.character(timevec))
my_table <- datatable(table)
and of course I could just print the total time in seconds, but as I said I find this very unintuitive to read:
##### This prints the seconds -> unintuitive to read
table <- data.frame(name = names, time = as.duration(timevec))
my_table <- datatable(table)
Any Ideas on how to achieve this or alternative suggestions how to intuitively display duration data?
solution by programming DT to sort a shown character column by a hidden numeric column via columnDefs
library(tidyverse)
library(lubridate)
library(DT)
names <- c("A", "B", "C", "D", "E", "F")
timevec_raw <- c(225, 2250, 22500, 225000, 2250000, 22500000)
timevec_period <- seconds_to_period(timevec_raw)
(table <- tibble(
name = names,
timenum = timevec_raw,
timechar = as.character(timevec_period)
)
)
my_table <- datatable(table,
options = list(
columnDefs = list(
list(
visible = FALSE, targets = 2
), # hide column 2 the numeric one
list(
orderData = c(2), # the ordering of column 3 comes from hidden column 2
targets = c(3)
)
)
)
)
I'm trying to use a custom formatter function to format grand summary rows in gt table.
in the example below I was trying to use seconds_to_period from lubridate but I get
the error "**Error in stop_if_not_gt(data = data) : **
require(tidyverse)
require(lubridate)
sp500 %>%
dplyr::filter(
date >= "2015-01-05" &
date <="2015-01-16"
) %>%
dplyr::arrange(date) %>%
dplyr::mutate(
week = paste0(
"W", strftime(date, format = "%V"))
) %>%
dplyr::select(-adj_close, -volume) %>%
gt(
rowname_col = "date",
groupname_col = "week"
) %>%
grand_summary_rows(
columns = vars(open, high, low, close),
fns = list(
min = ~min(.),
max = ~max(.),
avg = ~mean(.)),
formatter = fmt(fns=seconds_to_period),
use_seps = FALSE
)
I've tried some variations like formatter = fmt(columns=vars(min),fns=seconds_to_period) with no sucess.
Thanks
Since you didn't share the seconds_to_period function, my guess is you are trying a transformation/computation with a format function. As far as I know, that's not possible. formatter arg allows you to apply a format to an already computed summary cell. And the sintaxys to pass the fmt* arguments inside grand_summary_rows is quite different. Instead of passing them inside parenthesis fmt* function, you should pass them as grand_summary_rows arguments:
df |>
gt()|>
grand_summary_rows(
columns = vars(open, high, low, close),
fns = list(
min = ~min(.),
max = ~max(.),
avg = ~mean(.)),
formatter = fmt_number,
decimals = 1,
use_seps = FALSE
)
In any case, in your code you're passing use_steps, which is a fmt_number argument, to a fmt function, which does not admit it. Take a look at fmt docummentation.
Anyway, it's not clear what you a are trying to accomplish. OHLC are prices data. And I guess from your function name (seconds_to_period) that you're trying to give this prices data a time class format. If the case, you should compute/transform the content before trying to format it.
I am trying to get the date as Jan 20 to June 20 in the month column of rpivottable. but it's always showing in yyyy-mm-dd format e.g. 2020-01-01. My code as below:
library(readxl)
library(rpivotTable)
myexcel <- read_excel("claimH1data_date.xlsx")
x <- myexcel$Month
as.Date(x, format, tryFormats = c("%m-%Y"),tz = "UTC",
optional = TRUE)
format(x, format="%B %Y")
View(x)
rpivotTable(myexcel, rows = "Month",cols="Action", vals = "Freq",
aggregatorName = "Count", rendererName = "Table")
Can you please help? Thanks.
You can try :
library(readxl)
#Read the data
myexcel <- read_excel("claimH1data_date.xlsx")
#Sort the data based on date
myexcel <- myexcel[order(myexcel$Month), ]
#Apply the format
myexcel$Month <- format(myexcel$Month, format="%B %Y")
myexcel
library(DT)
seq_dates <- data.frame(dates = as.Date("2017-01-01") + 1:6 * 100)
datatable(seq_dates) %>% formatDate(1, "toDateString")
I get a datatable in viewer pane displaying dates in following format "Mon May 22 2017".
Q - How can I format date column as "MM-YY"
If I do,
dplyr::mutate(seq_dates, dates = format(dates, format = "%b-%Y")) %>%
datatable()
I get the required date format, but in this second case column sorting doesn't work (sorting is done on alphabets rather than dates.)
P.S - I'm implementing this on shiny.
Hi in these cases do I think the best solution is to add a dummy column with the dates in orginal format and have the dates column being sorted according to the values in the DUMMY column. This is in Datatable quite easily done. Example code below.
seq_dates <- data.frame(dates = as.Date("2017-01-01") + 1:6 * 100)
datatable(seq_dates %>% mutate(DUMMY = dates,dates = format(dates, format = "%b-%Y")),
options = list(
columnDefs = list(
list(targets = 1,orderData = 2),
list(targets = 2, visible = FALSE)
)
))
For what it's worth (and using formatDate), the best that I can do is as follows:
datatable(seq_dates) %>%
formatDate(
columns = 1,
method = "toLocaleDateString",
params = list(
'en-US',
list(
year = 'numeric',
month = 'numeric')
)
)
And this yields date values like 4/2017 and 10/2017.
I've tried to find these parameter options (in github and the original datatables documentation) but to no avail. The only example in DT uses the parameters of short, long and numeric.
Converting "%b-%y" "dates" to date format is not an easy thing as I could see...
If you're not too attached to displaying "%b-%y" format, the easy way is to use "%Y-%m" or "%y-%m" format and the filter will work just fine :
library(DT)
seq_dates <- as.data.frame(seq(Sys.Date() - 100, Sys.Date(), by = "m"))
seq_dates <- format(seq_dates, format = "%y-%m")
datatable(seq_dates)
#resulting in
#1 2017-02
#2 2017-03
#3 2017-04
#4 2017-05
#or
#1 17-02
#2 17-03
#3 17-04
#4 17-05
There is a render method that you can use:
datatable( ...
options = list(..
columnDefs = list(..
list(targets = c(1), render = JS(
"function(data, type, row, meta) {",
"return type === 'display' ? new Date(data).toLocaleString() : data;"))))