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‎integrations/acquisition/covid_hosp/state_timeseries/test_scenarios.py

+3-3
Original file line numberDiff line numberDiff line change
@@ -53,9 +53,9 @@ def test_acquire_dataset(self):
5353
self.test_utils.load_sample_dataset()
5454

5555
# make sure the data does not yet exist
56-
# with self.subTest(name='no data yet'):
57-
# response = Epidata.covid_hosp('MA', Epidata.range(20200101, 20210101))
58-
# self.assertEqual(response['result'], -2)
56+
with self.subTest(name='no data yet'):
57+
response = Epidata.covid_hosp('MA', Epidata.range(20200101, 20210101))
58+
self.assertEqual(response['result'], -2)
5959

6060
# acquire sample data into local database
6161
with self.subTest(name='first acquisition'):

‎src/ddl/covid_hosp.sql

+2-122
Original file line numberDiff line numberDiff line change
@@ -129,7 +129,6 @@ Data is public under the Open Data Commons Open Database License (ODbL).
129129
| adult_icu_bed_utilization_coverage | int(11) | YES | | NULL | |
130130
| adult_icu_bed_utilization_numerator | int(11) | YES | | NULL | |
131131
| adult_icu_bed_utilization_denominator | int(11) | YES | | NULL | |
132-
| record_type | char(1) | NO | MUL | NULL | |
133132
+------------------------------------------------------------------+---------+------+-----+---------+----------------+
134133
135134
- `id`
@@ -504,126 +503,6 @@ which contains data from the daily snapshot files.
504503
Schema is equivalent to `covid_hosp_state_timeseries`.
505504
*/
506505
CREATE TABLE `covid_hosp_state_daily` (
507-
`id` INT NOT NULL AUTO_INCREMENT,
508-
`issue` INT NOT NULL,
509-
`state` CHAR(2) NOT NULL,
510-
`date` INT NOT NULL,
511-
`critical_staffing_shortage_today_yes` INT,
512-
`critical_staffing_shortage_today_no` INT,
513-
`critical_staffing_shortage_today_not_reported` INT,
514-
`critical_staffing_shortage_anticipated_within_week_yes` INT,
515-
`critical_staffing_shortage_anticipated_within_week_no` INT,
516-
`critical_staffing_shortage_anticipated_within_week_not_reported` INT,
517-
`hospital_onset_covid` INT,
518-
`hospital_onset_covid_coverage` INT,
519-
`inpatient_beds` INT,
520-
`inpatient_beds_coverage` INT,
521-
`inpatient_beds_used` INT,
522-
`inpatient_beds_used_coverage` INT,
523-
`inpatient_beds_used_covid` INT,
524-
`inpatient_beds_used_covid_coverage` INT,
525-
`previous_day_admission_adult_covid_confirmed` INT,
526-
`previous_day_admission_adult_covid_confirmed_coverage` INT,
527-
`previous_day_admission_adult_covid_suspected` INT,
528-
`previous_day_admission_adult_covid_suspected_coverage` INT,
529-
`previous_day_admission_pediatric_covid_confirmed` INT,
530-
`previous_day_admission_pediatric_covid_confirmed_coverage` INT,
531-
`previous_day_admission_pediatric_covid_suspected` INT,
532-
`previous_day_admission_pediatric_covid_suspected_coverage` INT,
533-
`staffed_adult_icu_bed_occupancy` INT,
534-
`staffed_adult_icu_bed_occupancy_coverage` INT,
535-
`staffed_icu_adult_patients_confirmed_suspected_covid` INT,
536-
`staffed_icu_adult_patients_confirmed_suspected_covid_coverage` INT,
537-
`staffed_icu_adult_patients_confirmed_covid` INT,
538-
`staffed_icu_adult_patients_confirmed_covid_coverage` INT,
539-
`total_adult_patients_hosp_confirmed_suspected_covid` INT,
540-
`total_adult_patients_hosp_confirmed_suspected_covid_coverage` INT,
541-
`total_adult_patients_hosp_confirmed_covid` INT,
542-
`total_adult_patients_hosp_confirmed_covid_coverage` INT,
543-
`total_pediatric_patients_hosp_confirmed_suspected_covid` INT,
544-
`total_pediatric_patients_hosp_confirmed_suspected_covid_coverage` INT,
545-
`total_pediatric_patients_hosp_confirmed_covid` INT,
546-
`total_pediatric_patients_hosp_confirmed_covid_coverage` INT,
547-
`total_staffed_adult_icu_beds` INT,
548-
`total_staffed_adult_icu_beds_coverage` INT,
549-
`inpatient_beds_utilization` DOUBLE,
550-
`inpatient_beds_utilization_coverage` INT,
551-
`inpatient_beds_utilization_numerator` INT,
552-
`inpatient_beds_utilization_denominator` INT,
553-
`percent_of_inpatients_with_covid` DOUBLE,
554-
`percent_of_inpatients_with_covid_coverage` INT,
555-
`percent_of_inpatients_with_covid_numerator` INT,
556-
`percent_of_inpatients_with_covid_denominator` INT,
557-
`inpatient_bed_covid_utilization` DOUBLE,
558-
`inpatient_bed_covid_utilization_coverage` INT,
559-
`inpatient_bed_covid_utilization_numerator` INT,
560-
`inpatient_bed_covid_utilization_denominator` INT,
561-
`adult_icu_bed_covid_utilization` DOUBLE,
562-
`adult_icu_bed_covid_utilization_coverage` INT,
563-
`adult_icu_bed_covid_utilization_numerator` INT,
564-
`adult_icu_bed_covid_utilization_denominator` INT,
565-
`adult_icu_bed_utilization` DOUBLE,
566-
`adult_icu_bed_utilization_coverage` INT,
567-
`adult_icu_bed_utilization_numerator` INT,
568-
`adult_icu_bed_utilization_denominator` INT,
569-
-- new columns added Oct 10
570-
`geocoded_state` VARCHAR(32),
571-
`previous_day_admission_adult_covid_confirmed_18_19` INT,
572-
`previous_day_admission_adult_covid_confirmed_18_19_coverage` INT,
573-
`previous_day_admission_adult_covid_confirmed_20_29` INT,
574-
`previous_day_admission_adult_covid_confirmed_20_29_coverage` INT,
575-
`previous_day_admission_adult_covid_confirmed_30_39` INT,
576-
`previous_day_admission_adult_covid_confirmed_30_39_coverage` INT,
577-
`previous_day_admission_adult_covid_confirmed_40_49` INT,
578-
`previous_day_admission_adult_covid_confirmed_40_49_coverage` INT,
579-
`previous_day_admission_adult_covid_confirmed_50_59` INT,
580-
`previous_day_admission_adult_covid_confirmed_50_59_coverage` INT,
581-
`previous_day_admission_adult_covid_confirmed_60_69` INT,
582-
`previous_day_admission_adult_covid_confirmed_60_69_coverage` INT,
583-
`previous_day_admission_adult_covid_confirmed_70_79` INT,
584-
`previous_day_admission_adult_covid_confirmed_70_79_coverage` INT,
585-
`previous_day_admission_adult_covid_confirmed_80plus` INT,
586-
`previous_day_admission_adult_covid_confirmed_80plus_coverage` INT,
587-
`previous_day_admission_adult_covid_confirmed_unknown` INT,
588-
`previous_day_admission_adult_covid_confirmed_unknown_coverage` INT,
589-
`previous_day_admission_adult_covid_suspected_18_19` INT,
590-
`previous_day_admission_adult_covid_suspected_18_19_coverage` INT,
591-
`previous_day_admission_adult_covid_suspected_20_29` INT,
592-
`previous_day_admission_adult_covid_suspected_20_29_coverage` INT,
593-
`previous_day_admission_adult_covid_suspected_30_39` INT,
594-
`previous_day_admission_adult_covid_suspected_30_39_coverage` INT,
595-
`previous_day_admission_adult_covid_suspected_40_49` INT,
596-
`previous_day_admission_adult_covid_suspected_40_49_coverage` INT,
597-
`previous_day_admission_adult_covid_suspected_50_59` INT,
598-
`previous_day_admission_adult_covid_suspected_50_59_coverage` INT,
599-
`previous_day_admission_adult_covid_suspected_60_69` INT,
600-
`previous_day_admission_adult_covid_suspected_60_69_coverage` INT,
601-
`previous_day_admission_adult_covid_suspected_70_79` INT,
602-
`previous_day_admission_adult_covid_suspected_70_79_coverage` INT,
603-
`previous_day_admission_adult_covid_suspected_80plus` INT,
604-
`previous_day_admission_adult_covid_suspected_80plus_coverage` INT,
605-
`previous_day_admission_adult_covid_suspected_unknown` INT,
606-
`previous_day_admission_adult_covid_suspected_unknown_coverage` INT,
607-
`deaths_covid` INT,
608-
`deaths_covid_coverage` INT,
609-
`on_hand_supply_therapeutic_a_casirivimab_imdevimab_courses` INT,
610-
`on_hand_supply_therapeutic_b_bamlanivimab_courses` INT,
611-
`on_hand_supply_therapeutic_c_bamlanivimab_etesevimab_courses` INT,
612-
`previous_week_therapeutic_a_casirivimab_imdevimab_courses_used` INT,
613-
`previous_week_therapeutic_b_bamlanivimab_courses_used` INT,
614-
`previous_week_therapeutic_c_bamlanivimab_etesevimab_courses_used` INT,
615-
`icu_patients_confirmed_influenza` INT,
616-
`icu_patients_confirmed_influenza_coverage` INT,
617-
`previous_day_admission_influenza_confirmed` INT,
618-
`previous_day_admission_influenza_confirmed_coverage` INT,
619-
`previous_day_deaths_covid_and_influenza` INT,
620-
`previous_day_deaths_covid_and_influenza_coverage` INT,
621-
`previous_day_deaths_influenza` INT,
622-
`previous_day_deaths_influenza_coverage` INT,
623-
`total_patients_hospitalized_confirmed_influenza` INT,
624-
`total_patients_hospitalized_confirmed_influenza_covid` INT,
625-
`total_patients_hospitalized_confirmed_influenza_covid_coverage` INT,
626-
`total_patients_hospitalized_confirmed_influenza_coverage` INT,
627506
PRIMARY KEY (`id`),
628507
-- for uniqueness
629508
-- for fast lookup of most recent issue for a given state and date
@@ -632,7 +511,8 @@ CREATE TABLE `covid_hosp_state_daily` (
632511
KEY `date_by_issue_and_state` (`issue`, `state`, `date`),
633512
-- for fast lookup of all states for a given date and issue
634513
KEY `state_by_issue_and_date` (`issue`, `date`, `state`)
635-
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
514+
) ENGINE=InnoDB DEFAULT CHARSET=utf8
515+
SELECT * FROM covid_hosp_state_timeseries;
636516

637517
/*
638518
`covid_hosp_facility` stores the versioned "facility" dataset.

‎src/ddl/migrations/covid_hosp_state_split_tables.sql

+5-130
Original file line numberDiff line numberDiff line change
@@ -1,127 +1,6 @@
11
-- 1. Add new state_daily table mirroring state_timeseries table
22

33
CREATE TABLE `covid_hosp_state_daily` (
4-
`id` INT NOT NULL AUTO_INCREMENT,
5-
`issue` INT NOT NULL,
6-
`state` CHAR(2) NOT NULL,
7-
`date` INT NOT NULL,
8-
`critical_staffing_shortage_today_yes` INT,
9-
`critical_staffing_shortage_today_no` INT,
10-
`critical_staffing_shortage_today_not_reported` INT,
11-
`critical_staffing_shortage_anticipated_within_week_yes` INT,
12-
`critical_staffing_shortage_anticipated_within_week_no` INT,
13-
`critical_staffing_shortage_anticipated_within_week_not_reported` INT,
14-
`hospital_onset_covid` INT,
15-
`hospital_onset_covid_coverage` INT,
16-
`inpatient_beds` INT,
17-
`inpatient_beds_coverage` INT,
18-
`inpatient_beds_used` INT,
19-
`inpatient_beds_used_coverage` INT,
20-
`inpatient_beds_used_covid` INT,
21-
`inpatient_beds_used_covid_coverage` INT,
22-
`previous_day_admission_adult_covid_confirmed` INT,
23-
`previous_day_admission_adult_covid_confirmed_coverage` INT,
24-
`previous_day_admission_adult_covid_suspected` INT,
25-
`previous_day_admission_adult_covid_suspected_coverage` INT,
26-
`previous_day_admission_pediatric_covid_confirmed` INT,
27-
`previous_day_admission_pediatric_covid_confirmed_coverage` INT,
28-
`previous_day_admission_pediatric_covid_suspected` INT,
29-
`previous_day_admission_pediatric_covid_suspected_coverage` INT,
30-
`staffed_adult_icu_bed_occupancy` INT,
31-
`staffed_adult_icu_bed_occupancy_coverage` INT,
32-
`staffed_icu_adult_patients_confirmed_suspected_covid` INT,
33-
`staffed_icu_adult_patients_confirmed_suspected_covid_coverage` INT,
34-
`staffed_icu_adult_patients_confirmed_covid` INT,
35-
`staffed_icu_adult_patients_confirmed_covid_coverage` INT,
36-
`total_adult_patients_hosp_confirmed_suspected_covid` INT,
37-
`total_adult_patients_hosp_confirmed_suspected_covid_coverage` INT,
38-
`total_adult_patients_hosp_confirmed_covid` INT,
39-
`total_adult_patients_hosp_confirmed_covid_coverage` INT,
40-
`total_pediatric_patients_hosp_confirmed_suspected_covid` INT,
41-
`total_pediatric_patients_hosp_confirmed_suspected_covid_coverage` INT,
42-
`total_pediatric_patients_hosp_confirmed_covid` INT,
43-
`total_pediatric_patients_hosp_confirmed_covid_coverage` INT,
44-
`total_staffed_adult_icu_beds` INT,
45-
`total_staffed_adult_icu_beds_coverage` INT,
46-
`inpatient_beds_utilization` DOUBLE,
47-
`inpatient_beds_utilization_coverage` INT,
48-
`inpatient_beds_utilization_numerator` INT,
49-
`inpatient_beds_utilization_denominator` INT,
50-
`percent_of_inpatients_with_covid` DOUBLE,
51-
`percent_of_inpatients_with_covid_coverage` INT,
52-
`percent_of_inpatients_with_covid_numerator` INT,
53-
`percent_of_inpatients_with_covid_denominator` INT,
54-
`inpatient_bed_covid_utilization` DOUBLE,
55-
`inpatient_bed_covid_utilization_coverage` INT,
56-
`inpatient_bed_covid_utilization_numerator` INT,
57-
`inpatient_bed_covid_utilization_denominator` INT,
58-
`adult_icu_bed_covid_utilization` DOUBLE,
59-
`adult_icu_bed_covid_utilization_coverage` INT,
60-
`adult_icu_bed_covid_utilization_numerator` INT,
61-
`adult_icu_bed_covid_utilization_denominator` INT,
62-
`adult_icu_bed_utilization` DOUBLE,
63-
`adult_icu_bed_utilization_coverage` INT,
64-
`adult_icu_bed_utilization_numerator` INT,
65-
`adult_icu_bed_utilization_denominator` INT,
66-
`record_type` CHAR(1) NOT NULL,
67-
-- new columns added Oct 10
68-
`geocoded_state` VARCHAR(32),
69-
`previous_day_admission_adult_covid_confirmed_18_19` INT,
70-
`previous_day_admission_adult_covid_confirmed_18_19_coverage` INT,
71-
`previous_day_admission_adult_covid_confirmed_20_29` INT,
72-
`previous_day_admission_adult_covid_confirmed_20_29_coverage` INT,
73-
`previous_day_admission_adult_covid_confirmed_30_39` INT,
74-
`previous_day_admission_adult_covid_confirmed_30_39_coverage` INT,
75-
`previous_day_admission_adult_covid_confirmed_40_49` INT,
76-
`previous_day_admission_adult_covid_confirmed_40_49_coverage` INT,
77-
`previous_day_admission_adult_covid_confirmed_50_59` INT,
78-
`previous_day_admission_adult_covid_confirmed_50_59_coverage` INT,
79-
`previous_day_admission_adult_covid_confirmed_60_69` INT,
80-
`previous_day_admission_adult_covid_confirmed_60_69_coverage` INT,
81-
`previous_day_admission_adult_covid_confirmed_70_79` INT,
82-
`previous_day_admission_adult_covid_confirmed_70_79_coverage` INT,
83-
`previous_day_admission_adult_covid_confirmed_80plus` INT,
84-
`previous_day_admission_adult_covid_confirmed_80plus_coverage` INT,
85-
`previous_day_admission_adult_covid_confirmed_unknown` INT,
86-
`previous_day_admission_adult_covid_confirmed_unknown_coverage` INT,
87-
`previous_day_admission_adult_covid_suspected_18_19` INT,
88-
`previous_day_admission_adult_covid_suspected_18_19_coverage` INT,
89-
`previous_day_admission_adult_covid_suspected_20_29` INT,
90-
`previous_day_admission_adult_covid_suspected_20_29_coverage` INT,
91-
`previous_day_admission_adult_covid_suspected_30_39` INT,
92-
`previous_day_admission_adult_covid_suspected_30_39_coverage` INT,
93-
`previous_day_admission_adult_covid_suspected_40_49` INT,
94-
`previous_day_admission_adult_covid_suspected_40_49_coverage` INT,
95-
`previous_day_admission_adult_covid_suspected_50_59` INT,
96-
`previous_day_admission_adult_covid_suspected_50_59_coverage` INT,
97-
`previous_day_admission_adult_covid_suspected_60_69` INT,
98-
`previous_day_admission_adult_covid_suspected_60_69_coverage` INT,
99-
`previous_day_admission_adult_covid_suspected_70_79` INT,
100-
`previous_day_admission_adult_covid_suspected_70_79_coverage` INT,
101-
`previous_day_admission_adult_covid_suspected_80plus` INT,
102-
`previous_day_admission_adult_covid_suspected_80plus_coverage` INT,
103-
`previous_day_admission_adult_covid_suspected_unknown` INT,
104-
`previous_day_admission_adult_covid_suspected_unknown_coverage` INT,
105-
`deaths_covid` INT,
106-
`deaths_covid_coverage` INT,
107-
`on_hand_supply_therapeutic_a_casirivimab_imdevimab_courses` INT,
108-
`on_hand_supply_therapeutic_b_bamlanivimab_courses` INT,
109-
`on_hand_supply_therapeutic_c_bamlanivimab_etesevimab_courses` INT,
110-
`previous_week_therapeutic_a_casirivimab_imdevimab_courses_used` INT,
111-
`previous_week_therapeutic_b_bamlanivimab_courses_used` INT,
112-
`previous_week_therapeutic_c_bamlanivimab_etesevimab_courses_used` INT,
113-
`icu_patients_confirmed_influenza` INT,
114-
`icu_patients_confirmed_influenza_coverage` INT,
115-
`previous_day_admission_influenza_confirmed` INT,
116-
`previous_day_admission_influenza_confirmed_coverage` INT,
117-
`previous_day_deaths_covid_and_influenza` INT,
118-
`previous_day_deaths_covid_and_influenza_coverage` INT,
119-
`previous_day_deaths_influenza` INT,
120-
`previous_day_deaths_influenza_coverage` INT,
121-
`total_patients_hospitalized_confirmed_influenza` INT,
122-
`total_patients_hospitalized_confirmed_influenza_covid` INT,
123-
`total_patients_hospitalized_confirmed_influenza_covid_coverage` INT,
124-
`total_patients_hospitalized_confirmed_influenza_coverage` INT,
1254
PRIMARY KEY (`id`),
1265
-- for uniqueness
1276
-- for fast lookup of most recent issue for a given state and date
@@ -130,19 +9,15 @@ CREATE TABLE `covid_hosp_state_daily` (
1309
KEY `date_by_issue_and_state` (`issue`, `state`, `date`),
13110
-- for fast lookup of all states for a given date and issue
13211
KEY `state_by_issue_and_date` (`issue`, `date`, `state`)
133-
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
12+
) ENGINE=InnoDB DEFAULT CHARSET=utf8
13+
SELECT * FROM covid_hosp_state_timeseries;
13414

135-
-- 2. Move data with record_type=D into new table
136-
137-
INSERT INTO `covid_hosp_state_daily`
138-
SELECT * FROM `covid_hosp_state_timeseries`
139-
WHERE record_type='D';
140-
141-
-- 3. Remove that data from the old table
15+
-- 2. Remove data with incorrect record_type from both tables (keep D in daily, T in timeseries)
14216

14317
DELETE FROM `covid_hosp_state_timeseries` WHERE record_type='D';
18+
DELETE FROM `covid_hosp_state_daily` WHERE record_type='T';
14419

145-
-- 4. Remove the record_type column from both tables
20+
-- 3. Remove the record_type column from both tables
14621

14722
ALTER TABLE `covid_hosp_state_daily` DROP COLUMN record_type;
14823
ALTER TABLE `covid_hosp_state_timeseries` DROP COLUMN record_type;

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