police-violence

A look at the data from Mapping Police Violence.
git clone https://git.eamoncaddigan.net/police-violence.git
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commit 50082a06956860f073129d7673a4978658e436b4
parent f6f9f664588bb31b1453963c4c329af01bccf7c0
Author: eamoncaddigan <eamon.caddigan@gmail.com>
Date:   Thu, 24 Dec 2015 06:05:24 -0500

Figured out what %+replace% does, am using it.

Diffstat:
Mpolice-violence.Rmd | 18++++++++++--------
1 file changed, 10 insertions(+), 8 deletions(-)

diff --git a/police-violence.Rmd b/police-violence.Rmd @@ -7,9 +7,9 @@ output: html_document [Mapping Police Violence](http://mappingpoliceviolence.org/) just released [their 2015 Police Violence Report](http://mappingpoliceviolence.org/2015/), along with the data supporting it. -One of the most stunning conclusions of the original report is the finding that community violence does not predict police violence. This disproves a common narrative that police are simply responding to violence in kind, and suggests that department policy plays a role in police behavior. +One of the most stunning conclusions of the original report is the finding that community violence does not predict police violence. This disproves a common narrative that police are simply responding to violence in kind, and suggests that department policy plays a role in police behavior. -![Police Violence and Community Violence are Independent Issues](MPV-community-police-violence.jpg) +Here I take a stab at recreating the graph that accompanies the report. It plots community and police violence in the figure, with separate Y-axes for the factors. ```{r} library(readxl) @@ -31,18 +31,20 @@ p1 <- ggplot(mpvReport, aes(x = row_number, y = `Rate of Police Killings per Million Population`)) + geom_bar(color = "black", fill = "white", stat = "identity") + geom_point(size = 3) + - theme_classic() + - theme(axis.text.x=element_text(angle = -90, hjust = 0)) + - scale_x_continuous(limits = c(0.5, 60.5), + theme_classic() %+replace% + theme(axis.text.x=element_text(angle = 90, hjust = 1)) + + scale_x_continuous(name = "", + limits = c(0.5, 60.5), breaks = 1:60, labels = mpvReport$`Police Department`) p2 <- ggplot(mpvReport, aes(x = row_number, y = `Violent Crime per 1,000 residents`)) + geom_point(color = "blue", shape = 8) + - theme_classic() + + theme_classic() %+replace% theme(panel.background = element_rect(fill = NA), - axis.text.x=element_text(angle = -90, hjust = 0)) + - scale_x_continuous(limits = c(0.5, 60.5), + axis.text.x=element_text(angle = 90, hjust = 1)) + + scale_x_continuous(name = "", + limits = c(0.5, 60.5), breaks = 1:60, labels = mpvReport$`Police Department`)