Compiled from publicly available news sources including NY Times, CNN, NPR, and Wikipedia.
Pct_point_diff is calculated as (Dem vote percentage - GOP vote percentage).
license: mit | |
height: 500 | |
border: no |
Compiled from publicly available news sources including NY Times, CNN, NPR, and Wikipedia.
Pct_point_diff is calculated as (Dem vote percentage - GOP vote percentage).
CD;Incumbent;Party;Pres;Open;Not running | |
AK-AL;Young, Don;(R);Trump;FALSE; | |
AL-01;Byrne, Bradley;(R);Trump;FALSE; | |
AL-02;Roby, Martha;(R);Trump;FALSE; | |
AL-03;Rogers, Mike;(R);Trump;FALSE; | |
AL-04;Aderholt, Rob;(R);Trump;FALSE; | |
AL-05;Brooks, Mo;(R);Trump;FALSE; | |
AL-06;Palmer, Gary;(R);Trump;FALSE; | |
AL-07;Sewell, Terri;(D);Clinton;FALSE; | |
AR-01;Crawford, Rick;(R);Trump;FALSE; |
per_point_diff_2016|per_point_diff_2012|per_point_diff_2008|state_abbr|county_name|per_point_diff_12_16|per_point_diff_08_16 | |
-0.4947893435|-0.460579698|-0.4784061588|AL|Autauga County|-0.03420964548|-0.01638318471 | |
-0.5778616219|-0.5582317504|-0.5144755752|AL|Baldwin County|-0.01962987149|-0.0633860467 | |
-0.05611164581|0.02914739506|-0.01453138435|AL|Barbour County|-0.08525904087|-0.04158026146 | |
-0.5554412437|-0.4684781313|-0.4584683017|AL|Bibb County|-0.08696311238|-0.096972942 | |
-0.813819729|-0.7414512093|-0.6950591338|AL|Blount County|-0.07236851962|-0.1187605952 | |
0.5086151883|0.5280180519|0.4838411819|AL|Bullock County|-0.01940286364|0.02477400636 | |
-0.1352907311|-0.07529262891|-0.1335873931|AL|Butler County|-0.05999810223|-0.001703338005 | |
-0.4138382303|-0.3194636678|-0.3252101864|AL|Calhoun County|-0.09437456251|-0.0886280439 | |
-0.148062128|-0.0510232111|-0.08478202728|AL|Chambers County|-0.09703891693|-0.06328010075 |
const star = radius => | |
[0, .4, .8, .2, .6, 0].map(d => | |
Math.round(1000* radius*Math.cos(2*Math.PI*d - .5*Math.PI) )/1000 | |
+","+ | |
Math.round(1000* radius*Math.sin(2*Math.PI*d - .5*Math.PI) )/1000 | |
).join(' ') | |
star(7.5) |
[ | |
{ | |
"tree_id": 190422, | |
"spc_common": "honeylocust", | |
"Latitude": 40.77004563, | |
"longitude": -73.98494997 | |
}, | |
{ | |
"tree_id": 190426, | |
"spc_common": "honeylocust", |
<html> | |
<head> | |
<style> | |
.menu { | |
display: block; } | |
.menu select { | |
margin: 10px; } | |
.menu .legend { | |
margin: 10px; | |
position: relative; |
library(dplyr) | |
library(tidyr) | |
library(jsonlite) | |
#https://data.cityofnewyork.us/Environment/2015-Street-Tree-Census-Tree-Data/pi5s-9p35 | |
raw <- read.csv("~/Downloads/2015StreetTreesCensus_TREES.csv", stringsAsFactors = F) | |
trees <- tbl_df(raw) %>% | |
group_by(boroname, nta_name, spc_common, health) %>% | |
summarise(n = n()) | |
write(toJSON(trees), "~/Desktop/trees.json") |
voters <- read.csv("~/Downloads/voter_file.csv", stringsAsFactors = F) | |
voters_sub <- voters[c("SBOEID","DOB","REGDATE","ENROLLMENT","LASTVOTEDATE","COUNTYCODE","ED","WARD","SD","AD","LD")] | |
existing_eds <- tbl_df(voters_sub) %>% | |
group_by(ED, ENROLLMENT) %>% | |
summarise(count = n()) %>% | |
spread(ENROLLMENT, count) %>% | |
mutate(TOTAL = sum(BLK,CON,DEM,GRE,IND,OTH,REF,REP,WEP,WOR,na.rm=T), | |
DEM_PCT = DEM/TOTAL) | |
new_dems_eds <- tbl_df(voters_sub) %>% | |
filter(REGDATE >= 20161109) %>% |