transforming data into time series - r

Question

I have a csv data set that I would like t transform into time series data for time series analysis.
The data looks like that (there are additional columns, and there are 17,190 obs.):
temp interval
10.0 2014-04-01 00:00:00
10.0 2014-04-01 00:15:00
10.0 2014-04-01 00:30:00
10.0 2014-04-01 00:45:00
7.8 2014-04-01 01:00:00
The Interval column is in POSIXct format.
I would appreciate help with the code for transforming it into time series please.
Thank you

Answer 1

CSV stands for comma separated values. The data shown in the question is not in that form but if we assume that the data is a data frame DF shown reproducibly in the Note at the end then the following code gives a zoo series z and also converts it to a ts series tt where the times are the number of seconds since 1970-01-01 00:00:00. See ?read.zoo for more information on that function. Also the zoo package contains an entire vignette with many read.zoo examples.
z can be used for plotting and tt might be useful if you are using functions that only accept ts class input.
library(zoo)
z <- read.zoo(DF, index = "interval", tz = "")
tt <- as.ts(z)
Note
Lines <- "
temp interval
10.0 2014-04-01 00:00:00
10.0 2014-04-01 00:15:00
10.0 2014-04-01 00:30:00
10.0 2014-04-01 00:45:00
7.8 2014-04-01 01:00:00"
# read into separate lines, trim whitespace from ends and
# replace 2 or more consecutive spaces with comma
L <- gsub(" +", ",", trimws(readLines(textConnection(Lines))))
DF <- read.csv(text = L)

Answer 2

If you read in the csv with read_csv in tidyverse you'll get the interval column in POSIXct class automatically.
dput below:
library(tidyverse)
df <- structure(list(temp = c(10, 10, 10, 10, 7.8), interval = structure(c(1396310400,
1396311300, 1396312200, 1396313100, 1396314000), class = c("POSIXct",
"POSIXt"), tzone = "UTC")), class = c("spec_tbl_df", "tbl_df",
"tbl", "data.frame"), row.names = c(NA, -5L), spec = structure(list(
cols = list(temp = structure(list(), class = c("collector_double",
"collector")), interval = structure(list(format = ""), class = c("collector_datetime",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector")), skip = 1), class = "col_spec"))
you can then just reorder cols and convert to zoo.
library(zoo)
df <- df %>%
select(interval, temp) %>%
zoo()
class(df)
[1] "zoo"