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Sample scatter chart

read "ef2015.csv"
extend jahr = 2015
read "ef2019.csv"
extend jahr = 2019
union
select partei == "GPS"
project kanton, jahr, fiktive_waehlende
deserialize
rename _2015 GPS, _2019 GPS_2019
project kanton, GPS, GPS_2019
read "ef2015.csv"
extend jahr = 2015
read "ef2019.csv"
extend jahr = 2019
union
select partei == "SP"
project kanton, jahr, fiktive_waehlende
deserialize
rename _2015 SP, _2019 SP_2019
project kanton, SP, SP_2019
join natural
delegate "scatterchart -colors green,red"
print

kanton GPS GPS_2019 SP SP_2019
Aargau 10828.504066 18547.808 31825.686102 31223.594
Basel-Landschaft 12356.154391 14259.967 19297.245576 17271.009
Basel-Stadt 6235.1577699 9503.294 18577.169632 17535.029
Bern / Berne 30116.423749 47237.093 69663.135654 58495.534
Fribourg / Freiburg 4806.3212935 10913.424 22004.340205 18585.542
Genève 11903.453658 24440.756 20693.500607 14628.013
Glarus 279.000 4742 2861.000
Graubünden / Grigioni / Grischun 3218.421 10676.881085 9987.431
Jura 2023.6035652 3514.140 6595.3182796 6074.800
Luzern 9625.3717566 16279.440 18452.790995 17996.047
Neuchâtel 4243.9038397 9207.804 10786.081525 7360.773
Schaffhausen 1062.6117639 2075.115 8943.3981606 7947.164
Schwyz 763.54385609 1333.619 7105.290203 7059.509
Solothurn 4846.7209748 9071.773 17473.872169 14651.913
St. Gallen 8367.9638369 14136.104 20650.117635 17026.829
Thurgau 4153.9465243 7656.950 9697.0603234 9132.741
Ticino 4103.4265999 13022.272 18530.990839 15120.942
Uri 3821 0.000 2659.000
Valais / Wallis 6147.2131995 12591.247 16670.346113 17916.725
Vaud 20272.672258 36117.839 40011.127017 37421.225
Zug 2796.2154445 7555.281 5372.8047717 3671.819
Zürich 29469.966711 59035.610 91508.239784 72590.406