,这里有一个csv,其中包含我要绘制的变量以及需要在地图上显示的点的坐标。我的最终目标是创建一个包含多边形的地图,并且在每个多边形内部应根据坐标指定点。每个多边形都应根据2019年的学生人数(学生)进行着色。可接受任何替代方法
我相信下面的第一个代码块是正确的:
library(sf)
library(tidyverse)
library(data.table)
library(tigris)
library(leaflet)
library(mapview)
options(tigris_use_cache = TRUE)
# To keep enough digits on coords
options(digits = 11)
#coordinate reference system (long-lat system)
cr_sys = 4326
# Shp file for hs boundaries (constitutes overall district bounds)
hs_bounds <- st_read("C:/Users/makis/Documents/school/TPS_schools.shp")
# Read the feature class
#fc <- readOGR(dsn=fgdb )
#fc <- spTransform(fc, CRS("+proj=longlat +datum=WGS84 +no_defs"))
# Convert hs_bounds into longlat coord system
hs_bounds <- hs_bounds %>%
st_transform(4326)
tmp <- list.files(pattern = "school_report_data_fake.csv")
raw_master <- lapply(tmp,
function(x) read_csv(x,guess_max = 5000)) %>%
rbindlist(., fill = TRUE)
# r blocks in tps
tps_blocks <- blocks(state = "OK") %>%
st_as_sf() %>%
st_transform(crs = 4326) %>%
st_intersection(hs_bounds)
tps_bgs <- block_groups(state = "OK") %>%
st_as_sf() %>%
st_transform(crs = 4326) %>%
st_intersection(hs_bounds)
mapview(hs_bounds)
# Display all tps block groups on interactive map
tps_blocks_map <- mapview(tps_bgs) %>%
addFeatures(., hs_bounds)
# convert to df and remove geometry bc its a list col
tps_blocks_df <- tps_blocks %>%
as.data.frame() %>%
select(-geometry)
# Export blocks in tps. GEOID10 is the unique identifier for the block
write_csv(tps_blocks_df, path = "C:/Users/makis/Documents/school/tps_blocks.csv")
我在这里也尝试包含学生数据,但我在一个零数据的数据帧中得出结论
#r students by geography
student_geos <- raw_master %>%
#filter for students active in a given year
filter(year == 2019) %>%
# filter(row_number() %in% sample(length(year), 20000)) %>%
# Parse lat/long. I believe that I should do something here with the lat and long
#and some variable of the csv like the geocode variable that is used here
#a similar should be present in my csv file as well
#mutate(lat = as.numeric(str_extract(geocode, "[0-9]+.[0-9]+"))) %>%
#mutate(lon = as.numeric(str_extract(geocode, "-[0-9]+.[0-9]+"))) %>%
# Please don't ask me why this rowwise is necessary
rowwise() %>%
# Create sf point for each set of coords
mutate(pt = st_sfc(st_point(x = c(lon, lat)), crs = 4326)) %>%
# Turn df into sfc then take intersection of pts and blocks
st_as_sf() %>%
st_intersection(tps_blocks)
# convert to df and remove geometry bc its a list col
student_geos_df <- student_geos %>%
as.data.frame() %>%
select(-pt)
如果以上所有内容均正确,我应该执行以下操作:
# enrollment by tract
tract_enrol <- student_geos %>%
as.data.frame() %>%
group_by(year, TRACTCE10) %>%
summarize(enrollment = n())
# convert list of tracts into sfc
tracts <- tracts(state = "OK",
county = c("Tulsa", "Osage", "Wagoner", "Creek"),
year = 2010) %>%
st_as_sf() %>%
as.data.frame() %>%
#I guess student id instead of TRACTE10 here
inner_join(tract_enrol, by = "TRACTCE10") %>%
st_as_sf()
mapview(tracts, zcol = "enrollment", legend = TRUE)
答案 0 :(得分:1)
您的文件仍未下载。
我可以为您提供使用ggplot2制作地图的通用指南。这将绘制多边形和点。
您需要使用fortify()
修改Spatial_DataFrames,以使其成为ggplot2可以使用的格式。
library(ggplot2)
hs_b2 <- fortify(hs_bounds) #or instead of "hs_bounds", "tracts" or whatever your polygon
#is called. If that doesn't work you need "<-as.data.frame()".
#Make sure the output has a separate column for x and y.
#repeat for the points (student) object.
student_2 <- fortify(<studentpointsobject>)
ggplot(data=<student_2>, aes(x=x,y=y)) +
geom_polygon(data=hs_b2, aes(x=long, y=lat, group=group) , #this will create the polygon
colour="grey90", alpha=1, #one of your color options for polygons
fill="grey40") + #one of your color options for polygons
theme(axis.ticks.y = element_blank(),axis.text.y = element_blank(), # get rid of x ticks/text
axis.ticks.x = element_blank(),axis.text.x = element_blank()) + # get rid of y ticks/text
geom_point(aes(color="grey20")) #to get the points drawn. mess with "fill" and "color"
您可以在aes()中使用“颜色”或“填充”来自定义图。