Manipulating data with dates
0 likes50 views
The document discusses methods for manipulating dates in R using various functions such as as.date(), difftime(), and lubridate(). It covers converting date formats, calculating time differences, and extracting components like months and weekdays. Additionally, it explains the use of posixlt and posixct for date-time handling and provides examples of data filtering and merging.
![#once the data is in date format we can easily extract the months and the
weeks.
>months(datedata$Date.received)
>weekdays(datedata$Date.received)
#even we can filter the data using months() and weekdays()
#sub-setting using base R package
>datadate2<-datedata[(weekdays(datedata$Date.received)=="Sunday"),]
as.Date()
Rupak Roy](https://image.slidesharecdn.com/10-220113085311/85/Manipulating-data-with-dates-3-320.jpg)
Manipulating data with dates
- 1. Manipulating Dates Using as.Date, difftime(), as.POSIXct(), as.POSIXlt(), lubridate() Rupak Roy
- 2. #load the data >datedata<-read.csv(file.choose(),header = TRUE) >str(datedata) #using as.Date(): A factor or a character data type can be easily converted into a date format where as.Date(column_name, orginal_date_format_of the dataset) >datedata$Date.received<-as.Date(datedata$Date.received,"%m/%d/%Y") >datedata$Date.sent.to.company<- as.Date(datedata$Date.sent.to.company,"%m/%d/%Y") >str(datedata) #code for identify different combinations of date format #example: 15/aug/2016:“ %d/%b/%Y ” 13-JUNE-16: “ %d-%B-%y ” as.Date() %d Day of the month %m Month (in decimal) %Y Year (4 digits) %b Month (abbreviated) %y Year (2 digits) %B Month (full name)
- 3. #once the data is in date format we can easily extract the months and the weeks. >months(datedata$Date.received) >weekdays(datedata$Date.received) #even we can filter the data using months() and weekdays() #sub-setting using base R package >datadate2<-datedata[(weekdays(datedata$Date.received)=="Sunday"),] as.Date() Rupak Roy
- 4. #using difftime() function we can calculate the time interval / differences without being converted into minutes, hour, weeks, months or years. >difftime(time2, time1, tz, units = c("auto", "secs", "mins", "hours", "days", "weeks")) Where tz= an optional time zone specification to be used for the conversion units= Units in which the results are desired. >difftime(datedata$Date.received,datedata$Date.sent.to.company,units = "days") #this will give the output in a negative value because we are doing time1-time2 rather than time2-time1 i.e 5- 10 = -5 rather than 10-5 =5 #therefore >difftime(datedata$Date.sent.to.company,datedata$Date.received,units = "days") To know more about the difftime() function use >?difftime difftime()
- 5. These are date-time conversion functions to manipulate data or the objects of classes "POSIXlt" and "POSIXct" having time information along with the date. POSIXct is similar to POSIXlt the only difference is POSIXlt stores the data in a list format #saving the current date-time information as an example >datetime<-Sys.time() >class(datetime) >weekdays(datetime) >months(datetime) #convert the date and time into POSIXlt() >datetime<-as.POSIXlt(datetime) >datetime$zone >datetime$hour >datetime$wday as.POSIXct() and as.POSIXlt() Rupak Roy
- 6. Lubridate() is an another function that makes it easier to parse and manipulate dates. #install and load the package >install.packages(lubridate) >library(lubridate) >datedata<-read.csv(file.choose(),header = TRUE) >str(datedata) #converting the factor data type into date data type >datedata$Date.received<-mdy(datedata$Date.received) >str(datedata) Where, mdy = lubridate() Code Format dmy() 3/10/2017 mdy() 10/3/2017 dmy_hm() 3/10/2017 23:40 ydm() 2017/3/10 dmy_hms() mdy_hm() mdy_hms() ydm_hm()
- 7. Next: We will learn an another important function that is combining two or more data sets using merge(). Manipulating Dates Rupak Roy