heat_map_discrete: Create a heat map of Chicago with discrete shading.

Description Usage Arguments Value Examples

Description

Create a heat map of Chicago with discrete shading.

Usage

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heat_map_discrete(regions, summary_df, regions_var, fill_var, legend_name,
  palette, na_replace = NA, lines = "black", title = NULL,
  title_size = 15, region_labels = FALSE)

Arguments

regions

The type of region to plot. Options include: "CAs", "tracts," "districts," and "zips."

summary_df

A data frame with summary statistics by region. Should have one row for each region.

regions_var

The variable in summary_df that identifies the region. For example, if type = "CAs" a common merge_var.y would be "Community.Areas." In general, regions_var should be numeric (e.g. use community area numbers, not names.).

fill_var

The variable that determines color. For example, if the map shows homicides by police district, the fill_var would be the field that contains homicide totals.

legend_name

Self Explanatory. Should be a character vector of length one.

palette

The color palette. Current options are: green, blue, red, organge, and purple.

na_replace

What value should replace NAs in the fill_var. This arises most commonly in maps of homicides, where regions with zero homicides are sometimes missing from df.y. Add the lowest discrete value for your scale.

lines

Color of border lines. Default is black.

title

Title.

title_size

Title size.

region_labels

Option to add labels for CAs or districts. Default is false

Value

A map of Chicago. More specifically, an object of type "ggplot."

Examples

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data(hom_14)
library(dplyr)
hom_sum <- dplyr::summarise(group_by(hom_14, Community.Area), homicides = n())

There is now an na_replace option so disregard the following: 
# No na_replace option for discrete maps. Need to manually add zero homicide CAs.
additions <- c(1:77)[which(!c(1:77) %in% hom_sum$Community.Area)]
df_additions <- data.frame(Community.Area = additions, homicides = 0)
hom_sum <- rbind(hom_sum, df_additions)
hom_sum$range <- cut(hom_sum$homicides, c(0, 5, 10, 15, 20, 30, 40),
                     labels = c("0-4", "5-9", "10-14", "15-19",
                               "20-29", "30-39"), right = FALSE)

library(RColorBrewer)
colors <- brewer.pal(n = 6, name = "BuPu")
hm_dis <- heat_map_discrete(regions = "CAs", summary_df = hom_sum, regions_var = "Community.Area",
                            fill_var = "range", legend_name = "Total Homicides",
                            palette = colors, title = "Homicides by Community Area: 2014")

dmwelgus/MapChi documentation built on May 15, 2019, 9:38 a.m.