Hi all,
I have problems with adjusting the position of the data labels. As seen in the scatterplot below, the data labels are pretty messy at the bottom:
Graph_data labels_forum.gph
This is the code I used for the chart and the data:
Is there a way to adjust the data labels without the graph editor? Additionally, is there a way to adjust the data labels such that the year could be reflected too? For example, the label "Thailand" should be "Thailand, 2018" in the scatter plot.
Thanks!
I have problems with adjusting the position of the data labels. As seen in the scatterplot below, the data labels are pretty messy at the bottom:
Graph_data labels_forum.gph
This is the code I used for the chart and the data:
Code:
correlate Overall_digital Trust_safety if !inlist(Country,"Hong Kong", "China") // 2018 and 2019
local rho: display %3.2f r(rho)
sum Trust_safety if Year == 2019
local min = r(min)
local max = r(max)
#delimit ;
twoway (scatter Overall_digital Trust_safety if Country!= "Hong Kong") ||
(scatter Overall_digital Trust_safety if inlist(Country,"China", "India", "Indonesia", "Japan", "Malaysia", "Philippines")
| inlist(Country, "Singapore", "ROK", "Thailand", "Vietnam"), msymbol(i) mlabcolor(red) mlabel(Country))||
(lfit Overall_digital Trust_safety if !inlist(Country,"Hong Kong","China"), range(40 75))
, note(Note: Line of best fit and correlation coefficient exclude China and Hong Kong)
text(0 35 "{&rho} = `rho'")
ytitle(Overall Digital Index score)
xtitle(Trust & Safety score)
legend(off)
scheme(s2color)
;
#delimit cr
Code:
* Example generated by -dataex-. For more info, type help dataex
clear
input double(Overall_digital Trust_safety) int Year str12 Country
1.4911944748969637 62.1 2018 "China"
1.1213408324666971 . 2018 "Hong Kong"
-.9354383366385858 65.1 2018 "India"
-1.170759219326978 65.9 2018 "Indonesia"
.4900689245217592 47.9 2018 "Japan"
.0743814016041916 56.5 2018 "Malaysia"
-.9019645756671696 56.7 2018 "Philippines"
1.3019748954571109 49.8 2018 "Singapore"
.59285067651566 47.7 2018 "ROK"
-.8939165934565277 35.1 2018 "Thailand"
-1.1697324803731215 67.4 2018 "Vietnam"
1.4633771560661124 73.2 2019 "China"
1.3356631016510268 . 2019 "Hong Kong"
-.5816092928110765 70.7 2019 "India"
-1.1366984242244103 69.5 2019 "Indonesia"
.8734172000204578 44.1 2019 "Japan"
.21963797533267906 63.6 2019 "Malaysia"
-.8669008987190485 56 2019 "Philippines"
1.417392252169481 52.6 2019 "Singapore"
.9159432918807312 46.2 2019 "ROK"
-1.0820484226481373 57.3 2019 "Thailand"
-.9675688685359461 66.5 2019 "Vietnam"
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end
Thanks!