From: Tom
Hopper <> href="mailto:tomhop...@gmail.com";>tomhop...@gmail.com>
To: Felipe
Carrillo <> href="mailto:mazatlanmex...@yahoo.com";>mazatlanmex...@yahoo.com
>
Sent:
Tue, June 22, 2010 9:40:19 PM
Subject: Re: Plotting Data on a
Map
Felipe,
I am just learning these
tools, too, so it may be a good learning opportunity for both of
us. Please send
me the files and I will try to put it together and plot
it.
Regards,
Tom
On
Mon, Jun 21, 2010 at 11:57 PM, Felipe Carrillo <> ymailto="mailto:mazatlanmex...@yahoo.com
"
href="mailto:mazatlanmex...@yahoo.com";>mazatlanmex...@yahoo.com>
wrote:
Hi Tom:
I am just starting to use rgdal and
maptools but I have a long way to go. I went to a training
a couple
of weeks ago and the instructor showed us a csv file and a
shapefile with wolf
data from
a national park in the midwest. I am trying to put all of
the csv data and some predicted data
on a map using ggplot2 but I am
stuck with it. I am just trying to do this example because I want
to
see if I can apply this example to fish. Let me know if
interested.
Felipe D.
Carrillo
Supervisory Fishery Biologist
Department of the
Interior
US Fish & Wildlife Service
California,
USA
From: Tom
Hopper <> href="mailto:tomhop...@gmail.com";>tomhop...@gmail.com>
To:
href="mailto:ggpl...@googlegroups.com";>ggpl...@googlegroups.com
Sent:
Mon, June 21, 2010 2:27:14 PM
Subject: Re: Plotting Data on a
Map
Hadley,
Thank
you!
I doing this, I've
encountered an encountered and unexpected difference between the
graphs on my
Mac and my Windows machines. It appears that there is a default
setting
different between the two
programs.
Using the same commands
on both Mac and Windows, I found that the polygon borders are
plotted on the
Mac, but not on Windows, so on the Mac I see the country borders,
but on Windows
I do not. On the Mac, it looks like the default for geom_polygon is
something
like size = 0.01, colour = "gray50". On Windows, it's more like
colour =
alpha("gray50", 0), though in fact the visibility of polygon
borders seems to be
independent of both the size and colour
settings.
Regards,
Tom
On
Mon, Jun 21, 2010 at 3:00 AM, Hadley Wickham <> ymailto="mailto:had...@rice.edu
"
href="mailto:had...@rice.edu";>had...@rice.edu>
wrote:
Hi
Tom,
Thanks for contribution! Ploting map
data is never easy and its always
nice to see a success
story.
Hadley
On
Saturday, June 19, 2010, Tom Hopper <> href="mailto:tomhop...@gmail.com
">tomhop...@gmail.com>
wrote:
Well, it turns out that, in my haste to thank
Fernando, I posted code with some typos. I have also had a chance
to test it on
my Mac, and found that fortify() was throwing an error ("Error in
nchar(ID) :
invalid multibyte string 1"). I have added a call, currently
commented out, to
Sys.setlocale() to fix this. I have tested the code below under R
2.11.1 on both
Windows XP and Mac OS X 10.5.8, with the latest packages installed.
In fact, the
plot looks better in the Mac Quartz
window.
Sorry for the previous
errors.
# Download electricity generation data from
http://tonto.eia.doe.gov/cfapps/ipdbproject/iedindex3.cfm?tid=2&pid=2&aid=12&cid=&syid=2004&eyid=2008&unit=BKWH
# Download new map data from
http://thematicmapping.org/downloads/world_borders.php
# Bring the thematicmapping data into R
library("rgdal")
world.map <- readOGR(dsn="C:/",
layer="TM_WORLD_BORDERS-0.3")
# Save the map data as an R object
save(world.map,
"worldmap.rdata")
# As needed, reload the data
library(maptools)
gpclibPermit()
load("worldmap.rdata")
# Prepare the world.map data for ggplot2
library(ggplot2)
# On some setups, fortify throws "Error
in nchar(ID)"
# in that case, use
setlocale
# Sys.setlocale("LC_ALL", locale =
"C")
world.ggmap <- fortify(world.map, region =
"NAME")
# Load the electricity generation data and clean it up to match with
world.ggmape
elect.gen.tot <-
read
.csv
("Total_Electricity_Net_Generation_(Billion_Kilowatthours).csv",
sep =
",", dec =
".")
names(elect.gen.tot) <- c("id", "y2004", "y2005", "y2006", "y2007",
"y2008")
# make sure the id column is in the same case for both
sets
elect.gen.tot$id <-
tolower(elect.gen.tot$id)
world.ggmap$id <-
tolower(world.ggmap$id)
# merge the two data sets
world.ggmape <-
merge(world.ggmap, elect.gen.tot, by = "id", all =
TRUE)
world.ggmape <- world.ggmape[order(world.ggmape$order),
]
# NOTE: at this point, the electricity data country names do not
match
100%
# with the thematicmapping country names (column
"id").
# print out the country names
using
# table(world.ggmape$id)
#
and do a search for values of 1. Then find the corresponding
country
# name with values > 1 and rename the country
names in the electricity
# generation data to match
(e.g. "Tanzania" becomes "united republic of
#
tanzania").
# Once this data cleaning operation is
complete, repeat the above steps
# starting with reading
data into
elect.gen.tot.
# Plot the data using ggplot2
world.plot <-
ggplot(data = world.ggmape, aes(x = long, y = lat, group =
group))
world.plot + geom_polygon(aes(fill = y2007)) + labs(x =
"Longitude", y =
"Latitude", fill = "TWh") + opts(title = "Net Electricity
Generation in TWh for
2007\nData from EIA International Energy Statistics,
2008")
On Fri, Jun 18, 2010 at 11:39 AM, Tom Hopper <> ymailto="mailto:tomhop...@gmail.com
"
href="mailto:tomhop...@gmail.com";>tomhop...@gmail.com>
wrote:
Fernando,
That worked perfectly;
thank you!
There were some
mismatches in the country names, as you noted, but after cleaning
up the
electricity generation data everything looks great. I've updated
the electricity
generation data with the cleaned version and posted a graph to >
target="_blank" href="http://box.net";>box.net.
the
graph:
http://www.box.net/tomhopper/1/22918943/452739712
Below, for reference, is the complete R
code.
Thank you, and best
regards,
Tom
# Download electricity
generation data from > href="http://tonto.eia.doe.gov/cfapps/ipdbproject/iedindex3.cfm?tid=2&pid=2&aid=12&cid=&syid=2004&eyid=2008&unit=BKWH
"
target=_blank
http://tonto.eia.doe.gov/cfapps/ipdbproject/iedindex3.cfm?tid=2&pid=2&aid=12&cid=&syid=2004&eyid=2008&unit=BKWH
# Download new map data from > href="http://thematicmapping.org/downloads/world_borders.php
" target=_blank
http://thematicmapping.org/downloads/world_borders.php
# Bring the thematicmapping data into R
library(maptools)
gpclibPermit()
library("rgdal")
world.map <- readOGR(dsn="C:/",
layer="TM_WORLD_BORDERS-0.3")
#
Save the map data as an R object for later use
save(world.map,
"worldmap.rdata")
# As needed,
reload the data
#
load("worldmap.rdata")
# Prepare
the world.map data for ggplot2
library(ggplot2)
world.ggmap <- fortify(world.map,
region = "NAME")
# Load the
electricity generation data and clean it up to match with
world.ggmape
elect.gen.tot <-
read
.csv("Total_Electricity_Net_Generation_(Billion_Kilowatthours).csv",
sep = ",", dec = ".")
names(elect) <- c("id",
"y2004", "y2005", "y2006", "y2007",
"y2008")
elect.gen.tot$id <-
tolower(elect.gen.tot$id)
#
merge the two data sets
world.ggmape <-
merge(world.ggmap, elect.gen.tot, by = "id", all = TRUE)
world.ggmape <- world.ggmape[order(world.ggmape$order),
]
# NOTE: at this point, the
electricity data country names may not match 100%
# with
the thematicmapping country names (column "id").
# print
out the country names using
#
table(world.ggmape$id)
# and do a search for values of
1. Then find the corresponding country
# name with
values > 1 and rename the country names in the
electricity
# generation data to match (e.g. "Tanzania"
becomes "United Republic of
#
Tanzania").
# Once this data cleaning operation is
complete, repeat the above steps
# starting with reading
data into elect.gen.tot.
# Plot
the data using ggplot2
world.plot <- ggplot(data =
world, aes(x = long, y = lat, group = group))
world.plot
+ geom_polygon(aes(fill = y2007)) +
labs(x =
"Longitude", y = "Latitude", fill = "TWh") +
opts(title = "Net Electricity Generation in TWh for 2007\nData from
EIA
International Energy Statistics,
2008")
On Fri, Jun 18, 2010 at 2:10 AM, fernando <> ymailto="mailto:fgtabo...@gmail.com
"
href="mailto:fgtabo...@gmail.com";>fgtabo...@gmail.com>
wrote:
Hi
Tom,
I think fortify can help you in translating the sp object to
a
data.frame. Then you can use merge to join the two
tables. The code bellow
illustrates this, although I
think there are some problems in matching country
names.
Another issue is that if you add coord_map(), something strange
happens
with Antarctica (maybe a problem in shapefile
order?).
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