ideas for the future, possible extensions, etc. - please open an issue, to add more ideas. Thanks a lot.
Anything here is going to happen probably ONLY IF there is feedback, attention, donations, etc. ...
- mortality - but for that I need one more dataset. Not available at the moment. Does the RKI provide time series of that? Please find out thanks.
- total number of days when incidence was above 500/week/million ?
- error / confidence intervall for the calculated R_eff
- How to do that? Suggestions please. (For the currently used Reff_4_7(daily) code, see this tweet https://twitter.com/drandreaskruger/status/1256776383642165253 )
- My current averaging window size is 7 days. What about this: I could do smoothing by 3 and 5 and 7 and 9 and 11 days, and calculate the 4-days-difference quotient for each of those. That would give 5 different estimates for R_eff (which however are increasingly less "fresh / uptodate"). Perhaps that could help to assess the accuracy of the estimate? Opinions please. Thanks.
- reproduction number experiments:
- Reff_7_4(cumulative) additional to (or instead of) Reff_4_7(daily)
- because the latter has overlapping smoothing windows = so it UNDER-estimates the true Reff !
- but first try out other variants, and study the differences in smaller districts
- Reff_7_4(cumulative) additional to (or instead of) Reff_4_7(daily)
- current 7-days-incidence-versus-prevalence to cancel out the population completely --> that might be called "transmission rate" ?
- coloring of the prevalence column
- perhaps instead of expectation day show "how man days ago was expectation day", i.e. max(i) - expectationday[i] ?
- wider table = will show better the gradient in expectationdays of max-min = 26 days
- 7-days-incidence-per-million above/below 500, binary observable and without smoothing. Number in cell: weekly-incidence
- same for 300 and 350
- "top 10" (or rather "bottom 10") for ALL of the measures. Quick overview where are all the "red districts". No need for table sorting. But only show worst cases.
- show also the districts 50km AROUND that Bundesland (below the table at the top, but still linked to other Bundesland pages?)
Bundesländer (states):
- all 16 R plots in one picture
- all 16 prevalence plots in one picture
- all 16 incidence plots in one picture
OR:
- not absolute but relative case numbers (i.e. divided by population), and: same y-axis range for all 16 plots; helps to better compare the regions in Germany
Kreise (districts):
- all districts' neighbours R plots all in one table
- districts: extend districts = aggregate the numbers of a district with all its neighbouring districts <=50km = new plot
- plot DailyDeaths-versus-TotalDeaths AND DailyCases-versus-totalCases (i.e. incidence versus prevalence, as the population cancels itself), see https://aatishb.com/covidtrends/ and the source code repo
- progression of the expectationday over time
- in Kreise plots, also show the expectationday green bar of Bundesland and of Germany. And in Bundesland also show the Germany expectationday.
- overview table HTML generator, for arbitrary collection of (AGS1, AGS2, AGS3, Bundesland1, Bundesland2) codes, in JavaScript: https://covh.github.io/cov19de/pages/overview.html?loc=5316,5315,5122,5378,5120,Nordrhein-Westfalen&rows=3
- some kind of navigation pane, perhaps floating on the page?
- interlink all the existing pages
- age structure per district, 2011 data
- https://funkeinteraktiv.b-cdn.net/history.v4.csv ?
- also show the aggregating measures (e.g. R_4_7, 14-days-incidence, ...) at each districts plot.
- Idea: Perhaps just repeat the table, but only that one line?
- Or perhaps even including all 50km-neighbouring areas perhaps?
- Idea: Perhaps just repeat the table, but only that one line?
- refactor all used colors into a config file
- create a more beautiful colorscheme
- in plots all fonts bigger
- amazing tables JS modifier script: datatables.net suggested here
- consistency British English <-> American English
- I am not an expert in that, please YOU make a list of such inconsistencies. OR: fork the repo, directly correct typos, and pull request. Thanks.
- translations into other languages, e.g. German
- as many people speak English well enough (and e.g. only 2.9% humans speak German), this would happen only if there is good funding for that. See about.html#support.
- use 'datacolumns' everywhere (instead of dropping some columns and hoping the remainder is what was expected). Search for TODO.
- 'dates' can be generated easily from 'datacolumns' so drop from all function interfaces; instead generate locally
- refactor & beautify "expectationday table" generation code, so it can be recycled by others more easily, and becomes more versatile, and recyclable
- comments and explanations for each Python function (usually I do that but this time it was really fast prototyping; of course will do proper documentation BUT ONLY IF there's feedback & retweeting & public attention; why bother otherwise if I am the only code user --> in short: you please promote this project, thanks.). Once that's done, submit the project to https://coronavirustechhandbook.com/
- Explain how the table coloring is created, more verbose. That the averaging leads to edge days uncolored.
- move the useful synthetic data {dummykreis, dummyland} out of the dataset into a documentation page
- Germany map with colored districts.
- interesting suggestion: colorcoded Voronoi diagram of district centers
- same as 294/401 table scraping get_wikipedia_landkreise_table() also for Liste_der_kreisfreien_Städte_in_Deutschland
- a daily report generated automatically, with the current hotspots, and their measures? Perhaps also as spoken language file?
- (generous) timeout for downloading the googlesheet - try again an hour later? Early evening it was stuck for many minutes - at night time, it went well again.
- all done
- all done
what I moved from the above to here:
- more columns: incidence - but must be smoothed over the past 5-7 days because of the strong weekend effects
- more columns: R
- more analysis options for tables: sort tables by column headers (there is a javascript for that)
- more charts: "Was noch ganz toll wäre: eine Linien-Grafik die den Verlauf der täglichen Neuinfektionen für jedes Bundesland zeigt- also mit 16 Kurven."
- link from Deutschland.html to bundeslaender_plots.html - solved now by integrating the whole table into Deutschland.html instead.
- the googlesheet table (momentary mortality / prevalence) = links from each row to each Landkreis in cov19de
- logging: remove base path from files in log
- integration: link to TU Dortmund project at each district
- integration: Wikipedia pages for most districts. missing probably only "kreisfreie städte"?
- more comfort: fix the table header row - thanks for idea to heise forum
- responsive: more responsive design for phone browsers, or small screens. perhaps wrap all tables in an iframe which limits the width, so that plots get full screen width?
- how to support the project: other than cryptocurrencies --> now: github sponsors with creditcard & paypal
- existing plots: PREVIOUSLY: the green bar is only marking a specific DAY, but the HEIGHT of the bar is unused - it could represent something, e.g. the max value of the 1 week average. Or what else ... any suggestions? If there is no good idea, better turn the bar into a large DOT - because one user got confused that the green bar also has a height. NOW: green triangle pointing down at the "expectation day"
Much more was done, see e.g. history.txt and repo commits.
Worldwide data - Python coronavirus-tracker-api https://github.com/ExpDev07/coronavirus-tracker-api
curl https://coronavirus-tracker-api.herokuapp.com/v2/locations | json_pp | grep Germany --after-context 20 --before-context 20
curl https://coronavirus-tracker-api.herokuapp.com/v2/locations/120?timelines=1 | json_pp