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This one looked like it was a bit tricky -- Nice work getting it all.
One unfortunate thing is that it doesn't seem like Utah is choosing to report much of the information that we're prioritizing now.
I'd vote to leave this on the back burner for now (and cross our fingers that they choose to make a more useful dashboard) and focus on on our short-term test coverage goals. Thoughts @sglyon @tlyon3 ?
| return ( | ||
| sorts[["dt", "negative_tests_total", "positive_tests_total"]] | ||
| .melt(id_vars=["dt"], var_name="variable_name") | ||
| .assign(vintage=pd.Timestamp.utcnow(), fips=self.state_fips) |
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We have a new method for fetching the vintage so that we are consistent in how we set the vintage. See DatasetBaseNoDate._retrieve_vintage
| .agg("sum") | ||
| .reset_index()[["dt", "cases_total", "cumulative_hospitalized"]] | ||
| .melt(id_vars=["dt"], var_name="variable_name") | ||
| .assign(vintage=pd.Timestamp.utcnow(), fips=self.state_fips) |
| } | ||
| ) | ||
| renamed["dt"] = ( | ||
| renamed["dt"].map(lambda x: pd.datetime.fromtimestamp(x / 1000)).dt.date |
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Please use the ArcGIS._esri_ts_to_dt method rather than do this by hand.
| "DISTNAME": "district", | ||
| "COVID_Cases_Total": "cases_total", | ||
| "Day": "dt", | ||
| "Hospitalizations": "cumulative_hospitalized", |
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We don't currently collect cumulative hospitalization data.
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Most of the data is at the state level. The more granular data is separated into different districts, where a district could have 1 or more counties grouped. I'm not sure how to store this data