Reputation: 2839
I have data in the format Date, Time, Value. Here is a sample:
04/01/2010,07:10,17159
04/01/2010,07:20,4877
04/01/2010,07:30,6078
04/01/2010,07:40,3105
04/01/2010,07:50,4073
04/01/2010,08:00,6986
04/01/2010,08:10,7906
04/01/2010,08:20,7681
04/01/2010,08:30,5665
04/01/2010,08:40,6631
04/01/2010,08:50,4633
04/01/2010,09:00,6346
04/01/2010,09:10,6444
04/01/2010,09:20,6324
04/01/2010,09:30,11696
04/01/2010,09:40,7667
04/01/2010,09:50,6375
04/01/2010,10:00,5934
04/01/2010,10:10,12626
04/01/2010,10:20,11674
04/01/2010,10:30,4660
04/01/2010,10:40,3831
04/01/2010,10:50,7089
04/01/2010,11:00,4548
04/01/2010,11:10,2590
04/01/2010,11:20,3334
04/01/2010,11:30,5171
I want to convert this to a Time Series of Value keeping the same format. i.e. I need to be able store the date and time components too. This is is because i want to "deseasonalize" the data.
I have tried
z <- read.csv("fileName", header=TRUE,sep=",")
but not sure what to do from here. Can anyone show me how to load into a time series object properly? Or is there another way to do this?
Thanks in advance
Upvotes: 6
Views: 16088
Reputation: 1143
In addition to what has been mentioned as the answer, you can check this link (http://eclr.humanities.manchester.ac.uk/index.php/R_TSplots) which discusses the use of 'xts' in this case. I hope it helps.
Upvotes: -1
Reputation: 121568
You can use the zoo
package. The code below was writen to be reproducible but in actual practice text="Lines"
would be replaced with file="fileName"
. Also as shown in the question the Date field is ambiguous and you may need to adjust the percent codes if its not day/month/year.
library(zoo)
Lines <- "Date,Time,Value
04/01/2010,07:10,17159
04/01/2010,07:20,4877
04/01/2010,07:30,6078
04/01/2010,07:40,3105
"
z <- read.zoo(text = Lines, sep = ",", header = TRUE,
index = 1:2, tz = "", format = "%d/%m/%Y %H:%M")
which gives:
> z
2010-01-04 07:10:00 2010-01-04 07:20:00 2010-01-04 07:30:00 2010-01-04 07:40:00
17159 4877 6078 3105
Upvotes: 9