R- Conversion to TS - r

Question

I am new to R and I am currently struggling to convert a set of data into TS format.
Call_VolumeTS10 <- ts(Forecast_Data_Test$`Call Volume`, frequency = 578, start = c(2019, 1,1), end=c(2020, 7, 31))
However, the code does not properly convert data into a daily time series.
Is it a problem with my code?

Answer 1

As pointed out by #AlexB, the value for frequency is certainly oddly defined. However, the error you're having it's also related to how you defined start and end.
You cannot define start and end with a numeric vector of length 3. It must be a vector of length 2: the first number should be the year (or, generically speaking, the number of seasons that have passed) and the second number should be a number between 1 and the value of the frequency.
To properly write your ts, you should use this code:
Call_VolumeTS10 <- ts(Forecast_Data_Test$`Call Volume`, frequency = 365.25, start = c(2019, 1))
Start, end and frequency will be defined as follow:
your_data <- rnorm(578)
your_ts <- ts(your_data, start = c(2019, 1), frequency = 365.25)
tsp(your_ts)
#> [1] 2019.00 2020.58 365.25
## respectively: start end frequency
However, I suppose you want to define a ts to forecast it.
The problem is that a frequency of 365.25 is rarely handled correctly by forecasting methods (for example forecast::auto.arima or forecast::ets).
Probably you may need to use frequency = 7. Of course, in that case, the value for end in the time series definition will make no sense.
your_data <- rnorm(578)
your_ts <- ts(your_data, start = c(2019, 1), frequency = 7)
tsp(your_ts)
#> [1] 2019.000 2101.429 7.000
## respectively: start end frequency
Obviously, it has no meaning. So it would just make more sense to define it this way:
your_data <- rnorm(578)
your_ts <- ts(your_data, frequency = 7)
tsp(your_ts)
#> [1] 1.00000 83.42857 7.00000
## respectively: start end frequency
In this case, you can interpret the difference between 1.000 and 83.428 as if 82 weeks has passed since the beginning of the time series (plus a couple of days).
Alternatively, you can use the msts function from the forecast package that allows you to define multiple frequencies.
library(forecast)
msts(your_ts, start = c(2019, 1), seasonal.periods = c(7, 365.25))
your_ts
#> Multi-Seasonal Time Series:
#> Start: 2019 1
#> Seasonal Periods: 7 365.25
#> Data:
#> ...
That msts object is well-integrated with forecast::fourier and forecast::tbats.
I suggest you to have a look at this for some ideas about it.
About how to write start in a proper way...
"2019-01-01" is a pretty convenient day, because the right value for start will be c(2019, 1). However, if you find yourself with the need to write a different start date, I suggest you to use this code to define the start time:
start = c(lubridate::year(date), as.numeric(format(date, "%j")))
Where date is any date in the format yyyy-mm-dd.