violin plot

Requires: vioplot
To download vioplot type the following on the Stata command line:
ssc install vioplot


To run the example: copy the following into a do file and run


sysuse auto, clear

vioplot mpg, over(rep78) horizontal name(myplot) ///
title("Violin Plot of Mileage") subtitle("By repair record") ///
ytitle(Repair Record) ylab(, angle(horiz)) scheme(s2mono)



 

Density Plot


Requires: spgrid, spkde, spmap & mylabels 
to download these programs type the following 
on the Stata command line (if not already loaded):

ssc install spgrid
and then
ssc install spkde
and then
ssc install spmap
and then
ssc install mylabels

*------------------------------------------------


* 1. Normalize variables in the range [0,1]	

sysuse "auto.dta", clear
set more off

summarize price mpg
clonevar x = mpg
clonevar y = price
replace x = (x-0) / (50-0)
replace y = (y-0) / (20000-0)
mylabels 0(10)50, myscale((@-0) / (50-0)) local(XLAB)
mylabels 0(5000)20000, myscale((@-0) / (20000-0)) local(YLAB)

keep x y
save "xy.dta", replace

* 2. Generate a 100x100 grid

spgrid, shape(hexagonal) xdim(100) ///
xrange(0 1) yrange(0 1)               ///
dots replace                          ///
cells("2D-GridCells.dta")             ///
points("2D-GridPoints.dta")

* 3. Estimate the bivariate probability density function

spkde using "2D-GridPoints.dta", ///
xcoord(x) ycoord(y)                 ///
bandwidth(fbw) fbw(0.1) dots        ///
saving("2D-Kde.dta", replace)

* 4. Draw the density plot

use "2D-Kde.dta", clear
recode lambda (.=0)
spmap lambda using "2D-GridCells.dta",  ///
id(spgrid_id) clnum(20) fcolor(Rainbow) ///
ocolor(none ..) legend(off)             ///
point(data("xy.dta") x(x) y(y))         ///
freestyle aspectratio(1)                ///
xtitle(" " "Mileage (mpg)")             ///
xlab( `XLAB')                           ///
ytitle(" " "Price ({c S|}US)")          ///
ylab(`YLAB', angle(0))

exit
		 

sixplot

Displays six diagnostic and descriptive graphs for a single variable


Requires: sixplot
to download this program type the following on the Stata command line 
(if not already loaded):
ssc install sixplot

To run the example: copy the following into a do file and run



sysuse uslifeexp.dta


sixplot le_male

zmap

zmap graphs (or maps) binned values of a variable z with respect to two 
variables x and y treated as Cartesian coordinates.


Requires: zmap
to download this program type the following on the Stata 
command line (if not already loaded):
ssc install zmap

To run the example: copy the following into a do file and run




webuse nlswork, clear

egen mean = mean(ln_wage), by(age grade)

egen tag = tag(age grade)

label variable mean "mean ln wage"

summarize ln_wage if !missing(age, grade), detail

zmap mean age grade if tag, breaks(.993 1.166 1.361 1.641       ///
1.964 2.275 2.456) ms(S ..) ysc(on) xsc(on) yla(0/18, ang(h))   ///
ytitle(`: var label grade') mxla(15(5)45) note("")              ///
color(blue blue*0.5 orange*0.5 orange)   

netplot

An important part of what makes social network analysis so fascinating
to broad audiences is the possibility of visualization of networks.
netplot produces a network plot


Requires: netplot
to download this program type the following on the Stata command line
(if not already loaded):
ssc install netplot

To run the example: copy the following into a do file and run


//create a random network with 10 nodes
//(code adopted from the helpfile of stata2pajek)



clear

set obs 200

gen i=int(uniform()*10)+1

gen j=int(uniform()*10)+1

contract i j, freq(strength)

drop if i==j

sort i j

drop if strength <3 // --> keep only the "stronger" links

// Draw the network


netplot i j, type(circle) label

cmogram
cmogram graphs the means, medians, frequencies, or proportions 
of yvar, conditional on xvar.

Requires: cmogram
to download this program type the following on the Stata command 
line (if not already loaded):
ssc install cmogram

To run the example: copy the following into a do file and run


sysuse auto, clear

cmogram mpg weight, histopts(bin(5)) lfit cutpoint(3250) ///
lineat(3000 3250 3500) controls(price)

ellip
ellip calculates a confidence ellipse from the elliptically 
distributed variables yvar and xvar, and then graphs the 
confidence ellipse using graph twoway line.


Requires: ellip
to download this program type the following on the Stata command
line (if not already loaded):
ssc install ellip

To run the example: copy the following into a do file and run


sysuse auto, clear


ellip mpg weight, by(foreign, total legend(off)) ///
total tlabel(Total as a by-group) plot(scatter mpg weight)

drarea
Multiple graphics are produced in Stata by the rule "last drawn
first seen". So the objects that are drawn last are the ones
that are observed. The implication of this principle is that
when overlapping two rarea graphs the overlapping area is hidden
by the second rarea graph.  This command drarea overlays two
range area plots by merging the two colours and hence highlighting
the true overlap.

Requires: drarea
to download this program type the following on the Stata command
line (if not already loaded):
ssc install drarea

To run the example: copy the following into a do file and run



sysuse sp500, clear

generate high2 = high+15*uniform()

generate low2 = low+15*uniform()

drarea high low high2 low2 date in 1/20

linkplot
linkplot plots yvarlist versus xvar such that data points are 
linked (i.e. connected) within groups defined by distinct values of
linkvar. For example, with paired data it might be desired to 
link each pair, or with panel data it might be desired to link
observations within each panel.

Requires: linkplot
to download this program type the following on the Stata command
line (if not already loaded):
ssc install linkplot

To run the example: copy the following into a do file and run



clear
input ///
       A          B         id
      13.2       14.0          1
       8.2        8.8          2
      10.9       11.2          3
      14.3       14.2          4
      10.7       11.8          5
       6.6        6.4          6
       9.5        9.8          7
      10.8       11.3          8
       8.8        9.3          9
      13.3       13.6         10
end

rename A wearA
rename B wearB
reshape long wear, string i(id) j(j)
encode j, gen(material)

linkplot material wear, link(id) yla(1 2, valuelabel) ///
ysc(r(0.5 2.5)) yla(, ang(h))