Reputation: 11
I am working on a monthly-based time-series data set:
> head(data, n=10)
# A tibble: 10 x 2
Month Inflation
<dttm> <dbl>
1 1979-01-01 00:00:00 0.0258
2 1979-02-01 00:00:00 0.0234
3 1979-03-01 00:00:00 0.0055
4 1979-04-01 00:00:00 0.0302
5 1979-05-01 00:00:00 0.0305
6 1979-06-01 00:00:00 0.0232
7 1979-07-01 00:00:00 0.025
8 1979-08-01 00:00:00 0.0234
9 1979-09-01 00:00:00 0.0074
10 1979-10-01 00:00:00 0.0089
Although it appears that the data is yet to be recognized as a time-series data as it shows the following structure:
> str(data)
Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 479 obs. of 2 variables:
$ Month : POSIXct, format: "1979-01-01" "1979-02-01" "1979-03-01" "1979-04-01" ...
$ Inflation: num 0.0258 0.0234 0.0055 0.0302 0.0305 0.0232 0.025 0.0234 0.0074 0.0089 ...
When I tried to convert it using xts function, it gave me this error:
> inflation <- xts(data[,-1], order.by=as.Date(data[,1], "%m/%d/%Y"))
Error in as.Date.default(data[, 1], "%m/%d/%Y") :
do not know how to convert 'data[, 1]' to class “Date”
Please help me with the most appropriate way of data conversion. Thanks
Upvotes: 0
Views: 4971
Reputation: 497
# You have something like:
data <- data.frame(
Month = as.Date(as.Date("1979-01-01"):as.Date("2000-01-01"), origin="1970-01-01"),
Inflation = rnorm(7671)) # same number of obs
choose start and end dates appropriatelly
tseries <- ts(data$Inflation, start = c(1979,1), end = c(2000,1), frequency = 12)
plot(tseries)
Upvotes: 2