您的地理位置数据

Question

我经常需要在R中创建地理热图。目前，我一直在我办公室计算机上的Tableau许可版本中执行此操作，这项工作非常出色。但是当我不在办公室时，我需要学习如何做到这一点。数据有时是保密的，因此我无法通过互联网使用Tableau。我看了，但找不到能产生我需要的结果的任何解决方案。

该数据包括印度贾坎德邦州的地区名称以及6至14岁的儿童人口数千人。在Tableau中，我只需要在“县”级别将DISTNAME列设置为“地理角色”，并从互联网（OpenStreetMap）中拉出州的地图以及区域边界，并生成这样的热图，这是结果如果可能的话，我期待R：

数据是：

geo_data <- structure(list(DISTNAME = c("BOKARO", "CHATRA", "DEOGHAR", "DHANBAD", 
"DUMKA", "GARHWA", "GIRIDIH", "GODDA", "GUMLA", "HAZARIBAGH", 
"JAMTARA", "KHUNTI", "KODARMA", "LATEHAR", "LOHARDAGA", "PAKUR", 
"PALAMU", "PASHCHIMI SINGHBHUM", "PURBI SINGHBHUM", "RAMGARH", 
"RANCHI", "SAHIBGANJ", "SARAIKELA-KHARSAWAN", "SIMDEGA"), POP = c(521.5, 
196.5, 323.8, 445.5, 123, 373.9, 357.6, 248.2, 212.4, 686.7, 
626.7, 383.6, 391.9, 141, 436.1, 454.6, 301.3, 325.5, 193.7, 
238.3, 208.7, 587.4, 130.1, 268)), .Names = c("DISTNAME", "POP"
), row.names = c(NA, 24L), class = "data.frame")

看起来像：

              DISTNAME   POP
1               BOKARO 521.5
2               CHATRA 196.5
3              DEOGHAR 323.8
4              DHANBAD 445.5
5                DUMKA 123.0
6               GARHWA 373.9
7              GIRIDIH 357.6
8                GODDA 248.2
9                GUMLA 212.4
10          HAZARIBAGH 686.7
11             JAMTARA 626.7
12              KHUNTI 383.6
13             KODARMA 391.9
14             LATEHAR 141.0
15           LOHARDAGA 436.1
16               PAKUR 454.6
17              PALAMU 301.3
18 PASHCHIMI SINGHBHUM 325.5
19     PURBI SINGHBHUM 193.7
20             RAMGARH 238.3
21              RANCHI 208.7
22           SAHIBGANJ 587.4
23 SARAIKELA-KHARSAWAN 130.1
24             SIMDEGA 268.0

Answer 1

您需要SHP文件，可以使用exports.config = { directConnect: true, useAllAngular2AppRoots: true, specs: ['./**/*.spec.js'], baseUrl: 'http://10.209.1.38:9090', framework: 'jasmine2', capabilites: { 'browserName': 'chrome' }, jasmineNodeOpts: { showColors: true, defaultTimeoutInterval: 60000 }, onPrepare: function () { browser.driver.manage().window().maximize(); browser.get('/'); browser.sleep(500); } };找到该文件。完整的工作代码：

getData()

您的地理位置数据

library(tidyverse)
library(broom)
library(rgdal)

获取地图

geo_data <- structure(list(DISTNAME = c("BOKARO", "CHATRA", "DEOGHAR", "DHANBAD", "DUMKA", "GARHWA", "GIRIDIH", "GODDA", "GUMLA", "HAZARIBAGH", "JAMTARA", "KHUNTI", "KODARMA", "LATEHAR", "LOHARDAGA", "PAKUR", "PALAMU", "PASHCHIMI SINGHBHUM", "PURBI SINGHBHUM", "RAMGARH", "RANCHI", "SAHIBGANJ", "SARAIKELA-KHARSAWAN", "SIMDEGA"),
                       POP = c(521.5, 196.5, 323.8, 445.5, 123, 373.9, 357.6, 248.2, 212.4, 686.7, 626.7, 383.6, 391.9, 141, 436.1, 454.6, 301.3, 325.5, 193.7, 238.3, 208.7, 587.4, 130.1, 268)),
                  .Names = c("DISTNAME", "POP"),
                  row.names = c(NA, 24L),
                  class = "data.frame")

在geo_data中

id降低

library(raster)
IN2 <- getData('GADM', country='IND', level=2)
IN2 <- spTransform(IN2, CRS("+init=epsg:4326"))
IN2_map <- tidy(IN2, region = "NAME_2")

Answer 2

在下面的解决方案中，我使用了从http://projects.datameet.org/maps/districts/下载的地图shapefile文件

编辑：稍后我还尝试了从http://gadm.org/country中提取的Jharkhand地图，该地图显示了地区边界的细微差别。它与互联网上可用的其他政治地图更好地匹配。

这是我的解决方案：

library(tmap)
library(tmaptools)

geo_data <- data.frame(
  DISTNAME = c("BOKARO", "CHATRA", "DEOGHAR", "DHANBAD", "DUMKA", "GARHWA", "GIRIDIH", "GODDA", "GUMLA", "HAZARIBAGH", "JAMTARA", "KHUNTI", "KODARMA", "LATEHAR", "LOHARDAGA", "PAKUR", "PALAMU", "PASHCHIMI SINGHBHUM", "PURBI SINGHBHUM", "RAMGARH", "RANCHI", "SAHIBGANJ", "SARAIKELA-KHARSAWAN", "SIMDEGA"),
  POP = c(521.5, 196.5, 323.8, 445.5, 123, 373.9, 357.6, 248.2, 212.4, 686.7, 626.7, 383.6, 391.9, 141, 436.1, 454.6, 301.3, 325.5, 193.7, 238.3, 208.7, 587.4, 130.1, 268))

# the path to shape file
shp_file <- "H:/Mapping/maps-master/Districts/Census_2011/2011_Dist.shp"

india <- read_shape(shp_file, as.sf = TRUE, stringsAsFactors = FALSE)
india$DISTRICT <- toupper(india$DISTRICT)

jharkhand <- india[india$ST_NM =="Jharkhand", ]

jharkhand_pop <- merge(x = jharkhand,
                       y = geo_data,
                       by.x = "DISTRICT",
                       by.y = "DISTNAME")

#tmap_mode(mode = "plot") # static
tmap_mode(mode = "view") # interactive

qtm(jharkhand_pop, fill = "POP",
    text = "DISTRICT",
    text.size=.9)

静态地图（plot模式）非常好，但交互式地图（view模式）非常棒。它提供了从互联网上的三个不同来源提取额外地图信息的选项。

非常感谢tmap和tmaptools个软件包的创建者。这种方法远远优于许多相对较长和笨拙的解决方案，可以在互联网上找到。

如果我们想要更多自定义：

tm_shape(jharkhand_pop) +
  tm_polygons() +
  tm_shape(jharkhand_pop) +
  tm_borders() +
  tm_fill("POP",
          palette = get_brewer_pal("YlOrRd", n = 20),
          n = 20,
          legend.show = F,
          style = "order") + # "cont" or "order" for continuous variable
  tm_text("DISTRICT", size = .7, ymod = .1) +
  tm_shape(jharkhand_pop) +
  tm_text("POP", size = .7, ymod = -.2)

我们在plot模式下获得以下内容：

地理县级热图

2 个答案:

您的地理位置数据

获取地图

id降低