地图，ggplot2，按状态填充缺少地图上的某些区域 [英] Maps, ggplot2, fill by state is missing certain areas on the map
问题描述
我正在使用 maps 和 ggplot2 来可视化每个州不同年份的特定犯罪数量.我正在使用的数据集由 FBI 制作，可以从他们的网站或从 here(如果您不想下载数据集，我不怪您，但是复制并粘贴到这个问题中太大了，并且包含一小部分数据集不会帮助，因为没有足够的信息来重新创建图表).
I am working with maps and ggplot2 to visualize the number of certain crimes in each state for different years. The data set that I am working with was produced by the FBI and can be downloaded from their site or from here (if you don't want to download the dataset I don't blame you, but it is way too big to copy and paste into this question, and including a fraction of the data set wouldn't help, as there wouldn't be enough information to recreate the graph).
问题比描述更容易看到.
The problem is easier seen than described.
正如您所看到的，加利福尼亚州和其他几个州都缺少很大一部分.这是生成此图的代码:
As you can see California is missing a large chunk as well as a few other states. Here is the code that produced this plot:
# load libraries
library(maps)
library(ggplot2)
# load data
fbi <- read.csv("http://www.hofroe.net/stat579/crimes-2012.csv")
fbi <- subset(fbi, state != "United States")
states <- map_data("state")
# merge data sets by region
fbi$region <- tolower(fbi$state)
fbimap <- merge(fbi, states, by="region")
# plot robbery numbers by state for year 2012
fbimap12 <- subset(fbimap, Year == 2012)
qplot(long, lat, geom="polygon", data=fbimap12,
facets=~Year, fill=Robbery, group=group)
states 数据如下所示:
long lat group order region subregion
1 -87.46201 30.38968 1 1 alabama <NA>
2 -87.48493 30.37249 1 2 alabama <NA>
3 -87.52503 30.37249 1 3 alabama <NA>
4 -87.53076 30.33239 1 4 alabama <NA>
5 -87.57087 30.32665 1 5 alabama <NA>
6 -87.58806 30.32665 1 6 alabama <NA>
这就是 fbi 数据的样子:
And this is what the fbi data looks like:
Year Population Violent Property Murder Forcible.Rape Robbery
1 1960 3266740 6097 33823 406 281 898
2 1961 3302000 5564 32541 427 252 630
3 1962 3358000 5283 35829 316 218 754
4 1963 3347000 6115 38521 340 192 828
5 1964 3407000 7260 46290 316 397 992
6 1965 3462000 6916 48215 395 367 992
Aggravated.Assault Burglary Larceny.Theft Vehicle.Theft abbr state region
1 4512 11626 19344 2853 AL Alabama alabama
2 4255 11205 18801 2535 AL Alabama alabama
3 3995 11722 21306 2801 AL Alabama alabama
4 4755 12614 22874 3033 AL Alabama alabama
5 5555 15898 26713 3679 AL Alabama alabama
6 5162 16398 28115 3702 AL Alabama alabama
然后我沿着 region 合并了这两个集合.我试图绘制的子集是
I then merged the two sets along region. The subset I am trying to plot is
region Year Robbery long lat group
8283 alabama 2012 5020 -87.46201 30.38968 1
8284 alabama 2012 5020 -87.48493 30.37249 1
8285 alabama 2012 5020 -87.95475 30.24644 1
8286 alabama 2012 5020 -88.00632 30.24071 1
8287 alabama 2012 5020 -88.01778 30.25217 1
8288 alabama 2012 5020 -87.52503 30.37249 1
... ... ... ...
关于如何在没有那些丑陋的缺失点的情况下创建这个情节的任何想法?
Any ideas on how I can create this plot without those ugly missing spots?
推荐答案
我玩过你的代码.我可以说的一件事是，当您使用 merge 时，发生了一些事情.我使用 geom_path 绘制了州地图，并确认原始地图数据中不存在几条奇怪的线条.然后，我通过使用 merge 和 inner_join 进一步调查了这个案例.merge 和 inner_join 在这里做同样的工作.但是，我发现了不同之处.当我使用 merge 时，顺序改变了；数字的顺序不正确.inner_join 不是这种情况.您将在下面看到一些与加利福尼亚有关的数据.你的做法是对的.但是 merge 不知何故对您不利.不过，我不确定为什么该函数更改了顺序.
I played with your code. One thing I can tell is that when you used merge something happened. I drew states map using geom_path and confirmed that there were a couple of weird lines which do not exist in the original map data. I, then, further investigated this case by playing with merge and inner_join. merge and inner_join are doing the same job here. However, I found a difference. When I used merge, order changed; the numbers were not in the right sequence. This was not the case with inner_join. You will see a bit of data with California below. Your approach was right. But merge somehow did not work in your favour. I am not sure why the function changed order, though.
library(dplyr)
### Call US map polygon
states <- map_data("state")
### Get crime data
fbi <- read.csv("http://www.hofroe.net/stat579/crimes-2012.csv")
fbi <- subset(fbi, state != "United States")
fbi$state <- tolower(fbi$state)
### Check if both files have identical state names: The answer is NO
### states$region does not have Alaska, Hawaii, and Washington D.C.
### fbi$state does not have District of Columbia.
setdiff(fbi$state, states$region)
#[1] "alaska" "hawaii" "washington d. c."
setdiff(states$region, fbi$state)
#[1] "district of columbia"
### Select data for 2012 and choose two columns (i.e., state and Robbery)
fbi2 <- fbi %>%
filter(Year == 2012) %>%
select(state, Robbery)
现在我用 merge 和 inner_join 创建了两个数据框.
Now I created two data frames with merge and inner_join.
### Create two data frames with merge and inner_join
ana <- merge(fbi2, states, by.x = "state", by.y = "region")
bob <- inner_join(fbi2, states, by = c("state" ="region"))
ana %>%
filter(state == "california") %>%
slice(1:5)
# state Robbery long lat group order subregion
#1 california 56521 -119.8685 38.90956 4 676 <NA>
#2 california 56521 -119.5706 38.69757 4 677 <NA>
#3 california 56521 -119.3299 38.53141 4 678 <NA>
#4 california 56521 -120.0060 42.00927 4 667 <NA>
#5 california 56521 -120.0060 41.20139 4 668 <NA>
bob %>%
filter(state == "california") %>%
slice(1:5)
# state Robbery long lat group order subregion
#1 california 56521 -120.0060 42.00927 4 667 <NA>
#2 california 56521 -120.0060 41.20139 4 668 <NA>
#3 california 56521 -120.0060 39.70024 4 669 <NA>
#4 california 56521 -119.9946 39.44241 4 670 <NA>
#5 california 56521 -120.0060 39.31636 4 671 <NA>
ggplot(data = bob, aes(x = long, y = lat, fill = Robbery, group = group)) +
geom_polygon()
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