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state,county,name,unemployment
01,000,Alabama,0.061
01,001,"Autauga County, AL",0.052
01,003,"Baldwin County, AL",0.055
01,005,"Barbour County, AL",0.089
01,007,"Bibb County, AL",0.066
01,009,"Blount County, AL",0.054
01,011,"Bullock County, AL",0.078
01,013,"Butler County, AL",0.075
01,015,"Calhoun County, AL",0.07
@spiker830
spiker830 / us_preamble_similarity_graph.json
Created May 7, 2021 21:44
JSON graph of the similarity matrix for the US state preambles
{
"nodes": [
{
"name": "AL"
},
{
"name": "AK"
},
{
"name": "AZ"
@spiker830
spiker830 / 2019-county-population-estimates.csv
Created August 8, 2020 04:16
2019 county level population estimates, just the population estimate. From US Census Bureau: https://www.census.gov/data/tables/time-series/demo/popest/2010s-counties-total.html
STATE COUNTY STNAME CTYNAME POPESTIMATE2019
1 0 Alabama Alabama 4903185
1 1 Alabama Autauga County 55869
1 3 Alabama Baldwin County 223234
1 5 Alabama Barbour County 24686
1 7 Alabama Bibb County 22394
1 9 Alabama Blount County 57826
1 11 Alabama Bullock County 10101
1 13 Alabama Butler County 19448
1 15 Alabama Calhoun County 113605
We can't make this file beautiful and searchable because it's too large.
SUMLEV,REGION,DIVISION,STATE,COUNTY,STNAME,CTYNAME,CENSUS2010POP,ESTIMATESBASE2010,POPESTIMATE2010,POPESTIMATE2011,POPESTIMATE2012,POPESTIMATE2013,POPESTIMATE2014,POPESTIMATE2015,POPESTIMATE2016,POPESTIMATE2017,POPESTIMATE2018,POPESTIMATE2019,NPOPCHG_2010,NPOPCHG_2011,NPOPCHG_2012,NPOPCHG_2013,NPOPCHG_2014,NPOPCHG_2015,NPOPCHG_2016,NPOPCHG_2017,NPOPCHG_2018,NPOPCHG_2019,BIRTHS2010,BIRTHS2011,BIRTHS2012,BIRTHS2013,BIRTHS2014,BIRTHS2015,BIRTHS2016,BIRTHS2017,BIRTHS2018,BIRTHS2019,DEATHS2010,DEATHS2011,DEATHS2012,DEATHS2013,DEATHS2014,DEATHS2015,DEATHS2016,DEATHS2017,DEATHS2018,DEATHS2019,NATURALINC2010,NATURALINC2011,NATURALINC2012,NATURALINC2013,NATURALINC2014,NATURALINC2015,NATURALINC2016,NATURALINC2017,NATURALINC2018,NATURALINC2019,INTERNATIONALMIG2010,INTERNATIONALMIG2011,INTERNATIONALMIG2012,INTERNATIONALMIG2013,INTERNATIONALMIG2014,INTERNATIONALMIG2015,INTERNATIONALMIG2016,INTERNATIONALMIG2017,INTERNATIONALMIG2018,INTERNATIONALMIG2019,DOMESTICMIG2010,DOMESTICMIG2011,DOMESTICMIG2012,DOMESTICMIG2013,DOMESTI
@spiker830
spiker830 / us_state_population_estimates_2017_lookup.json
Created August 2, 2020 05:42
JSON object of state names to population. Source: https://worldpopulationreview.com/states (from US Census Bureau's 2017 population estimates)
{
"Alabama":4908620,
"Alaska":734002,
"Arizona":7378490,
"Arkansas":3039000,
"California":39937500,
"Colorado":5845530,
"Connecticut":3563080,
"Delaware":982895,
"District of Columbia":720687,
@spiker830
spiker830 / covid_cases_us_07-24-2020.json
Last active July 25, 2020 21:22
Covid-19 per state case/death data for July 24th (from Johns Hopkins) along with state population estimates (from US Census Bureau). Used for the visualization described here: https://investingdeeply.com/blog/animated-horizontal-bar-chart-d3/
[
{
"state":"Alabama",
"cases":76005,
"deaths":1438,
"population":4908620
},
{
"state":"Alaska",
"cases":2249,
@spiker830
spiker830 / covid_deaths.json
Last active April 12, 2020 14:43
JSON of total Covid-19 deaths from Jan 23 to Apr 10. Used for visualization at http://investingdeeply.com/blog/bar-chart-d3-vue/
[
{
"date":"Jan 23",
"total_deaths":25
},
{
"date":"Jan 24",
"total_deaths":41
},
{
@spiker830
spiker830 / europe_features.json
Created April 3, 2020 22:20
GeoJSON of country outlines of Europe. Low resolution. Used for map at http://investingdeeply.com/blog/basic-maps-with-d3/
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@spiker830
spiker830 / federal_hill_sales.json
Last active December 14, 2022 19:24
JSON of the average sale price for properties in the Federal Hill neighborhood of Baltimore, MD. Each data point is the average price within a lat long square. Used for heatmap at http://investingdeeply.com/blog/heatmaps-leaflet-heatmap-js/
[
{
"lat":"39.2705",
"lng":"-76.6165",
"price":120000
},
{
"lat":"39.2705",
"lng":"-76.6155",
"price":234500
@spiker830
spiker830 / us_preamble_similarity_matrix.json
Last active March 9, 2020 19:47
TF-IDF document similarity matrix comparing the preambles of the US state constitutions. Method discussed at http://investingdeeply.com/blog/tf-idf-document-similarity-state-preambles/
[
[
1.0,
0.2330767830582499,
0.3580449463374264,
0.33104457161464773,
0.30990506110472205,
0.30873798523027984,
0.23994100496376014,
0.14688136622463122,