Loop through dataframe in R and measure time difference between two values

Question

Summary: I am analyzing the time difference between an occured stimuli (A&B) and a possible response of the user.

The dataset has the following stru

Answer 1

Here's how you can do that with dplyr. First, you need to transform your Date column to a POSIXct object. Then, make sure the Date object is ordered with arrange. You then add a time difference column using mutate. You can then filter for rows where Stimuli A or B is 1 and is followed by a Response equal to 1.

df$Date <- as.POSIXct(strptime(df$Date,"%d.%m.%Y %H:%M"))
df %>%
  arrange(User,Date)%>%
  mutate(difftime= difftime(lead(Date),Date, units = "mins") ) %>%
  group_by(User)%>%
  filter((StimuliA==1 | StimuliB==1) & lead(Responses)==1)

                                  User                Date  Hour StimuliA StimuliB Responses   difftime
                                 <chr>              <dttm> <int>    <int>    <int>     <int>     <time>
1 005b98f3-5b1b-4d10-bdea-a55d012b2844 2015-11-25 13:59:00  1645        1        0         0 11253 mins
2 005b98f3-5b1b-4d10-bdea-a55d012b2844 2015-12-07 08:18:00  1928        1        0         0  2122 mins
3 005b98f3-5b1b-4d10-bdea-a55d012b2844 2015-12-08 19:40:00  1963        0        1         0 19510 mins
4 005b98f3-5b1b-4d10-bdea-a55d012b2844 2016-01-05 11:35:00  2627        0        1         0   106 mins
5 005b98f3-5b1b-4d10-bdea-a55d012b2844 2016-01-06 09:18:00  2649        1        0         0 56969 mins

Answer 2

SQL syntax should be able to get you your answer and is the conventional method for querying tabular data like these. The Data.Table package makes this sort of syntax accessible.

#import necessary library
library(data.table)

#instantiate data table
dt<-data.table(dt)

#convert date field to Date type
dt$Date <- as.POSIXct(dt$Date, format="%d.%m.%Y %H:%M")
#create another date field so as not to lose during join
dt$rollDate<-dt$Date

#create table with stimuliA and set key for sorting/joining purposes
stima.dt <- dt[StimuliA==1,.(User,rollDate,Date,Hour,StimuliA)]
setkey(stima.dt,User,rollDate)

#Same for stimuliB
stimb.dt <- dt[StimuliB==1,.(User,rollDate,Date,Hour,StimuliB)]
setkey(stimb.dt,User,rollDate)

#same for responses table
resp.dt <- dt[Responses==1,.(User,rollDate,Date,Hour,Responses)]
setkey(resp.dt,User,rollDate)

#Join stimuli A table to closes responses
stim.a<-resp.dt[stima.dt,roll=-Inf]

#calculate Hour differences
stim.a[,difftime(Date,i.Date,units="min")]

#Join stimuli B table to closes responses
stim.b<-resp.dt[stimb.dt,roll=-Inf]

#calculate Hour differences
stim.b[,difftime(Date,i.Date,units="min")]