Chargement des données :
tm_basemap(c(leaflet::providers$Esri.WorldTopoMap,
leaflet::providers$OpenStreetMap,
leaflet::providers$GeoportailFrance.orthos)) +
tm_shape(st_make_valid(all_isochrones),
name = "Isochrones 10min à pied") + tm_borders() +
tm_shape(data_car) + tm_dots(col = "data_rennes_classes",
palette = couleurs,
title = "Types d'emplacement",
legend.show = TRUE,
size = 0.9,
labels = c("Très peu favorable", "Peu favorable", "Moyennement favorable", "Favorable", "Très favorable")
) +
tm_shape(data_bike) + tm_dots(col = "data_rennes_classes",
palette = couleurs, title = "Types d'emplacement",
legend.show = TRUE,
size = 0.5,
labels = c("Très peu favorable", "Peu favorable", "Moyennement favorable", "Favorable", "Très favorable")) +
tm_shape(data_foot) + tm_dots(col = "data_rennes_classes",
palette = couleurs, title = "Types d'emplacement",
legend.show = TRUE,
size = 0.1,
labels = c("Très peu favorable", "Peu favorable", "Moyennement favorable", "Favorable", "Très favorable")) +
tm_shape(data_foot_c4) + tm_dots(size = 0.3, "#d95f0eff") +
tm_shape(data_foot_c5) + tm_dots(size = 0.3, "#993404ff") +
tm_shape(gares) + tm_dots() +
tm_text("Intitulé.gare", size = 1, fontface = 2,
just = "top", ymod = 0.5) +
tm_scale_bar()glimpse(raw_data_foot)## Rows: 26
## Columns: 23
## $ pk <chr> "28", "29", "30", "31", "32", "33", "34"…
## $ ID_number <int> 22801, 22811, 22821, 22831, 22841, 22851…
## $ sum_population <dbl> 8745, 6923, 1689, 1689, 2359, 2359, 670,…
## $ sum_lits <dbl> 2457, 2798, 1517, 1517, 2174, 2174, 657,…
## $ longueur_route <dbl> 15479.1062, 10379.9448, 8024.8130, 12438…
## $ longueur_pistes_cyclables <dbl> 1511.3255, 1575.9503, 1324.7271, 413.489…
## $ superficie_vegetation <dbl> 23776.63108, 103946.50697, 75906.62727, …
## $ nombre_arrets <dbl> 25, 10, 8, 19, 0, 0, 0, 0, 0, 0, 0, 0, 1…
## $ nombre_parkings <dbl> 1232, 1230, 10, 6, 0, 0, 0, 0, 0, 0, 0, …
## $ nombre_commerces <dbl> 11, 2, 2, 4, 0, 0, 0, 0, 0, 0, 1, 0, 0, …
## $ nombre_loisirs <dbl> 8, 3, 1, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ nombre_restauration <dbl> 20, 9, 8, 2, 0, 1, 0, 0, 0, 0, 0, 1, 1, …
## $ nombre_sports <dbl> 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ nombre_ronds_points <dbl> 1, 0, 1, 5, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0…
## $ nombre_eleves <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ superficie_iso <dbl> 669846.72, 662042.75, 516802.55, 711570.…
## $ ZA <dbl> 646070.08, 558096.24, 440895.92, 656620.…
## $ passage_niveau <dbl> 1, 3, 3, 4, 1, 1, 1, 0, 0, 1, 1, 0, 2, 0…
## $ sum_population_carreau_decoup <dbl> 1522.799072, 858.837888, 336.378225, 607…
## $ nombre_arrets_v2 <dbl> 7, 3, 2, 4, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0…
## $ nombre_sante <dbl> 11, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ pente_moyenne <dbl> 1.838647, 5.309373, 4.873297, 3.003272, …
## $ geom <POINT [m]> POINT (474102.4 6914309), POINT (4…glimpse(data_foot)## Rows: 32
## Columns: 13
## $ ID_number <dbl> 22801, 22811, 22821, 22831, 22841, 22851…
## $ sum_population_carreau_decoup <dbl> 1.0000000000, 0.5630432654, 0.2192095085…
## $ nombre_loisirs <dbl> 1.000, 0.375, 0.125, 0.500, 0.000, 0.000…
## $ nombre_commerces <dbl> 1.00000000, 0.18181818, 0.18181818, 0.36…
## $ nombre_restauration <dbl> 1.00, 0.45, 0.40, 0.10, 0.00, 0.05, 0.00…
## $ nombre_arrets <dbl> 0.96153846, 0.38461538, 0.30769231, 0.73…
## $ longueur_route <dbl> 1.0000000000, 0.6672502371, 0.5135642748…
## $ ZA <dbl> 0.89207553, 0.76854020, 0.60396422, 0.90…
## $ passage_niveau <dbl> 0.25, 0.75, 0.75, 1.00, 0.25, 0.25, 0.25…
## $ pente_moyenne <dbl> 0.05286009, 0.64084254, 0.56696606, 0.25…
## $ total_sum_allegee <dbl> 7.05075390, 3.49942473, 2.53428243, 4.55…
## $ geom <POINT [m]> POINT (474102.4 6914309), POINT (4…
## $ data_rennes_classes <int> 5, 4, 3, 4, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2…glimpse(raw_data_bike)## Rows: 25
## Columns: 23
## $ pk <chr> "28", "29", "30", "31", "32", "33", "34"…
## $ ID_number <int> 22801, 22811, 22821, 22831, 22841, 22851…
## $ sum_population <dbl> 11577, 11577, 10434, 7593, 7593, 7869, 2…
## $ sum_lits <dbl> 4157, 4157, 3974, 3455, 3455, 3455, 2174…
## $ longueur_route <dbl> 119559.672, 115738.423, 75340.363, 44003…
## $ longueur_pistes_cyclables <dbl> 16919.5441, 12039.8573, 6549.2796, 1873.…
## $ superficie_vegetation <dbl> 802677.49, 814159.12, 784597.91, 1030628…
## $ nombre_arrets <dbl> 86, 75, 63, 31, 27, 8, 0, 0, 12, 0, 12, …
## $ nombre_parkings <dbl> 6398, 5745, 1264, 509, 16, 4, 0, 0, 0, 0…
## $ nombre_commerces <dbl> 99, 112, 51, 18, 18, 2, 0, 0, 1, 0, 1, 2…
## $ nombre_loisirs <dbl> 38, 39, 23, 10, 11, 3, 0, 1, 1, 0, 1, 10…
## $ nombre_restauration <dbl> 129, 156, 81, 35, 34, 2, 2, 0, 2, 0, 4, …
## $ nombre_sports <dbl> 2, 3, 2, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0…
## $ nombre_ronds_points <dbl> 20, 18, 13, 7, 6, 2, 0, 0, 1, 0, 1, 8, 9…
## $ nombre_eleves <dbl> 965, 965, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ superficie_iso <dbl> 7649689.3, 7429630.5, 5158706.0, 4226492…
## $ ZA <dbl> 6847011.8, 6615471.4, 4374108.1, 3195863…
## $ passage_niveau <dbl> 5, 7, 9, 9, 9, 7, 4, 1, 2, 1, 4, 4, 4, 4…
## $ pente_moyenne <dbl> 3.230674, 3.648856, 4.808464, 6.443810, …
## $ sum_population_carreau_decoup <dbl> 8249.6722, 7828.4920, 5267.0826, 1894.53…
## $ nombre_arrets_v2 <dbl> 24, 20, 18, 8, 6, 2, 0, 0, 3, 0, 3, 9, 8…
## $ nombre_sante <dbl> 30, 31, 18, 1, 1, 0, 0, 0, 0, 0, 0, 10, …
## $ geom <POINT [m]> POINT (474102.4 6914309), POINT (4…glimpse(data_bike)## Rows: 31
## Columns: 15
## $ ID_number <dbl> 22801, 22811, 22821, 22831, 22841, 22851…
## $ sum_population_carreau_decoup <dbl> 0.97173592, 0.92148153, 0.61585924, 0.21…
## $ nombre_eleves <dbl> 0.7788539, 0.7788539, 0.0000000, 0.00000…
## $ nombre_loisirs <dbl> 0.80851064, 0.82978723, 0.48936170, 0.21…
## $ nombre_sante <dbl> 0.43478261, 0.44927536, 0.26086957, 0.01…
## $ nombre_commerces <dbl> 0.482926829, 0.546341463, 0.248780488, 0…
## $ nombre_restauration <dbl> 0.568281938, 0.687224670, 0.356828194, 0…
## $ nombre_sports <dbl> 0.6666667, 1.0000000, 0.6666667, 0.33333…
## $ longueur_route <dbl> 1.00000000, 0.96622037, 0.60910377, 0.33…
## $ ZA <dbl> 1.00000000, 0.96319317, 0.60689476, 0.41…
## $ passage_niveau <dbl> 0.5555556, 0.7777778, 1.0000000, 1.00000…
## $ pente_moyenne <dbl> 0.07533643, 0.19567924, 0.52938664, 1.00…
## $ total_sum_allegee <dbl> 6.71175851, 7.14237772, 3.85436439, 1.76…
## $ geom <POINT [m]> POINT (474102.4 6914309), POINT (4…
## $ data_rennes_classes <int> 4, 4, 3, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2…glimpse(raw_data_car)## Rows: 26
## Columns: 22
## $ pk <chr> "28", "29", "30", "31", "32", "33", "34"…
## $ ID_number <int> 22801, 22811, 22821, 22831, 22841, 22851…
## $ sum_population <dbl> 19108, 15247, 16265, 19235, 18216, 21431…
## $ sum_lits <dbl> 6045, 5948, 5959, 7751, 7568, 8651, 8708…
## $ longueur_route <dbl> 313174.58, 247837.82, 284918.01, 300939.…
## $ longueur_pistes_cyclables <dbl> 28984.838, 24908.930, 25038.291, 16473.9…
## $ superficie_vegetation <dbl> 13220067, 8522079, 12884345, 16447697, 1…
## $ nombre_arrets <int> 184, 139, 166, 154, 131, 168, 166, 71, 1…
## $ nombre_parkings <dbl> 7486, 7019, 7021, 5358, 3710, 4729, 3572…
## $ nombre_commerces <int> 135, 126, 129, 145, 83, 96, 86, 26, 49, …
## $ nombre_loisirs <int> 60, 54, 58, 64, 44, 57, 58, 19, 35, 7, 2…
## $ nombre_restauration <int> 180, 173, 187, 216, 136, 157, 145, 52, 1…
## $ nombre_sports <int> 6, 5, 5, 6, 5, 5, 5, 3, 3, 1, 3, 3, 4, 4…
## $ nombre_ronds_points <int> 32, 31, 31, 33, 23, 34, 28, 11, 20, 4, 1…
## $ nombre_eleves <dbl> 1348, 965, 965, 773, 1098, 1098, 1098, 0…
## $ superficie_iso <dbl> 64804105, 42364290, 52754134, 57974148, …
## $ ZA <dbl> 51584037, 33842211, 39869790, 41526451, …
## $ passage_niveau <int> 12, 11, 15, 18, 19, 20, 21, 13, 18, 7, 1…
## $ sum_population_carreau_decoup <dbl> 14099.588, 12160.520, 13003.418, 13163.2…
## $ nombre_arrets_v2 <int> 48, 37, 44, 43, 35, 44, 42, 18, 34, 11, …
## $ nombre_sante <dbl> 39, 33, 34, 41, 30, 34, 33, 2, 11, 0, 11…
## $ geom <POINT [m]> POINT (474102.4 6914309), POINT (4…glimpse(data_car)## Rows: 32
## Columns: 13
## $ ID_number <dbl> 22801, 22811, 22821, 22831, 22841, 22851…
## $ sum_population_carreau_decoup <dbl> 0.7382998, 0.6225387, 0.6728592, 0.68239…
## $ nombre_eleves <dbl> 0.5359841, 0.3836978, 0.3836978, 0.30735…
## $ nombre_loisirs <dbl> 0.5698925, 0.5053763, 0.5483871, 0.61290…
## $ nombre_sante <dbl> 0.30000000, 0.25384615, 0.26153846, 0.31…
## $ nombre_commerces <dbl> 0.516, 0.480, 0.492, 0.556, 0.308, 0.360…
## $ nombre_restauration <dbl> 0.5271565, 0.5047923, 0.5495208, 0.64217…
## $ nombre_sports <dbl> 0.4166667, 0.3333333, 0.3333333, 0.41666…
## $ ZA <dbl> 0.6737561, 0.3184508, 0.4391616, 0.47233…
## $ passage_niveau <dbl> 0.3125, 0.2500, 0.5000, 0.6875, 0.7500, …
## $ total_sum_allegee <dbl> 4.590256, 3.652035, 4.180498, 4.692721, …
## $ geom <POINT [m]> POINT (474102.4 6914309), POINT (4…
## $ data_rennes_classes <int> 4, 3, 4, 4, 3, 4, 4, 2, 3, 1, 2, 2, 3, 2…