Question

QUESTION

Can someone help walk me through the general approach to solving this problem?

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I’m trying to replicate a Train Diagram like this one (full size) using some train movement data of my own.

The graph looks to consist of…

1. Horizontal Axis: Time
2. Vertical Axis: Location
3. Lines: Delineate the path of individual trains
4. Colours: Not shown in the B&W image, but trains should be coloured separately

And my data looks like this…

Thanks for the help 🙂

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Sample can be reproduced like so…

dat <- structure(list(id = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L), .Label = c("2011U0024", "2011U0025", 
"2011U0026", "2011U0035", "2011U0039", "2011U0040", "2011U0041", 
"2011U0046", "2011U0047", "2011U0049"), class = "factor"), location = structure(c(1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L), .Label = c("a", 
"b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n"
), class = "factor"), time = structure(c(1294079880, 1294093080, 
1294094880, 1294100400, 1294102380, 1294124100, 1294125240, 1294126920, 
1294129020, 1294140120, 1294140900, 1294143960, 1294145100, 1294146600, 
1294086240, 1294100400, 1294105440, 1294111560, 1294114740, 1294137180, 
1294138380, 1294140120, 1294141320, 1294152420, 1294158000, 1294158900, 
1294160100, 1294162200, 1294100700, 1294113180, 1294115220, 1294120980, 
1294134780, 1294153920, 1294155060, 1294156680, 1294158480, 1294169460, 
1294170420, 1294171020, 1294171200, 1294173900, 1294290660, 1294307040, 
1294308720, 1294313880, 1294315860, 1294342200, 1294344600, 1294345080, 
1294347180, 1294358400, 1294360200, 1294360440, 1294360800, 1294364100, 
1294348860, 1294361400, 1294363500, 1294369560, 1294379160, 1294405080, 
1294407240, 1294407900, 1294409940, 1294421040, 1294421400, 1294421880, 
1294423200, 1294425240, 1294364100, 1294378200, 1294380180, 1294385700, 
1294388220, 1294414500, 1294416600, 1294421040, 1294422720, 1294434720, 
1294435500, 1294435920, 1294436400, 1294438920, 1294384440, 1294399440, 
1294401120, 1294406520, 1294408800, 1294429560, 1294431960, 1294434720, 
1294435980, 1294448160, 1294448340, 1294449360, 1294451400, 1294453500, 
1294468860, 1294502640, 1294504020, 1294509360, 1294514520, 1294537980, 
1294541400, 1294543920, 1294544640, 1294555860, 1294556520, 1294557120, 
1294558200, 1294564860, 1294501680, 1294513560, 1294515300, 1294521120, 
1294523820, 1294545960, 1294548780, 1294556820, 1294557420, 1294571580, 
1294572000, 1294572420, 1294575600, 1294579500, 1294549080, 1294562460, 
1294566300, 1294572180, 1294575420, 1294602180, 1294604520, 1294605300, 
1294606020, 1294617060, 1294620540, 1294620720, 1294624800, 1294630080
), class = c("POSIXct", "POSIXt"), tzone = "")), .Names = c("id", 
"location", "time"), row.names = c(NA, -140L), class = "data.frame")

Answer 1

It is rather straight-forward in ggplot. A single line of code suffices:

ggplot(dat, aes(x=time, y=location, colour=id, group=id)) + geom_line()