R map plot without longitude and latitude

Question

I would like to plot the R map without the longitude and latitude values. Most of the map functions use longitude and latitude values. The only information I have is the name of the state and frequency. Please let me know how to plot the R map.

    state   freq
1   california  14717
2   texas   6842
3   new york    6729
4   florida 6720
5   illinois    5921
6   NA  5897
7   georgia 5008
8   ohio    4197
9   michigan    3593
10  virginia    3278
11  new jersey  3097
12  north carolina  3084
13  washington  3048
14  pennsylvania    2972
15  maryland    2821
16  missouri    2615
17  minnesota   2318
18  massachusetts   2242
19  colorado    2210
20  indiana 2078
21  arizona 1901
22  wisconsin   1842
23  oregon  1817
24  tennessee   1737
25  alabama 1679
26  connecticut 1627
27  south carolina  1122
28  nevada  1090
29  kansas  1062
30  kentucky    983
31  oklahoma    971
32  louisiana   954
33  utah    877
34  arkansas    855
35  mississippi 787
36  nebraska    674
37  idaho   599
38  new hampshire   551
39  new mexico  472
40  rhode island    435
41  hawaii  409
42  west virginia   391
43  montana 330
44  delaware    300
45  vermont 207
46  alaska  200
47  south dakota    189
48  iowa    186
49  wyoming 150
50  maine   101
51  north dakota    52

Answer 1

Here is a plotly alternative using some of the techniques from previous respondents:

library(plotly)

# create df but taking a subset of original poster's data
df <- data.frame(state = c("california","texas","nevada","north dakota", rep("NA", 47)),
              freq = c(14717, 6842, 1090, 52, rep(0, 47)),
              stringsAsFactors = FALSE )

# generate location information for all states (using built-in data)
state.info <- inner_join(data.frame(state=tolower(state.name), 
                                    long=state.center$x, lat=state.center$y, 
                                    stringsAsFactors=FALSE),
                         data.frame(state=tolower(datasets::state.name), 
                                    abbrev=datasets::state.abb))

# join the test data to the states location info
map.df <- inner_join(state.info, df, by="state")

# set up plotly to zoom in to US only
g <- list(scope='usa', projection=list(type='albers usa'), 
          showlakes=TRUE, lakecolor=toRGB('white'))

# plot on the US map
plot_ly(map.df, type='choropleth', locationmode='USA-states', 
    locations=map.df$abbrev, z=map.df$freq, text=map.df$state) %>% 
    layout(geo=g, title='Frequency by State')

This produces:

Answer 2

This is the code that Deepayan Sarkar offered in his book "Lattice: " to plot a pseudo-3d barplot with continental US states as the x.y location for the bars. You should be able to substitute the 'density' values with the values in your dataset. You will probably need to remove the exclusion of AK and HI.

state.info <- data.frame(name = state.name, long = state.center$x, lat = state.center$y, 
                          area = state.x77[, "Area"], 
                           population = 1000 * state.x77[, "Population"]) 
state.info$density <- with(state.info, population / area)

library("maps") 
state.map <- map("state", plot=FALSE, fill = FALSE) 
panel.3dmap <- function(..., rot.mat, distance, xlim, ylim, zlim, xlim.scaled, 
ylim.scaled, zlim.scaled) { scaled.val <- function(x, original, scaled) { 
               scaled[1] + (x - original[1]) * diff(scaled) / diff(original) } 
m <- ltransform3dto3d(rbind(scaled.val(state.map$x, xlim, xlim.scaled), 
     scaled.val(state.map$y, ylim, ylim.scaled), zlim.scaled[1]), rot.mat, distance)
panel.lines(m[1,], m[2,], col = "grey76") } 

cloud(density ~ long + lat, state.info, subset = !(name %in% c("Alaska", "Hawaii")), 
panel.3d.cloud = function(...) { panel.3dmap(...) 
                                 panel.3dscatter(...) }, 
     type = "h", scales = list(draw = FALSE), zoom = 1.1, xlim = state.map$range[1:2], 
     ylim = state.map$range[3:4], xlab = NULL, ylab = NULL, zlab = NULL, 
     aspect = c(diff(state.map$range[3:4]) / diff(state.map$range[1:2]), 0.3), 
      panel.aspect = 0.75, lwd = 2, screen = list(z = 30, x = -60), 
      par.settings = list(axis.line = list(col = "transparent"),
                           box.3d = list(col = "transparent", alpha = 0)))

Answer 3

Here is a partial choropleth, using the partial data frame contributed by @akhmed.

df <- data.frame( state = c("california","texas","nevada","north dakota", rep("NA", 47)),
                  freq = c(14717, 6842, 1090, 52, rep(0, 47)),
                  stringsAsFactors = FALSE )

library(maps)
library(ggthemes)
states_map <- map_data("state", region = c("california","texas","nevada","north dakota"))
new_map <- merge(states_map, df, by.x = "region", by.y = "state")
new_map <- arrange(new_map, group, order) # to sort polygons in right order

ggplot(new_map, aes(x = long, y = lat, group = group, fill = freq)) + 
  geom_polygon(color = "black") + 
  coord_map("polyconic") + theme_tufte() + labs(x = "", y = "")

You can revise the color scheme with scale_fill_gradient2, for example.

Answer 4

Lacking a reproducible example, I manually typed just 4 states as an illustration:

library(dplyr)
library(ggplot2)

df <- data.frame( state = c("california","texas","nevada","north dakota"),
                  freq = c(14717, 6842, 1090, 52),
                  stringsAsFactors = FALSE )

state_level_df <- data.frame(state = tolower(state.name), 
                             long = state.center$x, 
                             lat = state.center$y,
                             stringsAsFactors = FALSE) %>%
                  inner_join( df, by="state" )

ggplot(state_level_df, aes(long, lat)) +
  borders("state") +
  geom_point(aes(color=freq,size=freq), show_guide=FALSE) +
  theme(text=element_text(size=18)) +
  scale_size(range=c(2,20)) + 
  scale_color_continuous(low="red",high="green") +
  theme_bw()

which gives me this:

Your full data frame df should work as well.