Question

I have data in a .csv file showing enquiries received by different teams on different dates. Enquiries are entered as follows:

Team,Date_received,Date_answered
Team 1,31/01/10,05/02/10
Team 3,05/03/10,17/04/10
...

I want to plot a graph showing how many enquiries each team received over each of the last six months but I’m new to R and getting nowhere fast. I’ve looked up time series documentation (in O’Reilly’s R in a Nutshell) but it seems to be much more complex than what I need.

So far I’ve read in the data and converted the date strings into POSIXlt as follows:

c_data <- read.table("~/data.csv", header=T, sep=",")
c_data$Date_received <- as.Date(c_data$Date_received, "%d/%m/%y")
c_data <- as.POSIXlt(c_data$Date_received)
...

but from there I’m lost. What I want to do is extract the month from the POSIXlt field, count the incidence of each ‘Team’ string in each month and plot them against each other, but I don’t know which functions handle those things and I’m struggling with the docs.

I know I’m at early stages here so even just a pointer to the function I should be reading about would be appreciated.

Answer 1

Starting with some dummy data:

c_data <- data.frame(Team=paste("team", sample(1:3,10, replace=TRUE)), 
                    Date_received=paste(sample(1:31,10,replace=TRUE), sample(1:12,10,replace=TRUE), rep(10,10,replace=TRUE), sep="/"))
c_data
    Team Date_received
1  team 3       13/7/10
2  team 1        2/5/10
3  team 2       14/5/10
4  team 1       15/4/10
5  team 1       25/1/10
6  team 3       30/4/10
7  team 3       23/9/10
8  team 3        7/9/10
9  team 2        7/6/10
10 team 2        4/6/10

First you have to declare your dates as Date objects.

c_data$Date_received <- as.Date(c_data$Date_received, "%d/%m/%y")

To extract the month, nothing simpler:

c_data$month <- format(c_data$Date_received, "%m")
c_data$month
[1] "07" "05" "05" "04" "01" "04" "09" "09" "06" "06"

And then, to find the incidence of each team per month, you just have to tabulate according to your teams and months:

t_data <- table(c_data$Team, c_data$month)
t_data

         01 04 05 06 07 09
  team 1  1  1  1  0  0  0
  team 2  0  0  1  2  0  0
  team 3  0  1  0  0  1  2

And now as a data.frame (for plotting purposes):

d_data <- as.data.frame(t_data)
d_data
     Var1 Var2 Freq
1  team 1   01    1
2  team 2   01    0
3  team 3   01    0
4  team 1   04    1
5  team 2   04    0
6  team 3   04    1
7  team 1   05    1
8  team 2   05    1
9  team 3   05    0
10 team 1   06    0
11 team 2   06    2
12 team 3   06    0
13 team 1   07    0
14 team 2   07    0
15 team 3   07    1
16 team 1   09    0
17 team 2   09    0
18 team 3   09    2

# Back to Date objects
d_data$Var2 <- as.Date(paste("1",d_data$Var2,"10",sep="/"), "%d/%m/%y") 

library(ggplot2)
ggplot(d_data, aes(Var2, Freq, group = Var1, color = Var1)) +
geom_line()