Roads
In cholera: Amend, Augment and Aid Analysis of John Snow's Cholera Map

knitr::opts_chunk$set(collapse = TRUE, comment = ">")
library(cholera)

Overview

In 1992, Rusty Dodson and Waldo Tobler digitized John Snow's cholera map. Unfortunately, they did not include the names of roads (e.g., Broad Street) in their data set. While not strictly necessary for analysis or visualization, having the names can be useful so I appended the actual street names from the map to the roads data set.

Roads data

Before discussing the details, some discussion of the structure of roads is warranted. The data contain 1241 pairs of x-y coordinates that define the endpoints of straight line segments used to describe some 528 numerically identified "streets".

head(roads)

nrow(roads)

length(unique(roads$street))

The correspondence between these 528 "streets" and streets in the real world is not one-to-one. Excluding the 50 "streets" used to draw the map's frame, the remaining 478 "streets" actually describe 206 real world roads (e.g., Oxford Street, Regent Street).

This discrepancy emerges because real world streets are approximated using straight line segments. In fact 40% of the "real world" roads are composed of multiple "street" segments: for example, Oxford Street consists of 26 line segments and Broad Street consists of 6.

# Map Border "Streets" #

top <- c(1:12, 14)
right <- c(37, 62, 74, 142, 147, 205, 240, 248, 280, 360, 405, 419, 465)
bottom <- c(483, seq(487, 495, 2), 498, 500, seq(503, 519, 2))
left <- c(31, 79, 114, 285, 348, 397, 469)
border <- sort(c(bottom, left, top, right))

length(border)

Road names

The primary source for road names is Snow's map (a high resolution version is available here. While great effort was made to correctly record and cross-reference names, there may still be errors. Error reports and suggestions for amendments are welcome.

Some roads on the map do not have a name. In those cases, I attach unique labels like "Unknown-C".

Some names appear multiple times even though they lie at different locations. For these, I use Roman numerals to distinguish them (e.g., "King Street (I)" and "King Street (II)").^[Streets with the same name were not an unusual occurrence. See Judith Flanders. 2012. The Victorian City: everyday life in Dickens' London. New York: St. Martin's Press, 57-58.]

Queen Street (I) and Marlborough Mews

There is one apparent coding error in Dodson and Tobler's road data. Queen Street (I) extends too far: the water pump #5 is clearly located on Marlborough Mews (see map, cited above) but ends up on Queen Street (I).

I amend this by moving the end point of Queen Street (I) westward so that the street only runs in a north-south direction. I do so by reassigning the segment that runs east-west to be part of Marlborough Mews.

snow.streets <- HistData::Snow.streets
snow.streets$id <- seq_len(nrow(snow.streets))

# Data frame of road names
road.data <- read.csv("~/Documents/Data IV/Snow/road3b.csv",
  stringsAsFactors = FALSE)

roads <- merge(snow.streets, road.data, by = "street", all.x = TRUE)
roads[is.na(roads$name), "name"] <- "Map Frame"

roads[roads$id == 277, "street"] <- 116
roads[roads$id == 277, "name"] <- "Marlborough Mews"
roads[roads$id == 277, c("x", "y")] <- roads[roads$id == 276, c("x", "y")]
roads[roads$name == "Queen Street (I)", "n"] <- 4
roads[roads$name == "Marlborough Mews", "n"] <- 3
roads <- roads[order(roads$id), ]

Finding roads by name, "street" number, or segment ID.

To help locate and visualize streets and road segments (including the map frame segments), you can use streetNameLocator(), streetNumberLocator(), or segmentLocator().

Note that streetNameLocator() uses the names from the roads data set and tries to corrects for case and for extra spaces: streetNameLocator("Oxford Street") and streetNameLocator("oxford street").

segmentLocator() provides more granular analysis. It uses individual road segments as the unit of observation.

List of road names

There are 206 "valid" road names; 207, if we include "Map Frame":

knitr::opts_chunk$set(collapse = TRUE, comment = "")

road.names <- sort(unique(roads$name))
road.names <- road.names[road.names != "Map Frame"]
road.names <- stats::setNames(data.frame(matrix(road.names, ncol = 2)), NULL)
print(road.names, right = FALSE)

Coordinate unit

The original map is 14.5 x 15.5 inches with a stated nominal scale of 30 inches per mile.

Dodson and Tobler write that "The scale of the source map is approx. 1:2000. Coordinate units are meters." By my estimate, one unit on the map is approximately 177 feet or 54 meters per unit.^[According to Dodson and Tobler's data, the length of Carnaby Street from its intersection with Great Marlborough to its intersection with Cross Street is 2.61 units. According to Google Maps, the approximate analog of that segment is the distance along parts of Great Marlborough Street and Carnaby Street between 19-21 Great Marlborough Street and 43 Carnaby Street (at Ganton Street): 463 ft. This translates into approximately 177 feet/unit or 54 meters/unit.]