Product_Code Date Order_Demand
Product_1904 09-01-2017 4000
Product_0250 09-01-2017 148
Product_0471 09-01-2017 30
Product_1408 06-01-2017 1000
Product_0689 06-01-2017 200
Product_0689 06-01-2017 300
Product_1926 06-01-2017 2
Product_1938 06-01-2017 20
I am new to R. I want to convert the above data to a time series object ts, such that the rownames will be Product_Code and column names will be months or quarters. Kindly help me!!
I think this should work for you,
library(xts)
library(lubridate)
# dummmy data
test_data <- data.frame(
Product_Code = c("Product_1904","Product_0250","Product_0471"),
Date = mdy(c("09-01-2017","09-02-2017","09-03-2017")),
Order_Demand = c(4000,148,30)
)
# convert dummy data into xts time series
xts::xts(test_data, order.by = test_data$Date) -> time_series_data
str(time_series_data)
An ‘xts’ object on 2017-09-01/2017-09-03 containing:
Data: chr [1:3, 1:3] "Product_1904" "Product_0250" "Product_0471" "2017-09-01" "2017-09-02" "2017-09-03" "4000" ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr [1:3] "Product_Code" "Date" "Order_Demand"
Indexed by objects of class: [Date] TZ: UTC
xts Attributes:
NULL
From next time please use dput() and copy paste the result from the R terminal to provide the data.