[R] Plot by FIPS Code using Shapefiles

[Anthony Damico]

so check the unique number of fips codes in the objects before and after

> merged_data <- merge(shapes_fips,max_change,by="FIPS",all.X=T, all.y=T)

also note that all.X should be all.x and you might want to use FALSE for
one or both of those



On Tue, May 5, 2015 at 11:40 AM, Shouro Dasgupta <shouro at gmail.com> wrote:

> Hello,
>
> Thank you for your reply. My original data has 3109 FIPS codes. Is there a
> way to merge only this data into the shapefiles? I hope I am clear.
>
> Thank you also for the link, I am trying to do something like this:
> https://gist.github.com/reubano/1281134.
>
> Thanks again!
>
> Sincerely,
>
> Shouro
>
> On Tue, May 5, 2015 at 5:21 PM, Anthony Damico <ajdamico at gmail.com> wrote:
>
>> hi, after running each individual line of code above, check that the
>> object still has the expected number of records and unique county fips
>> codes.  it looks like length( shapes$GEOID ) == 3233 but nrow( merged_data
>> ) == 3109.  the way for you to debug this is for you to go through line by
>> line after creating each new object  :)
>>
>> i'm also not sure it's safe to work with gis objects as you're doing,
>> there are some well-documented examples of working with tiger files here
>> https://github.com/davidbrae/swmap
>>
>>
>>
>> On Tue, May 5, 2015 at 11:00 AM, Shouro Dasgupta <shouro at gmail.com>
>> wrote:
>>
>>> I am trying to plot data by FIPS code using county shapes files.
>>>
>>> library(data.table)
>>> > library(rgdal)
>>> > library(colourschemes)
>>> > library(RColorBrewer)
>>> > library(maptools)
>>> > library(maps)
>>> > library(ggmap)
>>>
>>>
>>> I have data by FIPS code which looks like this:
>>> >
>>> >
>>> > dput(head(max_change))
>>> > structure(list(FIPS = c("01001", "01003", "01005", "01007", "01009",
>>> > "01011"), pred_hist = c(5.68493780563595e-06, 5.87686839563543e-06,
>>> > 5.68493780563595e-06, 5.84476370329784e-06, 5.89156133294344e-06,
>>> > 5.68493780563595e-06), pred_sim = c(5.60128903156804e-06,
>>> > 5.82369276823497e-06,
>>> > 5.60128903156804e-06, 5.75205304048323e-06, 5.80322399836766e-06,
>>> > 5.60128903156804e-06), change = c(-1.47141054005866,
>>> -0.904829303986895,
>>> > -1.47141054005866, -1.58621746782168, -1.49938750670105,
>>> -1.47141054005866
>>> > )), .Names = c("FIPS", "pred_hist", "pred_sim", "change"), class =
>>> > c("data.table",
>>> > "data.frame"), row.names = c(NA, -6L), .internal.selfref = <pointer:
>>> > 0x0000000000110788>)
>>>
>>>
>>>  I add leading zeroes by:
>>>
>>> max_change <- as.data.table(max_change)
>>> max_change$FIPS <- sprintf("%05d",as.numeric(max_change$FIPS))
>>>
>>> I downloaded shapefiles from here:
>>> ftp://ftp2.census.gov/geo/tiger/TIGER2014/COUNTY/.
>>>
>>> I obtain the FIPS codes from the shapefiles and order them using:
>>>
>>> shapes_fips <- shapes$GEOID
>>> > shapes_fips <- as.data.table(shapes_fips)
>>> > setnames(shapes_fips, "shapes_fips", "FIPS")
>>> > shapes_fips <- shapes_fips[with(shapes_fips, order(FIPS)), ]
>>> > shapes_fips$FIPS <- as.character(shapes_fips$FIPS)
>>>
>>>
>>> Then I merge the FIPS codes with my original dataset using:
>>>
>>> >
>>> > merged_data <- merge(shapes_fips,max_change,by="FIPS",all.X=T, all.y=T)
>>> > merged_data <- as.data.table(merged_data)
>>>
>>>
>>> Which looks like this:
>>>
>>> structure(list(FIPS = c("01001", "01003", "01005", "01007", "01009",
>>> > "01011"), pred_hist = c(5.68493780563595e-06, 5.87686839563543e-06,
>>> > 5.68493780563595e-06, 5.84476370329784e-06, 5.89156133294344e-06,
>>> > 5.68493780563595e-06), pred_sim = c(5.60128903156804e-06,
>>> > 5.82369276823497e-06,
>>> > 5.60128903156804e-06, 5.75205304048323e-06, 5.80322399836766e-06,
>>> > 5.60128903156804e-06), change = c(-1.47141054005866,
>>> -0.904829303986895,
>>> > -1.47141054005866, -1.58621746782168, -1.49938750670105,
>>> -1.47141054005866
>>> > )), .Names = c("FIPS", "pred_hist", "pred_sim", "change"), sorted =
>>> > "FIPS", class = c("data.table",
>>> > "data.frame"), row.names = c(NA, -6L), .internal.selfref = <pointer:
>>> > 0x0000000000110788>)
>>>
>>>
>>> But when I try to merged data back to the SpatialPolygonsDataFrame called
>>> shapes, I get the following error:
>>>
>>> shapes$change <- merged_data$change
>>>
>>> Error in `[[<-.data.frame`(`*tmp*`, name, value = c(-1.47141054005866,  :
>>> >   replacement has 3109 rows, data has 3233
>>>
>>>
>>>  Apologies for the messy example, what am I doing wrong? Any help will be
>>> greatly appreciated. Thank you!
>>>
>>> Sincerely,
>>>
>>> Shouro
>>>
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>>>
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>>
>>
>
>
> --
>
> Shouro Dasgupta
> PhD Candidate | Department of Economics
> Ca' Foscari University of Venezia
>
> ------------------------------
>
> Junior Researcher | Fondazione Eni Enrico Mattei (FEEM)
> Isola di San Giorgio Maggiore, 8 | 30124 Venice, Italy
> Tel: +39 041 2700 436
>
>

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