如何在R Studio中根据从XML提取的数据帧创建Choropleth映射

Question

(totally new to R) I have downloaded an XML file to use in R to create a choropleth map from the data. I am using US flu data. From my research I understand that I needed to make that XML file a data frame for R to read. So I have done that. When I view my data frame I get all the XML formatting with it. The question I have is how do I take the information that I need and extract it to create a map? At this point I am getting errors on even plotting the data. I have looked high and low for this information and I haven't found it as of yet.

 setwd("C:/Users/Steven/Downloads/Map_Final")
> library (XML)
> library(ggplot2)
> library(maps)
> library(plyr)
> library(mapproj)
> map('state')
> 
> xmlfile=xmlParse("flu.xml")
> 
> class(xmlfile)
[1] "XMLInternalDocument" "XMLAbstractDocument"
> ggplot(xmlfile)
Error: ggplot2 doesn't know how to deal with data of class XMLInternalDocumentXMLAbstractDocument
> xmltop = xmlRoot(xmlfile) #gives content of root
> 
> class(xmltop)#"XMLInternalElementNode" "XMLInternalNode" "XMLAbstractNode"
[1] "XMLInternalElementNode" "XMLInternalNode"        "XMLAbstractNode"       
> 
> xmlName(xmltop) #give name of node, PubmedArticleSet
[1] "timeperiod"
> 
> xmlSize(xmltop) #how many children in node, 19
[1] 54
> 
> xmlName(xmltop[[1]]) #name of root's children
[1] "state"
> 
> xmltop[[1]]
<state>
  <abbrev>ME</abbrev>
  <color>No Activity</color>
  <label>No Activity</label>
</state> 
> 
> xmltop[[2]]
<state>
  <abbrev>NH</abbrev>
  <color>Local Activity</color>
  <label>Local Activity</label>
</state> 
> 
> ggplot(xmltop)
Error: ggplot2 doesn't know how to deal with data of class XMLInternalElementNodeXMLInternalNodeXMLAbstractNode
> xmltop[[2]]
<state>
  <abbrev>NH</abbrev>
  <color>Local Activity</color>
  <label>Local Activity</label>
</state> 
> 
> xmltop[[2]]
<state>
  <abbrev>NH</abbrev>
  <color>Local Activity</color>
  <label>Local Activity</label>
</state> 
> 
> birdflu=ldply(xmlToList("flu.xml"), data.frame)
> ggplot(birdflu)
Error: No layers in plot
> View(birdflu)

XML File:

<timeperiod number="40" year="2014" subtitle="Week Ending October 11, 2014- Week 40">
<state>
<abbrev>ME</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>NH</abbrev>
<color>Local Activity</color>
<label>Local Activity</label>
</state>
<state>
<abbrev>VT</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>MA</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>RI</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>CT</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>NY</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>NJ</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>PR</abbrev>
<color>Regional</color>
<label>Regional</label>
</state>
<state>
<abbrev>VI</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>PA</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>DE</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>MD</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>DC</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>VA</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>WV</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>NC</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>SC</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>GA</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>FL</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>KY</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>TN</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>AL</abbrev>
<color>Local Activity</color>
<label>Local Activity</label>
</state>
<state>
<abbrev>MS</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>OH</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>IN</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>IL</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>MI</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>WI</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>MN</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>AR</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>LA</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>OK</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>TX</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>NM</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>IA</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>MO</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>NE</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>KS</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>ND</abbrev>
<color>Local Activity</color>
<label>Local Activity</label>
</state>
<state>
<abbrev>SD</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>MT</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>WY</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>CO</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>UT</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>AZ</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>NV</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>CA</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>HI</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>GU</abbrev>
<color>Widespread</color>
<label>Widespread</label>
</state>
<state>
<abbrev>ID</abbrev>
<color>No Activity</color>
<label>No Activity</label>
</state>
<state>
<abbrev>WA</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>OR</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
<state>
<abbrev>AK</abbrev>
<color>Sporadic</color>
<label>Sporadic</label>
</state>
</timeperiod>

Answer 1

Basic, annotated example below using built-in (ggplot) US map data. If you need the territories (which have more outbreaks it seems) you'll need to look at the other SO examples that show that (of which there are many).

library(xml2)
library(dplyr)
library(ggplot2)

# read in the XML file

flu <- read_xml("flu.xml")

# get data from it into data frame

flu_dat <- data_frame(id=flu %>% xml_find_all("//state/abbrev") %>% xml_text,
                      value=flu %>% xml_find_all("//state/color") %>% xml_text)

# for built-in (ggplot) map data we need names, not abbreviations

state_name <- state.name
names(state_name) <- state.abb

us <- map_data("state")

# convert abbrev to name; ensure ordered factor, filter by what the
# built-in plot has. NOTE that if you need the territories, you'll
# need to use another base map of which there are many examples on SO

flu_dat %>% 
  mutate(id=state_name[id],
         Level=factor(value, 
                      levels=c("No Activity", "Local Activity", 
                               "Sporadic", "Regional", "Widespread"),
                      ordered=TRUE)) %>% 
  filter(id %in% unique(us$region))-> flu_dat

us <- fortify(us, region="region")

# for theme_map convenience function
devtools::source_gist("33baa3a79c5cfef0f6df")

gg <- ggplot()
# plot outlines
gg <- gg + geom_map(data=us, map=us,
                    aes(x=long, y=lat, map_id=region, group=group),
                    fill="#ffffff", color="#7f7f7f", size=0.25)
# plot fills based on flu data
gg <- gg + geom_map(data=flu_dat, map=us,
                    aes(fill=Level, map_id=id),
                    color="#7f7f7f", size=0.25)
# manual fill scale showing all possible values on legend
gg <- gg + scale_fill_manual(values=c("#f2f0f7", "#dadaeb", "#bcbddc", 
                                      "#9e9ac8", "#756bb1"), drop=FALSE)
# a proper US projection
gg <- gg + coord_map("albers", lat0=39, lat1=45)
gg <- gg + theme_map()
gg <- gg + theme(legend.position="right")
gg