RandomCriticalAnalysis’s gists

RandomCriticalAnalysis / philly_shooting_quick_and_dirty.csv

Created August 16, 2020 15:57

We can make this file beautiful and searchable if this error is corrected: It looks like row 7 should actually have 13 columns, instead of 9 in line 6.

	tractStr,fid,geoid,population,poverty_rate,median_income,pct_white,pct_asian,pct_black,pct_white_or_asian,shootings,shooting_rate,shooting_rate_yj_transform
	000100,1,42101000100,4166,0.06937109937590015,102448,0.7366778684589534,0.04392702832453192,0.07513202112337974,0.7806048967834853,0,0,-1.3860356463057237
	000200,2,42101000200,2576,0.29253365973072215,47243,0.2080745341614907,0.11995341614906832,0.0562888198757764,0.328027950310559,2,0.78,-0.60289626497475
	000300,3,42101000300,3444,0.09255219694608913,91354,0.6387921022067363,0.05400696864111498,0.06416957026713124,0.6927990708478513,1,0.29,-1.0267090442254603
	000401,4,42101000401,2591,0.17697394010112796,62821,0.6086453106908529,0.06831339251254342,0.12118873021999228,0.6769587032033964,0,0,-1.3860356463057237
	000402,5,42101000402,3880,0.04690721649484536,78648,0.8378865979381444,0.038402061855670105,0.05515463917525773,0.8762886597938144,5,1.29,-0.2935049723600755
	000500,6,42101000500,2471,0.33153638814016173,43702,0.3537029542695265,0.0453257790368272,

RandomCriticalAnalysis / bea_economic_areas_county_crosswalk.csv

Created April 9, 2020 21:16

fips	bea_ea_code	bea_ea_name	pop10	county_name	gdp2018
1001	114	Montgomery-Alexander City, AL	54571	Autauga, AL	1690937
1003	112	Mobile-Daphne-Fairhope, AL	182265	Baldwin, AL	6606080
1005	48	Dothan-Enterprise-Ozark, AL	27457	Barbour, AL	851956
1007	19	Birmingham-Hoover-Cullman, AL	22915	Bibb, AL	424510
1009	19	Birmingham-Hoover-Cullman, AL	57322	Blount, AL	942904
1011	114	Montgomery-Alexander City, AL	10914	Bullock, AL	256130
1013	114	Montgomery-Alexander City, AL	20947	Butler, AL	632592
1015	19	Birmingham-Hoover-Cullman, AL	118572	Calhoun, AL	4428092
1017	11	Atlanta-Sandy Springs-Gainesville, GA-AL	34215	Chambers, AL	2218892

RandomCriticalAnalysis / facet example.r

Created April 2, 2020 22:29

RandomCriticalAnalysis / European CDC covid fetch

Created March 22, 2020 19:10

	library(tidyverse)
	library(readxl)
	library(httr)
	library(countrycode)
	library(janitor)
	library(hrbrthemes)
	library(ggrepel)
	library(scales)
	library(zoo)
	#devtools::install_github("slowkow/ggrepel")

RandomCriticalAnalysis / plot-corona.R

Created March 11, 2020 14:54 — forked from gorkang/plot-corona.R

COVID plot adapted from https://github.com/JonMinton/COVID-19

	# FROM: https://github.com/JonMinton/COVID-19



	DF = tidied_data %>%
	filter(type == "confirmed") %>%
	mutate(
	higher = case_when(
	higher == "Iran (Islamic Republic of)" ~ "Iran",
	higher == "Hong Kong SAR" ~ "Hong Kong",

RandomCriticalAnalysis / oecd_examples_helper_fn.R

Created November 22, 2019 17:45

Quick examples for helper OECD helper functions

	source("oecd_helper_library.R")


	# example of how to fetch parameter info from within R
	sna1_filter_short=show_filter_options('SNA_TABLE1',showLong=F)

	sna1_filter_long=show_filter_options('SNA_TABLE1',showLong=T)

RandomCriticalAnalysis / oecd_helper_library.R

Created November 22, 2019 17:43

Helper functions to make using OECD package easier

	library(tidyverse)
	library(OECD)

	# global variable to cache data structure in memory
	# this is crudely implemented, but much faster than hitting OECD.stat constantly

	if (!exists("oecd_cached_structures")) {
	oecd_cached_structures=list()
	} else {
	warning("oecd_cached_structures already set. You can delete the object if you wish to clear....")

RandomCriticalAnalysis / state_fiscal_test_score_correlation_example.R

Created May 7, 2018 14:36

Snippet to create correlation plot by state between school test scores and per pupil fiscal measures

	library(dplyr)
	library(reshape2)
	library(ggplot2)

	DataPath="." # you may need to update this if not working from same path
	setwd(DataPath)

	# Data from version 2.0 of covariates and pooled score estimates from SEDA
	# https://cepa.stanford.edu/seda/data-archive

RandomCriticalAnalysis / make_icp_data.R

Created January 27, 2018 00:27

Snippet to create ICP series with WHO NHE figures at PPPs for AIC and GDP

	require(dplyr)
	require(janitor)
	require(reshape2)
	require(countrycode)


	icp_raw = read.csv("ext_data/WorldBank_icp_2011.csv", stringsAsFactors = F) %>%
	filter(
	Country.Code != '' # remove blank lines and notes at end of file
	) %>%

RandomCriticalAnalysis / seda_relevant_snippet.R

Last active May 31, 2016 21:41

for Anatoly (relevant code for education analysis)

	# test scores and most covariates taken from
	# https://cepa.stanford.edu/seda/download?nid=1727&destination=node/1717

	# parents average years of education computed using data from census ACS (via dept of edu EDGE service)
	# http://nces.ed.gov/programs/edge/demographicACS.aspx

	pm = read.csv("cepa_pooled_means.csv",stringsAsFactors = F)
	cve = read.csv("cepa_covariates_from_excel.csv",stringsAsFactors = F)
	glarge = merge(cve,pm,by.x='leaid',by.y='nces_district_id')

	stated %>%
	filter(
	!is.na(region),
	date >= as.Date("2020-03-01"),
	state %in% c('NY','NJ','CT','MA','PA')
	) %>%
	mutate(
	date_from=as.integer(date - as.Date("2020-03-01")),
	value=death/pop*10^6
	) %>%

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