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GeoViz2018_R_ggplot.R
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GeoViz2018_R_ggplot.R
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## ---- echo = FALSE, message = FALSE--------------------------------------
library(tidyverse)
## ---- fig.show='hide', message = FALSE-----------------------------------
library(ggplot2) # ou library(tidyverse)
df_dmr_spatialise <- readRDS(file = "dans_ma_rue_clean.RDS")
ggplot(data = df_dmr_spatialise)
## ----plot-point, eval=FALSE----------------------------------------------
## pointData <- df_dmr_spatialise %>%
## filter(
## TYPE == "Problème sur un chantier"
## )
##
## ggplot(pointData) +
## geom_point(aes(x = Long, #<<
## y = Lat, #<<
## color = CODE_POSTAL)) #<<
## ----plot-label-out, ref.label="plot-point", echo=FALSE------------------
## ----plot-size, eval=FALSE-----------------------------------------------
## pointData <- df_dmr_spatialise %>%
## filter(
## TYPE == "Problème sur un chantier"
## )
##
## ggplot(pointData) +
## geom_point(aes(x = Long,
## y = Lat,
## color = CODE_POSTAL),
## size = 3,#<<
## alpha = .2)#<<
## ----plot-label-out-2, ref.label="plot-size", echo=FALSE-----------------
## ----plot-scale, eval=FALSE----------------------------------------------
## colData <- df_dmr_spatialise %>%
## filter(
## TYPE == "Problème sur un chantier"
## ) %>%
## group_by(CODE_POSTAL,
## ANNEE_DECLARATION) %>%
## summarise(NbProblemes = n())
##
## ggplot(colData) +
## geom_col(aes(x = CODE_POSTAL,
## y = NbProblemes,
## fill = ANNEE_DECLARATION,#<<
## group = ANNEE_DECLARATION),#<<
## position = "dodge") #<<
## ----plot-label-out-3, ref.label="plot-scale", echo=FALSE----------------
## ----plot-scale2, eval=FALSE---------------------------------------------
## colData <- df_dmr_spatialise %>%
## filter(
## TYPE == "Problème sur un chantier"
## ) %>%
## group_by(CODE_POSTAL,
## ANNEE_DECLARATION) %>%
## summarise(NbProblemes = n())
##
## ggplot(colData) +
## geom_col(aes(x = CODE_POSTAL,
## y = NbProblemes,
## fill = ANNEE_DECLARATION,
## group = ANNEE_DECLARATION),
## position = "dodge") +
## scale_y_log10() #<<
## ----plot-label-out-4, ref.label="plot-scale2", echo=FALSE---------------
## ----plot-scale3, eval=FALSE---------------------------------------------
## colData <- df_dmr_spatialise %>%
## filter(
## TYPE == "Problème sur un chantier"
## ) %>%
## group_by(CODE_POSTAL,
## ANNEE_DECLARATION) %>%
## summarise(NbProblemes = n())
##
## ggplot(colData) +
## geom_col(aes(x = CODE_POSTAL,
## y = NbProblemes,
## fill = as.character(ANNEE_DECLARATION),
## group = as.character(ANNEE_DECLARATION)),
## position = "dodge") +
## scale_y_log10() + #<<
## scale_fill_brewer(palette = "Greens", direction = -1) #<<
## ----plot-label-out-5, ref.label="plot-scale3", echo=FALSE---------------
## ------------------------------------------------------------------------
pointData <- df_dmr_spatialise %>% filter( TYPE == "Problème sur un chantier")
## ------------------------------------------------------------------------
ggplot(pointData) +
geom_point(aes(x = Long, y = Lat,
color = CODE_POSTAL),
size = 3, alpha = .2) +
coord_fixed(ratio = 1) # On fixe 1x = 1y #<<
## ---- fig.show='hold'----------------------------------------------------
ggplot(pointData) +
geom_point(aes(x = Long, y = Lat,
color = CODE_POSTAL),
size = 3, alpha = .2) +
coord_map(projection = "mercator") #<<
# ratio x/y selon la projection de Mercator #<<
## ---- fig.height=2.75----------------------------------------------------
ggplot(pointData) +
geom_point(aes(x = Long, y = Lat, color = CODE_POSTAL), size = 3, alpha = .2) +
coord_map(projection = "mercator") +
labs(title = 'Incidents déclarés à Paris entre 2012 et 2018',#<<
subtitle = 'Incidents de type "Problème sur un chantier"',#<<
caption = 'Sources : Données "Dans ma Rue", Paris OpenData, 2018',#<<
x = "Longitude", y = "Latitude")#<<
## ---- fig.height=3.75----------------------------------------------------
ggplot(pointData) +
geom_point(aes(x = Long, y = Lat, color = CODE_POSTAL), size = 3, alpha = .2) +
coord_map(projection = "mercator") +
labs(title = 'Incidents déclarés à Paris entre 2012 et 2018',
subtitle = 'Incidents de type "Problème sur un chantier"',
caption = 'Sources : Données "Dans ma Rue", Paris OpenData, 2018',
x = "Longitude", y = "Latitude") +
scale_color_discrete(guide = FALSE) + #<<
scale_x_continuous(labels = NULL, breaks = NULL, minor_breaks = NULL) + #<<
scale_y_continuous(labels = NULL, breaks = NULL, minor_breaks = NULL) #<<
## ---- eval = FALSE, fig.height=3, fig.width=12---------------------------
## ggplot(pointData) +
## geom_point(aes(x = Long, y = Lat, color = CODE_POSTAL), size = 2, alpha = .2) +
## coord_map(projection = "mercator") +
## labs(title = 'Incidents déclarés à Paris entre 2012 et 2018',
## subtitle = 'Incidents de type "Problème sur un chantier"',
## caption = 'Sources : Données "Dans ma Rue", Paris OpenData, 2018',
## x = "Longitude", y = "Latitude") +
## scale_color_discrete(guide = FALSE) +
## scale_x_continuous(labels = NULL, breaks = NULL, minor_breaks = NULL) +
## scale_y_continuous(labels = NULL, breaks = NULL, minor_breaks = NULL) +
## facet_wrap(~ANNEE_DECLARATION, nrow = 1) #<<
## ---- fig.height=3, fig.width=12, echo = FALSE---------------------------
ggplot(pointData) +
geom_point(aes(x = Long, y = Lat, color = CODE_POSTAL), size = 2, alpha = .2) +
coord_map(projection = "mercator") +
labs(title = 'Incidents déclarés à Paris entre 2012 et 2018',
subtitle = 'Incidents de type "Problème sur un chantier"',
caption = 'Sources : Données "Dans ma Rue", Paris OpenData, 2018',
x = "Longitude", y = "Latitude") +
scale_color_discrete(guide = FALSE) +
scale_x_continuous(labels = NULL, breaks = NULL, minor_breaks = NULL) +
scale_y_continuous(labels = NULL, breaks = NULL, minor_breaks = NULL) +
facet_wrap(~ANNEE_DECLARATION, nrow = 1) #<<
## ---- fig.height=3, fig.width=12, eval = FALSE---------------------------
## ggplot(pointData %>% filter(!is.na(SOUSTYPE))) +
## geom_point(aes(x = Long, y = Lat, color = CODE_POSTAL), size = 2, alpha = .2) +
## coord_map(projection = "mercator") +
## labs(title = 'Incidents déclarés à Paris entre 2012 et 2018',
## subtitle = 'Incidents de type "Problème sur un chantier"',
## caption = 'Sources : Données "Dans ma Rue", Paris OpenData, 2018',
## x = "Longitude", y = "Latitude") +
## scale_color_discrete(guide = FALSE) +
## scale_x_continuous(labels = NULL, breaks = NULL, minor_breaks = NULL) +
## scale_y_continuous(labels = NULL, breaks = NULL, minor_breaks = NULL) +
## facet_grid(SOUSTYPE~ANNEE_DECLARATION) #<<
## ---- fig.height=5, fig.width=12, echo = FALSE---------------------------
ggplot(pointData %>% filter(!is.na(SOUSTYPE))) +
geom_point(aes(x = Long, y = Lat, color = CODE_POSTAL), size = 2, alpha = .2) +
coord_map(projection = "mercator") +
labs(title = 'Incidents déclarés à Paris entre 2012 et 2018',
subtitle = 'Incidents de type "Problème sur un chantier"',
caption = 'Sources : Données "Dans ma Rue", Paris OpenData, 2018',
x = "Longitude", y = "Latitude") +
scale_color_discrete(guide = FALSE) +
scale_x_continuous(labels = NULL, breaks = NULL, minor_breaks = NULL) +
scale_y_continuous(labels = NULL, breaks = NULL, minor_breaks = NULL) +
facet_grid(SOUSTYPE~ANNEE_DECLARATION) #<<
## ------------------------------------------------------------------------
maCarte <- ggplot(pointData) +
geom_point(aes(x = Long, y = Lat)) +
coord_map(projection = "mercator")
maCarte
## ------------------------------------------------------------------------
maCarte +
geom_density2d(aes(x = Long, y = Lat)) #<<
## ------------------------------------------------------------------------
ggplot(pointData) +
aes(x = Long, y = Lat) +
geom_point(colour = "white", alpha = .4) + #<<
stat_density_2d(aes(fill = stat(level)), #<<
geom = "polygon") + #<<
coord_map(projection = "mercator")
## ------------------------------------------------------------------------
ggplot(pointData) +
aes(x = Long, y = Lat) +
stat_density_2d(aes(fill = stat(level)), #<<
geom = "polygon") + #<<
geom_point(colour = "white", alpha = .4) + #<<
coord_map(projection = "mercator")
## ---- eval = TRUE--------------------------------------------------------
library(patchwork) # devtools::install_github("thomasp85/patchwork")
## ---- fig.height = 3-----------------------------------------------------
carteData <- df_dmr_spatialise %>%
filter(TYPE %in% c("Propreté", "Voirie et déplacements", "Éclairage / Électricité")) %>%
filter(ANNEE_DECLARATION >= 2015) %>%
mutate(TRIMESTRE = paste(ANNEE_DECLARATION, TRIMESTRE_DECLARATION, sep="-")) %>%
arrange(TRIMESTRE, TYPE)
maCarte <- ggplot(carteData) +
geom_point(aes(Long, Lat, colour = TYPE), size = .5, alpha = .3) +
facet_grid(ANNEE_DECLARATION~TYPE) +
coord_map(projection = "mercator") +
scale_colour_discrete(guide = FALSE)
maCarte
## ---- fig.height = 3----------------------------------------------------
evolData <- carteData %>%
group_by(TRIMESTRE, TYPE) %>%
summarise(NbIncidents = n())
evolNombre <- ggplot(evolData) +
geom_line(aes(TRIMESTRE, NbIncidents, colour = TYPE, group = TYPE), size = 2) +
facet_wrap(~TYPE, nrow = 1) +
scale_colour_discrete(guide = FALSE)
evolNombre
## ---- fig.height = 3-----------------------------------------------------
arrdtData <- carteData %>%
group_by(ANNEE_DECLARATION, CODE_POSTAL) %>%
summarise(NbIncidents = n()) %>%
ungroup() %>%
mutate(ANNEE_DECLARATION = as.character(ANNEE_DECLARATION))
evolArrdt <- ggplot(arrdtData) +
geom_col(aes(CODE_POSTAL, NbIncidents, fill = ANNEE_DECLARATION), position = "dodge") +
scale_fill_viridis_d() +
theme(legend.position="bottom",
axis.text.x = element_text(angle = 45, hjust = 1))
evolArrdt
## ----fig.width=13, fig.height=7------------------------------------------
(maCarte | (evolNombre / evolArrdt)) #<<