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Extract 'Inspection Resulted in Closure' Feature from Restaurant Inspection Data #19
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Inspection Resulted in Closure
Feature from Restaurant Inspection Data
Could I ask: what sort of closures are we looking for? It seems that a lot of the inspectors will mention if the license has been suspended due to poor inspection results. Other inspections result in a cease and desist order for one component of the business, or the store entirely. Similarly, we should be looking at if a establishment has been reopened, and appropriately adjust the license start and end dates. |
This is a very good question. In our discussions with DOH I didn’t get a
nuanced interpretation of ‘temporary closure’ - I’m assuming this meant
full suspension at least. Perhaps we could derive features for each
‘level’? I could also ask our contacts at DOH for more clarification.
That’s a good point about the license period depending upon how people will
want to do the accounting. I think that in the end we will have an extra
metadata layer that provides more context around the inspections and
establishments.
…On Thu, Oct 5, 2017 at 7:21 PM smwitkowski ***@***.***> wrote:
Could I ask: what sort of closures are we looking for?
It seems that a lot of the inspectors will mention if the license has been
suspended due to poor inspection results. Other inspections result in a
cease and desist order for one component of the business, or the store
entirely.
Similarly, we should be looking at if a establishment has been reopened,
and appropriately adjust the license start and end dates.
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Migrated this issue to codefordc/the-rat-hack repository with notes to continue what has been started by the iPython notebook as issue_14. |
Start with the DC DOH Food Service Establishment Inspection report data in the
/Data Sets/Restaurant Inspections/
folder in Dropbox.Develop a script to extract the number of food establishment inspections that resulted in (temporary) closure of the establishment. More details on violations can be found here
Note that this issue depends upon the geocoding results from Issue #13
Input:
CSV files with inspection summary and violation details
Output:
A CSV file with
feature_id
: The ID for the feature, in this case, "restaurant_inspection_closures"feature_type
: Theestablishment_type
from the restaurant data setfeature_subtype
: Therisk_category
from1
-5
year
: The ISO-8601 year of the feature valueweek
: The ISO-8601 week number of the feature valuecensus_block_2010
: The 2010 Census Block of the feature valuevalue
: The value of the feature, i.e. the number of inspections that resulted in closure in establishments with the given types and risk categories in the specified week, year, and census block.When you are finished
Submit a pull request on GitHub (or upload your scripts)
Upload any files to Dropbox
Need more information?
Flag Jason or Elizabeth, or ask your question in the comments below and we'll respond as soon as we can!
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