Table of Contents
Creating a time series in R involves using the ts() function to create a time series object from a vector of values. You can specify the starting and ending points of the time series, as well as the frequency, and then you can plot the time series using the plot() function. Additionally, you can use the decompose() function to decompose the time series into its seasonal, trend, and random components.
The easiest way to create a time series object in R is to use the ts() function.
This function uses the following basic syntax:
ts(data, start, end, frequency)
where:
- data: A vector or matrix of time series values
- start: The time of the first observation
- end: The time of the last observation
- frequency: The number of observations per unit of time.
The following examples show how to use this function to create different time series objects in practice.
Example 1: Create Time Series with Monthly Data
Suppose we have the following vector called data that contains the number of sales made by some retail store during 20 consecutive months, starting on October 1st, 2023:
#create vector of 20 values
data <- c(6, 7, 7, 7, 8, 5, 8, 9, 4, 9, 12, 14, 14, 15, 18, 24, 20, 15, 24, 26)
We can use the ts() function and specify frequency=12 to create a time series object from this vector:
#create time series object from vector ts_data <- ts(data, start=c(2023, 10), frequency=12) #view time series object ts_data Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2023 6 7 7 2024 7 8 5 8 9 4 9 12 14 14 15 18 2025 24 20 15 24 26
Notice that the vector of values has been converted to a time series object where the values are now associated with a month from October 2023 to May 2025.
We can also use the class() function to confirm that ts_data is indeed a time series object:
#display class of ts_data object
class(ts_data)
[1] "ts"
Example 2: Create Time Series with Yearly Data
Suppose we have the following vector called data that contains the number of sales made by some retail store during 20 consecutive years, starting in 2000:
#create vector of 20 values
data <- c(6, 7, 7, 7, 8, 5, 8, 9, 4, 9, 12, 14, 14, 15, 18, 24, 20, 15, 24, 26)
#create time series object from vector ts_data <- ts(data, start=2023, frequency=1) #view time series object Time Series: Start = 2000 End = 2019 Frequency = 1 [1] 6 7 7 7 8 5 8 9 4 9 12 14 14 15 18 24 20 15 24 26
Notice that the vector of values has been converted to a time series object where the values are now associated with a year from 2000 to 2019.
We can also use the class() function to confirm that ts_data is indeed a time series object:
#display class of ts_data object
class(ts_data)
[1] "ts"
If we’d like, we can also use the plot() function to visualize the sales by year:
#create line plot of time series data
plot(ts_data)
Notice that the x-axis displays the year and the y-axis displays the sales values.
We can also customize the plot to make it easier to read:
#create line plot with custom x-axis, y-axis, title, line color and line width plot(ts_data, xlab='Year', ylab='Sales', main='Sales by Year', col='blue', lwd=3)
Feel free to modify the arguments in the plot() function to create the exact time series plot you’d like.
The following tutorials explain how to perform other common tasks in R: