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mikkelkrogsholm / docker-compose.yml
Last active January 20, 2020 04:11 — forked from pantsel/docker-compose.yml
example docker-compose.yml for kong, postgres and konga
version: "3"
networks:
kong-net:
driver: bridge
services:
#######################################
# Postgres: The database used by Kong
@mikkelkrogsholm
mikkelkrogsholm / docker-compose.yml
Last active January 8, 2019 15:42
docker-compose for kong, konga and elastic
version: "3"
networks:
kong-net:
driver: bridge
services:
#######################################
# Postgres: The database used by Kong
@mikkelkrogsholm
mikkelkrogsholm / fw_data.csv
Created January 4, 2019 10:28
We can't make this file beautiful and searchable because it's too large.
name,adresse,postnr,by,place_id,lat,lng,hour,weekday,popularity,pop_rel
Fitness World,Nygade 63E,6200,Aabenraa,ChIJb75A59lTs0cR0hqn2MR3i5s,55.04291180000001,9.416379700000002,0,Monday,0,0
Fitness World,Nygade 63E,6200,Aabenraa,ChIJb75A59lTs0cR0hqn2MR3i5s,55.04291180000001,9.416379700000002,1,Monday,0,0
Fitness World,Nygade 63E,6200,Aabenraa,ChIJb75A59lTs0cR0hqn2MR3i5s,55.04291180000001,9.416379700000002,2,Monday,0,0
Fitness World,Nygade 63E,6200,Aabenraa,ChIJb75A59lTs0cR0hqn2MR3i5s,55.04291180000001,9.416379700000002,3,Monday,0,0
Fitness World,Nygade 63E,6200,Aabenraa,ChIJb75A59lTs0cR0hqn2MR3i5s,55.04291180000001,9.416379700000002,4,Monday,0,0
Fitness World,Nygade 63E,6200,Aabenraa,ChIJb75A59lTs0cR0hqn2MR3i5s,55.04291180000001,9.416379700000002,5,Monday,0,0
Fitness World,Nygade 63E,6200,Aabenraa,ChIJb75A59lTs0cR0hqn2MR3i5s,55.04291180000001,9.416379700000002,6,Monday,6,0.06
Fitness World,Nygade 63E,6200,Aabenraa,ChIJb75A59lTs0cR0hqn2MR3i5s,55.04291180000001,9.416379700000002,7,Monday,13,0.13
Fitness World,Nyg
@mikkelkrogsholm
mikkelkrogsholm / ep2019.csv
Created May 27, 2019 11:44
We can't make this file beautiful and searchable because it's too large.
election,constituency,place,party_letter,party,votes,dif_votes
Europa-Parlamentsvalg 2019,Frederikshavnkredsen,Skagen,A,Socialdemokratiet,1.023,376
Europa-Parlamentsvalg 2019,Frederikshavnkredsen,Skagen,B,Radikale Venstre,142,61
Europa-Parlamentsvalg 2019,Frederikshavnkredsen,Skagen,C,Det Konservative Folkeparti,127,-73
Europa-Parlamentsvalg 2019,Frederikshavnkredsen,Skagen,F,SF - Socialistisk Folkeparti,225,61
Europa-Parlamentsvalg 2019,Frederikshavnkredsen,Skagen,I,Liberal Alliance,37,-35
Europa-Parlamentsvalg 2019,Frederikshavnkredsen,Skagen,N,Folkebevægelsen mod EU,163,-74
Europa-Parlamentsvalg 2019,Frederikshavnkredsen,Skagen,O,Dansk Folkeparti,497,-569
Europa-Parlamentsvalg 2019,Frederikshavnkredsen,Skagen,V,"Venstre, Danmarks Liberale Parti",1.100,640
Europa-Parlamentsvalg 2019,Frederikshavnkredsen,Skagen,Ø,Enhedslisten - De Rød-Grønne,88,88
@mikkelkrogsholm
mikkelkrogsholm / waterposts.csv
Created July 26, 2019 16:36
This csv holds data on public and free water posts in Denmarks three largest cities
lat lng name vejnavn husnr postnr postnrnavn kommunekode
56.155787 10.20136 Mølleparken Åboulevarden 100 8000 Aarhus C 0751
56.1585 10.205833 Klostertorv Klostertorvet 10 8000 Aarhus C 0751
56.17001 10.220779 Risskov Dronning Margrethes Vej 16 8200 Aarhus N 0751
56.129284 10.203796 Mindeparken Carl Nielsens Vej 15B 8000 Aarhus C 0751
56.152705 10.201608 Ridehuset Frederiks Allé 6A 8000 Aarhus C 0751
56.150825 10.204959 Banegårdspladsen Banegårdspladsen 4A 8000 Aarhus C 0751
56.139098 10.207785 Tangkrogen Strandvejen 19 8000 Aarhus C 0751
56.156581 10.209509 Sct. Clemens Torv Skt. Clemens Torv 1 8000 Aarhus C 0751
55.657398 12.635994 Amager Strandvej - helårsåben Amager Strandvej 168 2300 København S 0101
@mikkelkrogsholm
mikkelkrogsholm / prediction.R
Created May 4, 2020 08:43
This is the code used to create my prediction of COVID 19 hospitalisation needs in Denmark
library(tidyverse)
options(scipen = 999)
# http://epirecip.es/epicookbook/chapters/sir/r_desolve
# Load deSolve library
library(deSolve)
################################################################################
@mikkelkrogsholm
mikkelkrogsholm / estimate_r.R
Created May 7, 2020 06:40
## Infrastructure notes ########################################################
# I am running this in docker image rocker/tidyverse:3.6.1
# Load packages
library(tidyverse)
library(EpiEstim)
## Fetch data from the covid19data API #########################################
url <- "https://api.covid19data.dk/ssi_newly_hospitalized"
@mikkelkrogsholm
mikkelkrogsholm / gist:1ed3b7b3629f9f4023ec859b75a848a3
Created October 28, 2020 10:07
Code for comparing danish covid deaths with others deaths
library(tidyverse)
library(lubridate)
# JH Data
newnames <- c("province", "country", "lat", "lon")
url_global_deaths = "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv"
global_deaths_raw <- read_csv(url_global_deaths)
@mikkelkrogsholm
mikkelkrogsholm / world_in_data_epidemic.R
Created November 7, 2020 10:24
Code comparing covid cases and deaths in Denmark
# Load the tidyverse
library(tidyverse)
# Load the data from Our World in Data
csv_url <- "https://covid.ourworldindata.org/data/owid-covid-data.csv"
data <- read_csv(csv_url)
# Filter the data to only get Denmark and data after feb 27
pd <- data %>%
@mikkelkrogsholm
mikkelkrogsholm / forecast_ads.csv
Created November 25, 2020 19:41
Script and Analytical Data Set for forecasting Covid in Denmark
date regionnavn tests cases pospct rm
2020-03-04 Hovedstaden 32 2 0.0625 0.11133660616743324
2020-03-05 Hovedstaden 36 10 0.2777777777777778 0.12637420015239564
2020-03-06 Hovedstaden 49 0 0 0.17998937478667856
2020-03-07 Hovedstaden 48 8 0.16666666666666666 0.21897701285265764
2020-03-08 Hovedstaden 76 12 0.15789473684210525 0.2549464006077597
2020-03-09 Hovedstaden 157 71 0.45222929936305734 0.23185372267637208
2020-03-10 Hovedstaden 279 116 0.4157706093189964 0.24419940168871773
2020-03-11 Hovedstaden 280 88 0.3142857142857143 0.23092312343548096
2020-03-12 Hovedstaden 155 18 0.11612903225806452 0.22144888839733617