Convert DataFrame with Date Column to Time Series Object in R
In this article, we will discuss how to convert dataframe with date column to time series object in the R programming language.
Time series object are a series of data points in which each data point is associated with a timestamp. For example, is a price of a stock in the stock market at different points of time. The data for the time series is stored in an R object called time-series object. These are also called as xts / zoo Object.
To convert the given dataframe with the date column to the time series object, the user first needs to import and load the xts package.
Syntax:
install.packages(“xts”)
library(“xts”)
The user then needs to call the xts() function with the required parameters the main need to call this function is to create the time-series object in R language and at the end use is.xts() function we will be conforming to the time-series object created by xts() function in R language.
xts() function is basically used as the constructor for creating an extensible time-series object.
Syntax:
xts(x = NULL, order.by = index(x), frequency = NULL, unique = TRUE, tzone = Sys.getenv(“TZ”), …)
Parameters:
- x:-an object containing the time series data
- order.by:-a corresponding vector of unique times/dates – must be of a known time-based class.
- frequency:-numeric indicating the frequency of order.
- unique:-should index be checked for unique time-stamps?
- tzone:-time zone of series. This is ignored for Date indices
- …:-additional attributes to be added.
Example:
R
library ( "xts" ) gfg_date <- data.frame (date = c ( "2004-05-07" , "2005-10-12" , "2011-11-11" , "2020-11-11" , "2021-12-11" ),val= c (1,2,3,4,5)) gfg_date$date<- as.Date (gfg_date$date) gfg_ts <- xts (gfg_date$val, gfg_date$date) gfg_ts is.xts (gfg_ts) |
Output: