caseymm / django-ebola Goto Github PK

Whether it comes as pdf or json, what's the best way to use it?

• Possible to do something with rate of change over time if we grab as many previous ones as we can and load them all in?

possibly just create a text field to hold the array or such on the location model?

• summary view of location stats
• list view of sitreps
• detail view sitreps
• list view of locations
• detail view of locations

Is any of this data worth cataloging?

• would be able to save locations and geocode them - wouldn't be live query, but would be quicker than geocoding in browser
• take a look at what other data they provide that may be useful outside of mapping

No rush, just for the next data load whenever that is...
For the sparkline data can you remove the quote from the value (not the key) so it is just the array that includes the [ ] of new_weekly_deaths and new_weekly_cases?

ex.
"new_weekly_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 6, 4, 2, 4, 15, 1],

for your refrence from a previous email:
for sparkline/'aaData'
ex) {"aaData": [{"cases_cum": 63, "new_weekly_deaths": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 6, 4, 2, 4, 15, 1]", "total_deaths_all": 34,...
http://django-ebola.herokuapp.com/data/?format=table_sparkline_ex_natl

Documents is broken. Not critical to function, but would be nice to have.

have:

main_weekly.json
main_daily.json

Currently broken down by location/date. Each of those entries has fk to location and to date.

Do we want to keep doing it this way, or have one giant model? Not sure what would be best considering what type of data/json we want to pull out.

• create email
• look at: https://django-data-importer.readthedocs.org/en/latest/readme.html
• in tandem with: http://tomatohater.com/2012/01/17/custom-django-management-commands-on-heroku/
• call email at end of single load command
• TABLED: check this out: http://django.readthedocs.org/en/latest/topics/http/file-uploads.html

with one entry

export json

regional_drilldown.json

{
"aaData": [{"daily_deaths": [0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, -2, 0, 0, 5, 0, -8, 0, 0, 0, 0], "cases_cum": 63, "total_deaths_all": 34, "hcw_cases_cum": 5, "hcw_deaths_cum": 4, "location__name": "Bomi County", "daily_cases": [0, 2, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 4, 0, 19, 0, 0, 0, 0]}, {"daily_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "cases_cum": 3, "total_deaths_all": 2, "hcw_cases_cum": 0, "hcw_deaths_cum": 0, "location__name": "Grand Gedeh", "daily_cases": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, {"daily_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0], "cases_cum": 46, "total_deaths_all": 19, "hcw_cases_cum": 3, "hcw_deaths_cum": 1, "location__name": "Grand Bassa", "daily_cases": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 6, 0, 0]}, {"daily_deaths": [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 0, 0, 0, 0, 0, 0, 0, 2], "cases_cum": 147, "total_deaths_all": 41, "hcw_cases_cum": 26, "hcw_deaths_cum": 5, "location__name": "Bong County", "daily_cases": [0, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 3]}, {"daily_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "cases_cum": 0, "total_deaths_all": 0, "hcw_cases_cum": 0, "hcw_deaths_cum": 0, "location__name": "Grand Kru", "daily_cases": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, {"daily_deaths": [0, 5, 0, 0, 0, 0, 0, 35, 29, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "cases_cum": 576, "total_deaths_all": 437, "hcw_cases_cum": 59, "hcw_deaths_cum": 28, "location__name": "Montserrado County", "daily_cases": [0, 16, 0, 0, 0, 0, 0, 22, 35, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11]}, {"daily_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "cases_cum": 108, "total_deaths_all": 72, "hcw_cases_cum": 3, "hcw_deaths_cum": 0, "location__name": "Nimba County", "daily_cases": [0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 5, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]}, {"daily_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "cases_cum": 1, "total_deaths_all": 0, "hcw_cases_cum": 0, "hcw_deaths_cum": 0, "location__name": "Gbarpolu County", "daily_cases": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, {"daily_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "cases_cum": 2, "total_deaths_all": 0, "hcw_cases_cum": 0, "hcw_deaths_cum": 0, "location__name": "Sinoe County", "daily_cases": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, {"daily_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "cases_cum": 9, "total_deaths_all": 5, "hcw_cases_cum": 0, "hcw_deaths_cum": 0, "location__name": "River Gee County", "daily_cases": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0]}, {"daily_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1], "cases_cum": 10, "total_deaths_all": 9, "hcw_cases_cum": 3, "hcw_deaths_cum": 0, "location__name": "Grand Cape Mount", "daily_cases": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0]}, {"daily_deaths": [10, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8], "cases_cum": 628, "total_deaths_all": 320, "hcw_cases_cum": 20, "hcw_deaths_cum": 17, "location__name": "Lofa County", "daily_cases": [30, 0, 0, 0, 0, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 40, 31]}, {"daily_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "cases_cum": 0, "total_deaths_all": 0, "hcw_cases_cum": 0, "hcw_deaths_cum": 0, "location__name": "Maryland County", "daily_cases": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, {"daily_deaths": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "cases_cum": 1, "total_deaths_all": 1, "hcw_cases_cum": 0, "hcw_deaths_cum": 0, "location__name": "RiverCess County", "daily_cases": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, {"daily_deaths": [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8], "cases_cum": 245, "total_deaths_all": 111, "hcw_cases_cum": 32, "hcw_deaths_cum": 19, "location__name": "Margibi County", "daily_cases": [14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 19]}]
}

• fix file path
• auto update data on form submit
• check live db
• push heroku master

• use Max to get total deaths for each week
• before save, get this week total minus last week total
• save that to week as new total

Make standard json file with cases and deaths as separate lists:
dictionary keys

{
"deaths":{"total_deaths": [0, 17, 0, 3, 3, 2, 0, 34, 37, 0, 135, 11, 5, 0, 0]},{name: total_deaths_confirmed,data: [19, 11, 0, 13, 4, 0, 0, 146, 25, 0, 169, 27, 0, 0, 0]},{name: total_deaths_probable,data: [15, 13, 0, 3, 2, 0, 0, 140, 49, 0, 133, 34, 0, 1, 0]
},
"cases":{
[{"name: cases_cum_probable,data:" [31, 40, 0, 12, 4, 0, 0, 345, 89, 0, 309, 50, 3, 0, 0]},{name: cases_cum_confirmed,data: [31, 24, 0, 13, 4, 0, 0, 220, 30, 0, 225, 41, 0, 1, 1]},{name: cases_cum_suspected,data: [1, 83, 1, 21, 2, 3, 0, 63, 126, 0, 42, 17, 6, 0, 1]}]
}
}

?format=json&fields=deaths,cases_cum,hcw_cases_cum

• generate for each date (list and detail just like for locations)
• supply 'latest' url that will redirect to supplied SitRep.objects.latest('formatted_date')

looking fun...