Description Usage Arguments Examples
The map used is state.map in the package choroplethrMaps. See state.regions in the choroplethrMaps package for a data.frame that can help you coerce your regions into the required format.
1 | state_choropleth(df, title = "", legend = "", buckets = 7, zoom = NULL)
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df |
A data.frame with a column named "region" and a column named "value". Elements in the "region" column must exactly match how regions are named in the "region" column in state.map. |
title |
An optional title for the map. |
legend |
An optional name for the legend. |
buckets |
The number of equally sized buckets to places the values in. A value of 1 will use a continuous scale, and a value in [2, 9] will use that many buckets. |
zoom |
An optional vector of states to zoom in on. Elements of this vector must exactly match the names of states as they appear in the "region" column of ?state.regions. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | # demonstrate default parameters - visualization using 7 equally sized buckets
data(df_pop_state)
state_choropleth(df_pop_state, title="US 2012 State Population Estimates", legend="Population")
# demonstrate continuous scale and zoom
data(df_pop_state)
state_choropleth(df_pop_state,
title="US 2012 State Population Estimates",
legend="Population",
buckets=1,
zoom=c("california", "oregon", "washington"))
# demonstrate how choroplethr handles character and factor values
# demonstrate user creating their own discretization of the input
data(df_pop_state)
df_pop_state$str = ""
for (i in 1:nrow(df_pop_state))
{
if (df_pop_state[i,"value"] < 1000000)
{
df_pop_state[i,"str"] = "< 1M"
} else {
df_pop_state[i,"str"] = "> 1M"
}
}
df_pop_state$value = df_pop_state$str
state_choropleth(df_pop_state, title="Which states have less than 1M people?")
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