feat: add regions df for all areas

results/analysis/all_variables_15-18-21_Sat_104.csv

@@ -0,0 +1,13 @@
+,area,time,average speed,average duration,average transit time,average walk time,average walk share,walk share under 40%,average amount of changes,max changes,time difference to car,transit is reasonable,out of,cinemas,population aggr,population density,built-up area,transit departures,transit stops,level
+0,Heidelberg,18.0,2.041633463932617,1509.472115384615,777.9807692307693,731.4913461538462,52.82912090548519,0.3173076923076923,0.6033653846153846,4.0,812.7310096153847,89.66346153846155,1.0,5,162273,1491.07,30.58,47709.0,238.0,top
+1,Halle (Saale),18.0,2.0309891888023297,1606.7093385214007,804.9805447470817,801.728793774319,55.232978546077646,0.2596153846153846,0.3638132295719844,5.0,995.0832684824902,89.03846153846155,0.9884615384615384,6,242083,1792.81,52.92,60209.0,290.0,top
+2,Osnabrück,18.0,1.958742249138484,2003.0859564164648,1118.6440677966102,884.4418886198547,44.87394408291448,0.46875,0.8716707021791767,5.0,1373.287167070218,84.61538461538461,0.9927884615384616,5,167366,1397.05,50.2,60580.0,317.0,top
+3,Aachen,18.0,1.9087026819344992,1160.9978846153847,747.6923076923077,413.3055769230769,41.856507202424936,0.5211538461538462,0.7807692307692308,7.0,638.3396153846153,79.8076923076923,1.0,5,252136,1567.52,40.0,83796.0,414.0,top
+0,Landau in der Pfalz,18.0,1.0464947923634034,1325.3460784313727,488.2352941176471,837.1107843137255,67.05064304609756,0.1057692307692307,0.1764705882352941,3.0,936.435294117647,46.15384615384615,0.9807692307692308,2,47610,574.03,24.95,6234.0,90.0,mid
+1,Bad Soden am Taunus,18.0,1.2401457989112998,960.501923076923,439.61538461538464,520.8865384615384,60.22795634375304,0.2884615384615384,0.0192307692307692,1.0,751.3788461538461,33.65384615384615,1.0,1,23162,1852.96,40.8,2117.0,33.0,mid
+2,Aue-Bad Schlema,18.0,,,,,,0.0,,,,0.0,0.0,1,19864,545.26,38.32,3531.0,72.0,mid
+3,Alfeld (Leine),18.0,1.0594983365781243,4068.389423076923,1994.423076923077,2073.966346153846,60.13777162199404,0.0961538461538461,0.5096153846153846,2.0,3586.750961538462,27.884615384615387,1.0,1,18723,256.9,18.8,2264.0,65.0,mid
+0,Kandern,18.0,,,,,,0.0,,,,0.0,0.0,1,8537,137.12,9.16,556.0,23.0,base
+1,Kühlungsborn,18.0,1.11165373070417,1787.4259615384617,180.0,1607.4259615384617,89.5287633316919,0.0,0.0,0.0,1365.6320388349516,57.69230769230769,1.0,1,8037,497.03,29.62,363.0,11.0,base
+2,Seefeld,18.0,,,,,,0.0,,,,0.0,0.0,1,7694,220.77,12.83,1562.0,24.0,base
+3,Ankum,18.0,1.0858923601081465,1265.128735632184,113.79310344827586,1151.3356321839085,88.07366752792119,0.0,0.0,0.0,1050.2448275862068,33.65384615384615,0.8365384615384616,1,8035,121.19,12.58,796.0,43.0,base

scripts/analysis/concat_areas.py

@@ -91,4 +91,4 @@ def make_areas_df(only_valid=False, path_end='15-18-21_Sat_104'):
     time = [15, 18, 21]
     make_big_df(time, 'analysis')
     make_big_df(time, 'starts_variables')
-    make_areas_df(True)
+    make_areas_df()