Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width = 5,
fig.height = 6
)
## ----mf_basemap, message=FALSE, warning=FALSE---------------------------------
library(mapsf)
# import the sample data set
mtq <- mf_get_mtq()
# set a theme
mf_theme("iceberg")
# plot a shadow
mf_shadow(mtq)
# plot municipalities
mf_map(mtq, type = "base", add = TRUE)
# layout
mf_layout(
title = "Martinique",
credits = paste0(
"Sources: IGN, 2018\n",
"mapsf ",
packageVersion("mapsf")
)
)
## ----mf_prop, message=FALSE, warning=FALSE------------------------------------
library(mapsf)
# import the sample data set
mtq <- mf_get_mtq()
# set a theme
mf_theme("darkula")
# plot a shadow
mf_shadow(mtq)
# plot municipalities
mf_map(mtq, add = TRUE)
# plot population
mf_map(
x = mtq,
var = "POP",
type = "prop",
inches = 0.25,
col = "brown4",
leg_pos = "topright",
leg_adj = c(0, -2),
leg_title = "Total population"
)
# layout
mf_layout(
title = "Population Distribution in Martinique",
credits = paste0(
"Sources: Insee and IGN, 2018\n",
"mapsf ",
packageVersion("mapsf")
)
)
## ----mf_map_c-----------------------------------------------------------------
library(mapsf)
# import the sample data set
mtq <- mf_get_mtq()
# population density (inhab./km2) using sf::st_area()
mtq$POPDENS <- 1e6 * mtq$POP / sf::st_area(mtq)
# set a theme
mf_theme("green")
# plot population density
mf_map(
x = mtq,
var = "POPDENS",
type = "choro",
breaks = "geom",
nbreaks = 5,
pal = "Greens",
border = "white",
lwd = 0.5,
leg_pos = "topright",
leg_title = "Population Density\n(people per km2)"
)
# layout
mf_layout(
title = "Population Distribution in Martinique",
credits = paste0(
"Sources: Insee and IGN, 2018\n",
"mapsf ",
packageVersion("mapsf")
)
)
## ----mf_map_t-----------------------------------------------------------------
library(mapsf)
# import the sample data set
mtq <- mf_get_mtq()
# set theme
mf_theme("dark")
# plot administrative status
mf_map(
x = mtq,
var = "STATUS",
type = "typo",
pal = c("aquamarine4", "yellow3", "wheat"),
lwd = .5,
val_order = c(
"Prefecture",
"Sub-prefecture",
"Simple municipality"
),
leg_pos = "topright",
leg_adj = c(0, 1),
leg_title = ""
)
# labels for a few municipalities
mf_label(
x = mtq[mtq$STATUS != "Simple municipality", ], var = "LIBGEO",
cex = 0.9, halo = TRUE, r = 0.15
)
# layout
mf_layout(
title = "Administrative Status",
credits = paste0(
"Sources: Insee and IGN, 2018\n",
"mapsf ",
packageVersion("mapsf")
)
)
## ----mf_map_pc, fig.width=5---------------------------------------------------
library(mapsf)
# import the sample data set
mtq <- mf_get_mtq()
# set theme
mf_theme("candy")
# Plot the municipalities and expand the map space on the right
mf_map(x = mtq, expandBB = c(0, 0, 0, .15))
# Plot symbols with choropleth coloration
mf_map(
x = mtq,
var = c("POP", "MED"),
type = "prop_choro",
border = "grey50",
lwd = 1,
leg_pos = c("topright"),
leg_title = c("Population", "Median Income\n(in euros)"),
breaks = "equal",
nbreaks = 4,
pal = "Greens",
leg_val_rnd = c(0, -2),
leg_frame = TRUE
)
# layout
mf_layout(
title = "Population & Wealth in Martinique, 2015",
credits = paste0(
"Sources: Insee and IGN, 2018\n",
"mapsf ",
packageVersion("mapsf")
),
frame = TRUE
)
## ----mf_map_pt, fig.width=5---------------------------------------------------
library(mapsf)
# import the sample data set
mtq <- mf_get_mtq()
# set theme
mf_theme("ink")
# plot the municipalities and expand the map space on the right
mf_map(x = mtq, expandBB = c(0, 0, 0, .15))
# plot symbols with choropleth coloration
mf_map(
x = mtq,
var = c("POP", "STATUS"),
type = "prop_typo",
symbol = "square",
border = "white",
lwd = .5,
leg_pos = "topright",
leg_title = c("Population", "Administrative\nStatus"),
val_order = c(
"Prefecture", "Sub-prefecture",
"Simple municipality"
)
)
# layout
mf_layout(
title = "Population Distribution in Martinique",
credits = paste0(
"Sources: Insee and IGN, 2018\n",
"mapsf ",
packageVersion("mapsf")
)
)
## ----mf_label-----------------------------------------------------------------
library(mapsf)
# import the sample data set
mtq <- mf_get_mtq()
# set theme
my_theme <- list(
name = "mytheme",
bg = "lightblue1",
fg = "darkseagreen4",
mar = c(0, 0, 0, 0),
tab = TRUE,
pos = "left",
inner = TRUE,
line = 1,
cex = .9,
font = 3
)
mf_theme(my_theme)
# plot municipalities
mf_map(mtq, col = "#e4e9de", border = "darkseagreen4")
# plot labels
mf_label(
x = mtq,
var = "LIBGEO",
col = "black",
cex = 0.7,
font = 4,
halo = TRUE,
bg = "white",
r = 0.1,
overlap = FALSE,
lines = FALSE
)
# layout
mf_layout(
title = "Municipalities of Martinique",
credits = paste0(
"Sources: Insee and IGN, 2018\n",
"mapsf ",
packageVersion("mapsf")
),
arrow = FALSE
)
# north arrow
mf_arrow(pos = "topright")
## ----mf_grad------------------------------------------------------------------
library(mapsf)
# import the sample data set
mtq <- mf_get_mtq()
# import the csv file embedded in mapsf
mob <- read.csv(system.file("csv/mob.csv", package = "mapsf"))
# Select links from Fort-de-France (97209))
mob_97209 <- mob[mob$i == 97209, ]
# create an sf object of links
mob_links <- mf_get_links(x = mtq, df = mob_97209)
# set theme
mf_theme("jsk")
# Plot the municipalities
mf_map(mtq)
# plot graduated links
mf_map(
x = mob_links,
var = "fij",
type = "grad",
breaks = c(100, 500, 1000, 4679.0),
lwd = c(1, 4, 8),
leg_pos = "topright",
leg_title = "Nb. of\nCommuters",
col = "red4",
leg_frame = TRUE
)
# map layout
mf_layout(
title = "Commuting to Fort-de-France",
credits = paste0(
"Sources: Insee and IGN, 2018\n",
"mapsf ",
packageVersion("mapsf")
),
arrow = FALSE
)
## ----echo = FALSE-------------------------------------------------------------
mf_theme("default")
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