Installation | Syntax | Citation guidelines | Examples | Feedback | Change log
(22 Aug 2024)
This package provides the ability to draw bi-variate maps in Stata. It is based on the Bi-variate maps Guide.
As of version 2.0 (released on 22nd August 2024), bimap uses geoplot for Stata versions 17 or newer, and spmap for Stata versions 16 or earlier. Users with newer versions can still opt to use the original spmap implementation by defining the original code (with minor changes, see below) and using the option old
. Information on which version is detected and which map package is used can be displayed by using the detail
option.
As more and more users switch to newer Stata versions, the spmap implementation will eventually be phased out. As of v2.0 it will no longer be developed further.
The package can be installed via SSC or GitHub. The GitHub version, might be more recent due to bug fixes, feature updates etc, and may contain syntax improvements and changes in default values. See version numbers below. Eventually the GitHub version is published on SSC. All examples are updated to the latest version and might not be compatible with the old ones. Please check the documentation and change logs.
The package can be installed from SSC (v1.9):
ssc install bimap, replace
Or it can be installed from GitHub (v2.0):
net install bimap, from("https://raw.githubusercontent.com/asjadnaqvi/stata-bimap/main/installation/") replace
For using the command with geoplot
the following packages are required:
ssc install geoplot, replace
ssc install moremata, replace
ssc install palettes, replace
ssc install colrspace, replace
For using the command with spmap
the following packages are required:
ssc install spmap, replace
ssc install palettes, replace
ssc install colrspace, replace
Even if you have these packages installed, please check for updates: ado update, update
.
Optional: Users can also install the geo2xy
package for projection transformations, even though geoplot
supports projects internally as well:
ssc install geo2xy, replace
Optional: If you want to make a clean figure, then it is advisable to load a clean scheme. I personally use the following:
ssc install schemepack, replace
set scheme white_tableau
You can also push the scheme directly into the graph using the scheme(schemename)
option.
I also prefer narrow fonts in figures with long labels. You can change this as follows:
graph set window fontface "Arial Narrow"
The syntax for the latest version is as follows:
bimap vary varx [if] [in], frame(name)
[ geo(options) geopost(options)
palette(name) reverse clr0(str) clrx(str) clry(str) clrsaturate(num)
cut(pctile|equal) cutx(numlist) cuty(numlist) binsproper bins(num >=2) binx(num >=2) biny(num >=2) values count
percent showlegend ocolor(str) osize(str) ndocolor(str) ndfcolor(str) ndfsize(str) xdiscrete ydiscrete
labxgap(num) labygap(num) textx(str) texty(str) formatx(str) formaty(str) detail
textsize(str) textlabsize(str) vallabsize(str) textcolor(str) textlabcolor(str) vallabcolor(str)
xscale(num) yscale(num) * ]
with the following minimal syntax requirement:
bimap vary varx, frame(framename)
bimap vary varx [if] [in], shp(shapefile)
[ old polygon(str) line(str) point(str) label(str) arrow(str) diagram(str) scalebar(str)
palette(name) reverse clr0(str) clrx(str) clry(str) clrsaturate(num)
cut(pctile|equal) cutx(numlist) cuty(numlist) binsproper bins(num >=2) binx(num >=2) biny(num >=2) values count
percent showlegend ocolor(str) osize(str) ndocolor(str) ndfcolor(str) ndfsize(str) xdiscrete ydiscrete
labxgap(num) labygap(num) textx(str) texty(str) formatx(str) formaty(str) detail
textsize(str) textlabsize(str) vallabsize(str) textcolor(str) textlabcolor(str) vallabcolor(str)
xscale(num) yscale(num) * ]
with the following minimal syntax requirement:
bimap vary varx, shp(shapefile)
Note that v2.0 changes the use of the shapefile syntax. This might be a minor inconvinience for older users of bimap.
See help bimap
for details.
Software packages take countless hours of programming, testing, and bug fixing. If you use this package, then a citation would be highly appreciated. Suggested citations:
in BibTeX
@software{bimap,
author = {Naqvi, Asjad},
title = {Stata package ``bimap''},
url = {https://github.com/asjadnaqvi/stata-bimap},
version = {2.0},
date = {2024-08-22}
}
or simple text
Naqvi, A. (2024). Stata package "bimap" version 2.0. Release date 22 August 2024. https://github.com/asjadnaqvi/stata-bimap.
or see SSC citation (updated once a new version is submitted)
The examples showcase both the syntax for the use with geoplot
(first syntax) and spmap
(second syntax). The map outputs have been aligned to the extent possible but very minor differences in outputs might remain. Additionally, as geoplot
is still in active development, output might break with latest updates or syntax might change. Please report these as soon as possible.
Since I am using Stata 18+, I have to specify old
option to pass the syntax to use spmap
. This might be uncessary if you have older Stata versions.
Users can either download the files from GIS and dump them in a folder or directly get them from Stata:
Set up the data:
cd <change path to the working directory>
foreach x in county county_shp2 state state_shp2 usa_county2 {
copy "https://github.com/asjadnaqvi/stata-bimap/raw/main/GIS/`x'.dta" "`x'.dta", replace
}
Test whether the geoplot
is working properly. First set up the layer frames:
// create the geoframes
geoframe create county, replace shp(county_shp2)
geoframe create state, replace shp(state_shp2)
geoframe create cities usa_county2, replace shp(county_shp2) // minor example of pairing with point location data.
// make the country frame active
frames change county
destring _all, replace
merge 1:1 STATEFP COUNTYFP using county_race
keep if _m==3
drop _m
geoplot (area county share_afam) (line state)
Test whether the spmap
is working properly:
spmap share_afam using county_shp2, id(_ID) clm(custom) clb(0(10)100) fcolor(Heat)
Let's test the bimap
command:
bimap share_hisp share_afam, frame(county) cut(pctile) palette(pinkgreen)
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(pinkgreen)
bimap share_hisp share_afam , frame(county) cut(pctile) palette(pinkgreen) count values
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(pinkgreen) count values
bimap share_hisp share_afam , cut(pctile) palette(pinkgreen) percent values frame(county).
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(pinkgreen) percent values
bimap share_hisp share_afam, frame(county) cut(equal) palette(pinkgreen) count values
bimap share_hisp share_afam, shp(county_shp2) old cut(equal) palette(pinkgreen) count values
These old palettes can still be used and will default to 3x3 bins.
local i = 1
foreach x in pinkgreen0 bluered0 greenblue0 purpleyellow0 yellowblue0 orangeblue0 brew1 brew2 brew3 census rgb viridis gscale {
bimap share_hisp share_afam, frame(county) cut(pctile) palette(`x') percent title("Legacy scheme: `x'")
local ++i
}
local i = 1
foreach x in pinkgreen0 bluered0 greenblue0 purpleyellow0 yellowblue0 orangeblue0 brew1 brew2 brew3 census rgb viridis gscale {
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(`x') percent title("Legacy scheme: `x'")
local ++i
}
bimap share_asian share_afam, cut(pctile) palette(bluered) frame(county) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
textx("Share of African Americans") texty("Share of Asians") texts(3.5) textlabs(3) values count ///
osize(none) geo((line state))
bimap share_asian share_afam, shp(county_shp2) old cut(pctile) palette(bluered) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
textx("Share of African Americans") texty("Share of Asians") texts(3.5) textlabs(3) values count ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(white) osize(0.3))
bimap share_asian share_afam, cut(pctile) palette(orangeblue) frame(county) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
textx("Share of African Americans") texty("Share of Asians") texts(3.5) textlabs(3) values count ///
osize(none) geo((line state, lc(white) lw(0.2)))
bimap share_asian share_afam, shp(county_shp2) old cut(pctile) palette(yellowblue) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
textx("Share of African Americans") texty("Share of Asians") texts(3.5) textlabs(3) values count ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
bimap share_asian share_hisp, cut(pctile) palette(orangeblue) frame(county) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
textx("Share of Hispanics") texty("Share of Asians") texts(3.5) textlabs(3) values count ///
osize(none) geo((line state, lc(black) lw(0.2)))
bimap share_asian share_hisp, shp(county_shp2) old cut(pctile) palette(orangeblue) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
textx("Share of Hispanics") texty("Share of Asians") texts(3.5) textlabs(3) values count ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
bimap share_hisp share_afam, cut(pctile) palette(pinkgreen) percent frame(county) ///
title("{fontface Arial Bold:A Stata bivariate map}") ///
note("Data from the US Census Bureau. Counties with population > 100k plotted as proportional dots.", size(1.8)) ///
textx("Share of African Americans") texty("Share of Hispanics") texts(3.5) textlabs(3) values ///
osize(none) ///
geo( (line state, lc(black) lw(0.2)) (point cities [w = tot_pop] if tot_pop>1e5, mc(lime%80) msize(0.8) lc(black)) )
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(pinkgreen) percent ///
title("{fontface Arial Bold:A Stata bivariate map}") ///
note("Data from the US Census Bureau. Counties with population > 100k plotted as proportional dots.", size(1.8)) ///
textx("Share of African Americans") texty("Share of Hispanics") texts(3.5) textlabs(3) values ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(white) osize(0.3)) ///
point(data("usa_county2") x(_CX) y(_CY) select(keep if tot_pop>100000) proportional(tot_pop) psize(absolute) fcolor(lime%85) ocolor(black) osize(0.12) size(0.9) )
Let's make a bimap
with percentiles as cut-offs and percentages shown in boxes:
bimap share_hisp share_afam, cut(pctile) palette(orangeblue) frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values percent ///
osize(none) geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(orangeblue) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values percent ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
we can now modify the cut-offs as follows:
bimap share_hisp share_afam, cut(pctile) palette(orangeblue) frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values percent ///
osize(none) geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cuty(0(20)100) cutx(0(20)100) palette(orangeblue) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values percent ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
Cut-offs can be formatted as follows:
bimap share_hisp share_afam, cuty(0(25)100) cutx(0(25)100) formatx(%3.0f) formaty(%3.0f) palette(orangeblue) frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
osize(none) geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cuty(0(25)100) cutx(0(25)100) formatx(%3.0f) formaty(%3.0f) palette(orangeblue) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
If we define only one custom cut-off, the other will automatically take on the pctile values:
bimap share_hisp share_afam, cutx(0 2 6 100) formatx(%5.0f) palette(orangeblue) frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values percent ///
osize(none) geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cutx(0 2 6 100) formatx(%5.0f) palette(orangeblue) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values percent ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
bimap share_hisp share_afam, cut(pctile) palette(census) frame(county) ///
note("Data from the US Census Bureau.", size(small)) ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.2) textlabs(3) values percent labxgap(0.05) labygap(0.05) ///
ocolor(black) osize(0.03) ///
geo((line state, lc(black) lw(0.2))) showlegend ///
geopost( ///
compass ///
sbar(length(1000) units(km) position(sw)) ///
)
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(census) ///
note("Data from the US Census Bureau.", size(small)) ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.2) textlabs(3) values percent ///
ocolor(black) osize(0.03) ///
polygon(data("state_shp2") ocolor(black) osize(0.2) legenda(on) leglabel(State boundaries)) ///
scalebar(units(500) scale(1/1000) xpos(100) label(Kilometers)) ///
showleg legenda(off) legend(pos(7) size(5)) legstyle(2)
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(census) ///
note("Data from the US Census Bureau.", size(small)) ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.2) textlabs(3) values percent labxgap(0.05) labygap(0.05) ///
ocolor(black) osize(0.03) ///
polygon(data("state_shp2") ocolor(black) osize(0.2) legenda(on) leglabel(State boundaries)) ///
scalebar(units(500) scale(1/1000) xpos(100) label(Kilometers)) ///
showleg legenda(off) legend(pos(7) size(5)) legstyle(2)
Check for legend color options:
bimap share_asian share_afam, cut(pctile) frame(county) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
textx("Share of African Americans") texty("Share of Asians") values count textcolor(lime) textlabcolor(blue) vallabc(red) ///
osize(none) ///
geo((line state, lc(white) lw(0.3)))
bimap share_asian share_afam, shp(county_shp2) old cut(pctile) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
textx("Share of African Americans") texty("Share of Asians") values count textcolor(lime) textlabcolor(blue) vallabc(red) ///
osize(none) ///
polygon(data("state_shp2") ocolor(white) osize(0.3))
Check for label wrapping in the legend:
bimap share_asian share_afam, cut(pctile) frame(county) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
textx("Share of African Americans") texty("Share of Asians") wrap(16) values count ///
osize(none) ///
geo((line state, lc(white) lw(0.3)))
bimap share_asian share_afam, shp(county_shp2) old cut(pctile) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
textx("Share of African Americans") texty("Share of Asians") wrap(16) values count ///
osize(none) ///
polygon(data("state_shp2") ocolor(white) osize(0.3))
Check for hiding the legend:
bimap share_asian share_afam, cut(pctile) frame(county) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
osize(none) ///
geo((line state, lc(white) lw(0.3))) nolegend
bimap share_asian share_afam, shp(county_shp2) old cut(pctile) ///
title("{fontface Arial Bold:A Stata bivariate map}") note("Data from the US Census Bureau.") ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(white) osize(0.3)) nolegend
If condition checks with legends
bimap share_hisp share_afam if STATEFP==36, cut(pctile) palette(census) frame(county) ///
title("New York") ///
note("Data from the US Census Bureau.", size(small)) ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.2) textlabs(3) values percent ///
ocolor(black) osize(0.03) ///
geo((line state if _ID==19, lc(black) lw(0.2))) nolegend
bimap share_hisp share_afam if STATEFP==36, shp(county_shp2) old cut(pctile) palette(census) ///
title("New York") ///
note("Data from the US Census Bureau.", size(small)) ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.2) textlabs(3) values percent ///
ocolor(black) osize(0.03) ///
polygon(data("state_shp2") select(keep if _ID==19) ocolor(black) osize(0.2) legenda(on) leglabel(State boundaries)) ///
showleg legenda(off) legend(pos(7) size(5)) legstyle(2)
bimap share_hisp share_afam, cut(pctile) palette(orangeblue) bins(5) frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
osize(none) ///
geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(orangeblue) bins(5) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
bimap share_hisp share_afam, cut(pctile) palette(orangeblue) binx(4) biny(5) frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
osize(none) ///
geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(orangeblue) binx(4) biny(5) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
bimap share_hisp share_afam, cut(pctile) palette(orangeblue) binx(3) biny(8) frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
osize(none) ///
geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(orangeblue) binx(3) biny(8) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
bimap share_hisp share_afam, cut(pctile) palette(orangeblue) bins(8) frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values ///
osize(none) ///
geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(orangeblue) bins(8) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.1))
bimap share_hisp share_afam, cut(pctile) palette(orangeblue) bins(8) frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values ///
osize(none) ///
geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(orangeblue) reverse bins(8) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
bimap share_hisp share_afam, cut(pctile) palette(orangeblue) clr0(white) clrx(red) bins(6) clrsat(10) frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
osize(none) ///
geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(orangeblue) clr0(white) clrx(red) bins(6) clrsat(10) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
bimap share_hisp share_afam, cut(pctile) palette(orangeblue) bins(4) percent frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values ///
osize(none) ///
geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cut(pctile) palette(orangeblue) bins(4) percent ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
Bins can be scaled to show actual division. Use this cautiously especially if the data distribution is highly skewed.
bimap share_hisp share_afam, cuty(0 20 60 100) cutx(0 30 50 75 100) palette(orangeblue) formatx(%5.0f) formaty(%5.0f) binsproper frame(county) ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
osize(none) ///
geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old cuty(0 20 60 100) cutx(0 30 50 75 100) palette(orangeblue) formatx(%5.0f) formaty(%5.0f) binsproper ///
note("Data from the US Census Bureau.") ///
texty("Share of Hispanics") textx("Share of African Americans") texts(3.5) textlabs(3) values count ///
ocolor() osize(none) ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
Let's make some variables discrete:
xtile discx = share_afam, n(4)
gen discy = share_hisp < 10
lab de dx 1 "Catx 1" 2 "Catx 2" 3 "Catx 3" 4 "Catx 4"
lab val discx dx
lab de dy 0 "Caty 0" 1 "Caty 1"
lab val discy dy
tab discy discx, m
We can also now declare these variables as discrete while using bimap
in any combination:
bimap discy share_afam, palette(yellowblue) values count ydisc frame(county)
bimap discy share_afam, shp(county_shp2) old palette(yellowblue) values count ydisc
bimap share_hisp discx, palette(yellowblue) values count xdisc frame(county)
bimap share_hisp discx, shp(county_shp2) old palette(yellowblue) values count xdisc
bimap discy discx, palette(yellowblue) values count xdisc ydisc frame(county)
bimap discy discx, shp(county_shp2) old palette(yellowblue) values count xdisc ydisc
replace share_hisp = . if stname=="Texas"
bimap share_hisp share_afam, palette(orangeblue) frame(county) ///
ndfcolor(pink) ndocolor(lime) ndsize(0.2) ///
values count ///
geo((line state, lc(black) lw(0.2)))
bimap share_hisp share_afam, shp(county_shp2) old palette(orangeblue) ///
ndfcolor(pink) ndocolor(lime) ndsize(0.3) ///
values count ///
polygon(data("state_shp2") ocolor(black) osize(0.2))
Please open an issue to report errors, feature enhancements, and/or other requests.
v2.0 (22 August 2024)
- Major update. Support for
geoplot
for Stata versions 17 or newer. Support forspmap
for Stata versions 16 or older. Versions are auto detected. - Stata 17 or newer users can use the option
old
to call in thespmap
version. This ensures that the code of seasonedbimap
users does not break. - Minor change in syntax for
spmap
versions frombimap y x using shapefile
tobimap y x, shp(shapefile)
. This is to ensure consistency for upcoming releases. - Option
detail
added to show which Stata version is detected and which map program is used. This might be useful in case you want to have more information.
v1.9 (19 June 2024)
- Fixed and added several options to control legends:
textcolor()
,textlabcolor()
,vallabcolor()
. - Better options for
textsize()
,textlabsize()
,vallabsize()
. - Added
wrap()
to wrap labels in legends. - Added
nolegend
option to generate maps without a bi-variate legend. This is useful is several maps are being generated with a controlled legend and need to be combined in one figure. - Several improvements to graph passthru options.
v1.82 (04 May 2024)
- Added
textcolor()
to control random colors appearing in legend labels under some schemes. - Backend improvements to some defaults.
v1.81 (22 Aug 2023)
- Fixed a bug where missing data points where getting dropped (reported by Steve Johnson).
- Fixed passthru of the
ndisze()
option.
v1.8 (26 Jun 2023)
- Changed the ways
cutx()
andcuty()
are calculated (requested by Paul Hufe). These now take on lists which are used as provided. - Removed
textgap()
that was left over from the old legend code. - Added
labxgap()
andlabygap()
to allows users to offset the labels and improved the position of the legend axes titles. - Various improvements including
v1.7 (15 Jun 2023)
- Added two new options
xdiscrete
andydiscrete
to support discrete variables.
v1.62 (19 May 2023)
- Fixed bugs in legend labels (reported by Kit Baum). Minor improvements.
v1.61 (12 Apr 2023)
- Fixed a major bug in the legend. The boxes were not rescaling properly.
v1.6 (17 Mar 2023) (major update)
- Scalable color palettes.
- Customizable bins.
- Customizable colors.
- Dynamic scalable legends.
- Option for proper spacing of bins on legends.
- Several defaults and checks added.
- Several quality of life adjustments to make
bimap
easier to use.
v1.51 (14 Nov 2022)
- Minor fixes to legend text options.
v1.5 (05 Nov 2022)
- Three new palettes added:
rgb
,viridis
,gscale
. - Added
spmap
passthru options forarrow
,diagram
, andscalebar
.
v1.4 (04 Oct 2022)
- Added the option to add custom cut-offs.
- Added the option to format cut-offs,
- Added the option to show default
spmap
legends. - Code clean up. New error checks.
v1.33 (29 Sep 2022)
- Bug fixes to
spmap
passthru options. - Add a new option
textgap
to allow adjustment of the distance of axes labels to the legend.
v1.32 (19 Aug 2022)
- Fixed an error in variable name comparisons (thanks to Cristian Jordan Diaz).
v1.31 (20 Jun 2022)
- Error fix in cut-offs skipping the last shape file (thanks to Mattias Öhman).
- Fixed color assignments to the 3x3 groups. If a group was missing, the colors were wrongly assigned.
v1.3 (26 May 2022)
- Percent option added to legend to show box share (thanks to Kit Baum).
- Legend corner label made lighter for visibility.
- Four special use palettes added:
brew1
,brew2
,brew3
,brew4
,census
.
v1.2 (29 Apr 2022)
- Fixed a bug in cut-off groupings (thanks to Ruth Watkinson).
- Error in how cut-off values are collected is fixed.
- Two palettes added
yellowblue
,orangeblue
. If you have more palette suggestions, then please let me know! - Several
spmap
additional layer commands added as passthru options (thanks to Pierre-Henri Bono). - Count of each category added as an option.
- Several bug fixes and error checks added.
v1.1 (14 Apr 2022)
- Errors in ado file corrected.
- Help file was missing a couple of options.
v1.0 (08 Apr 2022)
- Public release.