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Sample bubble chart

read "ef2015.csv"
extend jahr = 2015
read "ef2019.csv"
extend jahr = 2019
union
project inline kanton, jahr, fiktive_waehlende sum
extend wahlanteil = fiktive_waehlende / fiktive_waehlende_sum
select partei == "GPS"
dup
project kanton, jahr, wahlanteil
deserialize
swap
project kanton, fiktive_waehlende_sum avg
// scale bubbles to pixels
update fiktive_waehlende_sum_avg = fiktive_waehlende_sum_avg / 20000
join natural
label _2015 "GPS"
delegate "bubblechart -colors green"
print

kanton GPS 2019 fiktive_waehlende_sum_avg
Aargau 0.054699359813 0.09781515812 9.689624974983
Basel-Landschaft 0.141946447834 0.179956924321 4.157225049996
Basel-Stadt 0.111801286892 0.176950322124 2.736899999986
Bern / Berne 0.085068155108 0.135850420564 17.543524975117
Fribourg / Freiburg 0.052855051944 0.124637955254 4.462375000026
Genève 0.11467571274 0.24611560228 5.07767499998
Glarus 0.027493102089 0.5074
Graubünden / Grigioni / Grischun 0.055164734579 2.91710005
Jura 0.072749624863 0.156239544894 1.257700025003
Luzern 0.070726947628 0.122282280478 6.730549999986
Neuchâtel 0.0930884808 0.208081268403 2.246024975013
Schaffhausen 0.034234729337 0.068296305019 1.535575024995
Schwyz 0.014063653137 0.02609770846 2.634825
Solothurn 0.055552994152 0.114172107104 4.167549974995
St. Gallen 0.057460045162 0.105356506437 6.995125024986
Thurgau 0.054373874605 0.105991751305 3.715924974993
Ticino 0.035280994265 0.121137413954 5.595174999972
Uri 0.26282844958 0 0.6622
Valais / Wallis 0.048884399201 0.105883539641 6.116649999996
Vaud 0.112503453229 0.196775988825 9.093599974986
Zug 0.071574869954 0.192295270865 1.958924975001
Zürich 0.068892244905 0.140771127038 21.178550025069