1

我有每个州的基于位置的响应时间数据。我希望能够创建一个地图类型的热图：

有我的df：

structure(list(DATE_TIME = structure(c(1369419660, 1369419720, 
1369419720, 1369419780, 1369419780, 1369419840, 1369419840, 1369419900, 
1369419960, 1369419960, 1369419960, 1369420020, 1369420020, 1369420020, 
1369420020, 1369420080, 1369420080, 1369420080, 1369420080, 1369420140, 
1369420140, 1369420140, 1369420140, 1369420200, 1369420200, 1369420260, 
1369420260, 1369420260, 1369420260, 1369420260), class = c("POSIXct", 
"POSIXt"), tzone = ""), SITE = c("Logon to My Accounts", "Logon to My Accounts", 
"Logon to My Accounts", "Logon to My Accounts", "Logon to My Accounts", 
"Logon to My Accounts", "Logon to My Accounts", "Logon to My Accounts", 
"Logon to My Accounts", "Logon to My Accounts", "Logon to My Accounts", 
"Logon to My Accounts", "Logon to My Accounts", "Logon to My Accounts", 
"Logon to My Accounts", "Logon to My Accounts", "Logon to My Accounts", 
"Logon to My Accounts", "Logon to My Accounts", "Logon to My Accounts", 
"Logon to My Accounts", "Logon to My Accounts", "Logon to My Accounts", 
"Logon to My Accounts", "Logon to My Accounts", "Logon to My Accounts", 
"Logon to My Accounts", "Logon to My Accounts", "Logon to My Accounts", 
"Logon to My Accounts"), RESPONSE_TIME = c(7.069, 7.056, 11.535, 
7.33, 9.566, 5.21, 6.483, 6.652, 8.222, 9.368, 10.055, 6.301, 
6.33, 7.802, 10.132, 6.241, 6.997, 7.499, 7.823, 6.173, 6.912, 
7.979, 10.128, 7.072, 7.65, 6.048, 7.681, 8.08, 8.272, 9.583), 
    AVAIL_PERCENT = c(100L, 100L, 100L, 100L, 100L, 100L, 100L, 
    100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 
    100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 
    100L, 100L, 100L), AGENT = c(45869L, 45540L, 45672L, 45036L, 
    45421L, 42627L, 44981L, 42432L, 45869L, 45693L, 42108L, 40522L, 
    40521L, 45540L, 45672L, 40517L, 45036L, 45421L, 40511L, 42627L, 
    44981L, 40370L, 40369L, 40368L, 42432L, 40282L, 45693L, 42108L, 
    40296L, 45869L), LOCATION = c("seattle", "hartford", "houston", 
    "san diego", "montreal", "new york", "philadelphia", "chicago", 
    "seattle", "dallas", "pittsburgh", "miami", "denver", "hartford", 
    "houston", "atlanta", "san diego", "montreal", "milwaukee", 
    "new york", "philadelphia", "vancouver", "toronto", "calgary", 
    "chicago", "san jose", "dallas", "pittsburgh", "mexico city", 
    "seattle")), .Names = c("DATE_TIME", "SITE", "RESPONSE_TIME", 
"AVAIL_PERCENT", "AGENT", "LOCATION"), row.names = c(NA, 30L), class = "data.frame")

我试过这个：

require(maps)
require(ggplot2)

ggplot(df, aes(map_id = LOCATION)) + geom_map(aes(fill = RESPONSE_TIME), map = states_map) + expand_limits(x = states_map$long, y = states_map$lat)

有什么想法我在这里做错了吗？

4

1 回答 1

0

转换df$LOCATION为相应的状态。

加载数据集：

data(us.cities)
data(state, package="datasets")

c2s = sapply(df$LOCATION,function(x){
            us.cities[grep(x,us.cities$name,ignore.case=T)[1],2]})

> head(c2s)
  seattle  hartford   houston san diego  montreal  new york 
     "WA"      "CT"      "TX"      "CA"        NA      "NY"

获取州缩写：

a2n = tolower(state.name)
names(a2n) = state.abb
df = cbind(df,a2n[c2s])

> head(df)
            DATE_TIME                 SITE RESPONSE_TIME AVAIL_PERCENT AGENT
1 2013-05-24 14:21:00 Logon to My Accounts         7.069           100 45869
2 2013-05-24 14:22:00 Logon to My Accounts         7.056           100 45540
3 2013-05-24 14:22:00 Logon to My Accounts        11.535           100 45672
4 2013-05-24 14:23:00 Logon to My Accounts         7.330           100 45036
5 2013-05-24 14:23:00 Logon to My Accounts         9.566           100 45421
6 2013-05-24 14:24:00 Logon to My Accounts         5.210           100 42627
   LOCATION  c2s    a2n[c2s]
1   seattle   WA  washington
2  hartford   CT connecticut
3   houston   TX       texas
4 san diego   CA  california
5  montreal <NA>        <NA>
6  new york   NY    new york

colnames(df)[7:8] = c("State.Abb","State")

省略加拿大各州和情节：

ggplot(df[!is.na(df$State),], aes(map_id = State)) + geom_map(aes(fill = RESPONSE_TIME), map = states_map) + expand_limits(x = states_map$long, y = states_map$lat)

在此处输入图像描述

要获取整个地图，只需将剩余状态附加到底部df

于 2013-05-31T20:23:49.603 回答