I have a dataset with 3 variables:
the first is date (example"01/01/2019" )
the second is hour (example:"01:00"), and
the third is a numeric.
I want to construct an object ts, but I don't know how I can do this.The first and second variables are characters.
I want an hour time series
Related
I am trying to decompose a time series object. I have coerced a xts object into time series
To know the structure of my time series object
sapply(ts_group1_ts, class)
store item yearmonth total_sales
"ts" "ts" "ts" "ts"
>decompose(ts_group1_ts[,'total_sales'])
Error in `-.default`(x, trend) : non-numeric argument to binary operator
I want to decompose the total sales part of my time series . Please tell how to decompose. I realise that the error is because the function is not identifying total_sales as integer. How to achieve that in time series object
On doing forced conversion to numeric I get below output:
>decompose(as.numeric(ts_group1_ts[,'total_sales']))
Error in decompose(as.numeric(ts_group1_ts[, "total_sales"])) :
time series has no or less than 2 periods
But the frequency of my time series is 12
>frequency(ts_group1_ts)
12
I have a dataset consisting of 4 variables namely date,Gold price,crude price and dollar price. I converted the class of the data to time series using ts() function. After converting, the dates got changed into some value. I am able to retrieve the dates from converted values using as.Date() function.Now I want to replace the date values by date itself in the ts object's date variable.
#CONVERTING DATA FRAME TO TIME SERIES OBJECT.
Gold.ts <- ts(Gold,start=Gold$DATE[1])
head(Gold.ts)
#OUTPUT.
DATE GOLD.PRICE CRUDE DOLLAR.INR
[1,] 13152 533.9 63.42 44.705
[2,] 13153 526.3 62.79 44.600
[3,] 13154 539.7 64.21 44.320
head(as.Date(index(Gold.ts)))
[1] "2006-01-04" "2006-01-05" "2006-01-06" "2006-01-07" "2006-01-08" "2006- 01-09"
Gold.ts$DATE <- as.Date(index(Gold.ts)) # This won't work because $ is not acceptable to extract variables from a time series object.
index(Gold.ts) <- as.Date(index(Gold.ts)) #This should work but gives error. How to display date instead of values in time series object i.e Gold.ts?
What is the right way to do it?
I have the following problem. I have a XTS containing a date column and several valuations, which should be ranked (biggest = best rank). So my original XTS is test:
> str(index(Test))
Date[1:235], format: "1995-01-31" "1995-02-28" "1995-03-31" "1995-04-28" "1995-05-31" "1995-06-30" "1995-07-31" ...
Now, my rankValuations function:
rankValuations<-function(ValuationXTS){
#Ranks the xts object asset valuations
#ValuationXTS is a xts time series with asset valuations
#Returns an xts object with ranks (asset with the greatest valuation receives 1)
#The ties parameter results in an ascending ranking. If two share the same rank, the first in the matrix gets the first rank
ranked<-as.xts(t(apply(-ValuationXTS,1,rank, ties.method="first",na.last=TRUE)))
}
After running this my index format has changed to POSIX:
> Test<-rankValuations(Test)
> str(index(Test))
POSIXct[1:235], format: "1995-01-31" "1995-02-28" "1995-03-31" "1995-04-28" "1995-05-31" "1995-06-30" "1995-07-31" ...
And this is a big problem because in the POSIX I have now a timezone. If using later on merge.xts it never matches since the POSIX dates are 1 day prior than in the to be merged with XTS which has a Date index. So how can I stop the rank method of changing Date to POSIX?
I have a data.frame with two columns. The first column contains various specific times during a day. The second column contains the animal behavior (behavior period) that I observed at each specific time:
Time; Behavior
10:20; feeding
10:25; feeding
10:30; resting
...
For each of those behavior periods I have an additional dataset (TimeSeries) which contains data about the actual animal movement (output from a movement sensor). Each TimeSeries has about 100 rows:
Time; Var1; Var2
10:20:01; 1345; 5232
10:20:02; 1423; 5271
...
Now I would like to link each TimeSeries with the behavior from the first dataset. So, that R knows that "feeding" is related to the TimeSeries of 10:20 and 10:25 and that "resting" is related to the TimeSeries of 10:30 and so on.
Afterwards I want to use this "knowledge" to calculate mean and sd from each TimeSeries. So I will have all the means and sd's from all TimeSeries for each behavior.
It is not clear whether your times are currently characters, factors, POSIXct, variables, etc. So you should first convert them (possibly in a new column) to a numeric variable, something like the number of seconds since midnight. Functions like strptime, difftime, and as.numeric may help.
Add a column to the first data frame that is just 1:nrow(firstdf). Then add a column to the second dataframe that is computed by the findInterval function:
seconddf$newcol <- findInterval( seconddf$seconds, firstdf$seconds )
Now you can merge the 2 data frames on the new columns and the finer grained times will be associated with the activity from the most recent time.
I have a dataframe containing 3 columns including minutes and hours.
I want to convert these columns (namely minutes and column) to time format. Given the data in drame:
Score Hour Min
10 10 56
23 17 01
I would like to get:
Score Time
10 10:56:00
23 17:01:00
You could use ISOdatetime to convert the numbers in the hour and min to a POSIXct object. However, a POSIXct object is only defined when it also includes a year, month and day. So depending on your needs to can do several things:
If you need a real time object which is correctly printed in graphs for example and can be used in arithmetic (addition, subtraction), you need to use ISOdatetime. ISOdatetime returns a so called POSIXct object, which is an R object which represents time. Then in ISOdatetime you just use fixed values for year, month, and day. This ofcourse only works if your dataset does not span multiple years.
If you just need a character column Time, you can convert the POSIXct output to string using strftime. By setting the format argument to "%H:%M:00". In this case however, you could also use sprintf to create the new character column without converting to POSIXct: sprintf("%s:%s:00", drame$Hour, drame$Min).
You can use paste() function to merge the two column data into a char and then use strptime() to convert to timestamp
x<-1:6
##1 2 3 4 5 6
y<-8:13
## 8 9 10 11 12 13
timestamp <- paste(x,":",y,":00",sep="")
timestamp
will result in
#1:8:00 2:9:00 3:10:00 4:11:00 5:12:00 6:13:00
If you prefer to convert this to timestamp object try using
strptime(mergedData,"%H:%M:%S")
## uses current date by default
if you happen to have Date in another column use paste() to make a char formattted date and use below to get date time
##strptime(mergedData,"%d/%m/%Y %H:%M:%S")