Query the Data Delivery Network
Query the DDNThe easiest way to query any data on Splitgraph is via the "Data Delivery Network" (DDN). The DDN is a single endpoint that speaks the PostgreSQL wire protocol. Any Splitgraph user can connect to it at data.splitgraph.com:5432 and query any version of over 40,000 datasets that are hosted or proxied by Splitgraph.
For example, you can query the covid19_reported_patient_impact_and_hospital table in this repository, by referencing it like:
"healthdata-gov/covid19-reported-patient-impact-and-hospital-6xf2-c3ie:latest"."covid19_reported_patient_impact_and_hospital"or in a full query, like:
SELECT
":id", -- Socrata column ID
"previous_day_admission_adult_covid_suspected_18_19_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 suspected age 18-19 years
"total_staffed_pediatric_icu_beds_coverage", -- Total number of pediatric ICU beds in the facility that are currently set-up, staffed and are or could be used for a patient within the reporting period (coverage). This count includes occupied and unoccupied ICU beds, including any ICU beds that are, or could be, staffed and used for a pediatric patient. This count excludes NICU, newborn nursery, and outpatient surgery beds. This is a subset of #3c and #5a. Any beds counted in #5c should NOT be counted in #5b. This field is required as of 2/2/2022. Note: All pediatric ICU beds should be considered, regardless of the unit on which the bed is housed. This includes ICU beds located in non-ICU locations, such as mixed acuity units.
"total_staffed_pediatric_icu_beds", -- Total number of pediatric ICU beds in the facility that are currently set-up, staffed and are or could be used for a patient within the reporting period. This count includes occupied and unoccupied ICU beds, including any ICU beds that are, or could be, staffed and used for a pediatric patient. This count excludes NICU, newborn nursery, and outpatient surgery beds. This is a subset of #3c and #5a. Any beds counted in #5c should NOT be counted in #5b. This field is required as of 2/2/2022. Note: All pediatric ICU beds should be considered, regardless of the unit on which the bed is housed. This includes ICU beds located in non-ICU locations, such as mixed acuity units.
"staffed_pediatric_icu_bed_occupancy_coverage", -- Total number of set-up and staffed pediatric ICU beds occupied by a patient (coverage). This count excludes NICU, newborn nursery, and outpatient surgery beds. This is subset of #4c and #6a. This field is required as of 2/2/2022. Note: All occupied pediatric ICU beds should be considered, regardless of the unit on which the bed is housed. This includes ICU beds located in non-ICU locations, such as mixed acuity units.
"previous_day_admission_pediatric_covid_confirmed_unknown_covera", -- Enter the number of patients, by age group, who were admitted to an inpatient or ICU bed on the previous calendar day who had laboratory-confirmed COVID19 at the time of admission (coverage). The summary of age breakdowns should be identical to #18a. This includes patients ages 0-4, 5-11, and 12-17 years old admitted to any inpatient bed, regardless of whether the bed is designated as pediatric vs. adult. This field is required as of 2/2/2022. See Appendix D for the definition of laboratory-confirmed COVID-19.
"all_pediatric_inpatient_beds_coverage", -- Total number of pediatric beds in the facility that are currently set-up, staffed and able to be used for a patient within the reporting period (coverage). This count includes occupied and unoccupied inpatient pediatric beds including both PICU and med-surge beds (beds in which medical or surgical pediatric patients may be routinely placed). Include any surge/hallway/overflow beds that are open for use for a patient, regardless of whether they are occupied or available. This count excludes NICU, newborn nursery beds, and outpatient surgery beds. This is a subset of #3a. This field is required as of 2/2/2022.
"all_pediatric_inpatient_beds", -- Total number of pediatric beds in the facility that are currently set-up, staffed and able to be used for a patient within the reporting period. This count includes occupied and unoccupied inpatient pediatric beds including both PICU and med-surge beds (beds in which medical or surgical pediatric patients may be routinely placed). Include any surge/hallway/overflow beds that are open for use for a patient, regardless of whether they are occupied or available. This count excludes NICU, newborn nursery beds, and outpatient surgery beds. This is a subset of #3a. This field is required as of 2/2/2022.
"deaths_covid_coverage", -- The number of hospital facilities that reported deaths_covid for the given time period.
"previous_day_admission_adult_covid_suspected_unknown_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 suspected age unknown
"previous_day_admission_adult_covid_suspected_30_39_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 suspected age 30-39 years
"previous_day_admission_adult_covid_confirmed_unknown_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 confirmed age unknown
"previous_day_admission_adult_covid_confirmed_20_29_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 confirmed age 20-29 years
"adult_icu_bed_utilization_denominator", -- 59. Sum of "total_staffed_adult_icu_beds" for hospitals reporting both "staffed_adult_icu_bed_occupancy" and "total_staffed_adult_icu_beds".
"adult_icu_bed_utilization", -- 56. Percentage of staffed adult ICU beds that are being utilized in this state. This number only accounts for hospitals in the state that report both "staffed_adult_icu_bed_occupancy" and "total_staffed_adult_icu_beds" fields.
"adult_icu_bed_covid_utilization", -- 52. Percentage of total staffed adult ICU beds currently utilized by patients who have suspected or confirmed COVID-19 in this state. This number only accounts for hospitals in the state that report both "staffed_icu_adult_patients_confirmed_and_suspected_covid" and "total_staffed_adult_icu_beds" fields.
"inpatient_bed_covid_utilization", -- 48. Percentage of total (used/available) inpatient beds currently utilized by patients who have suspected or confirmed COVID-19 in this state. This number only accounts for hospitals in the state that report both "inpatient_beds_used_covid" and "inpatient_beds" fields.
"inpatient_beds_utilization_numerator", -- 42. Sum of "inpatient_beds_used" for hospitals reporting both "inpatient_beds_used" and "inpatient_beds"
"total_pediatric_patients_hospitalized_confirmed_covid", -- 36. Reported patients currently hospitalized in a pediatric inpatient bed, including NICU, newborn, and nursery, who are laboratory-confirmed-positive for COVID-19. This include those in observation beds.
"staffed_adult_icu_bed_occupancy_coverage", -- 25. Number of hospitals reporting "staffed_adult_icu_bed_occupancy" in this state
"previous_day_admission_adult_covid_suspected", -- 18. Number of patients who were admitted to an adult inpatient bed on the previous calendar day who had suspected COVID-19 at the time of admission in this state
"hospital_onset_covid", -- 8. Total current inpatients with onset of suspected or laboratory-confirmed COVID-19 fourteen or more days after admission for a condition other than COVID-19 in this state.
"all_pediatric_inpatient_bed_occupied_coverage", -- Total number of set-up and staffed inpatient pediatric beds that are occupied by a patient (coverage). Includes both PICU and med-surge beds (beds in which medical or surgical pediatric patients may be routinely placed). Include any occupied surge/hallway/overflow beds that are open for use. This count excludes NICU, newborn nursery, and outpatient surgery beds. This is a subset of #4a, and reflects occupancy levels for beds reported in #3c. This field is required as of 2/2/2022.
"all_pediatric_inpatient_bed_occupied", -- Total number of set-up and staffed inpatient pediatric beds that are occupied by a patient. Includes both PICU and med-surge beds (beds in which medical or surgical pediatric patients may be routinely placed). Include any occupied surge/hallway/overflow beds that are open for use. This count excludes NICU, newborn nursery, and outpatient surgery beds. This is a subset of #4a, and reflects occupancy levels for beds reported in #3c. This field is required as of 2/2/2022.
"previous_day_admission_adult_covid_suspected_50_59_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 suspected age 50-59 years
"previous_day_admission_adult_covid_suspected_18_19", -- Number of patients admitted to adult inpatient bed on previous calendar day with suspected COVID-19, age 18-19 years
"percent_of_inpatients_with_covid", -- 44. Percentage of inpatient population who have suspected or confirmed COVID-19 in this state. This number only accounts for hospitals in the state that report both "inpatient_beds_used_covid" and "inpatient_beds_used" fields.
"previous_day_admission_pediatric_covid_confirmed_0_4_coverage", -- Enter the number of patients, by age group, who were admitted to an inpatient or ICU bed on the previous calendar day who had laboratory-confirmed COVID19 at the time of admission (coverage). The summary of age breakdowns should be identical to #18a. This includes patients ages 0-4, 5-11, and 12-17 years old admitted to any inpatient bed, regardless of whether the bed is designated as pediatric vs. adult. This field is required as of 2/2/2022. See Appendix D for the definition of laboratory-confirmed COVID-19.
"previous_day_admission_adult_covid_suspected_50_59", -- Number of patients admitted to adult inpatient bed on previous calendar day with suspected COVID-19, age 50-59 years
"previous_day_admission_adult_covid_confirmed_80_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 confirmed age 80+ years
"previous_day_admission_adult_covid_confirmed_20_29", -- Number of patients admitted to adult inpatient bed on previous calendar day with confirmed COVID-19, age 20-29 years
"previous_day_admission_adult_covid_suspected_80", -- Number of patients admitted to adult inpatient bed on previous calendar day with suspected COVID-19, age 80 years and older
"previous_day_admission_adult_covid_confirmed_40_49_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 confirmed age 40-49 years
"adult_icu_bed_covid_utilization_numerator", -- 54. Sum of "staffed_icu_adult_patients_confirmed_and_suspected_covid" for hospitals reporting both "staffed_icu_adult_patients_confirmed_and_suspected_covid" and "total_staffed_adult_icu_beds".
"date", -- The date of the report
"staffed_icu_pediatric_patients_confirmed_covid_coverage", -- Total number of pediatric ICU beds occupied by laboratory confirmed positive COVID-19 patients (coverage). This is a subset of #6c, occupied pediatric ICU beds. This count excludes NICU, newborn nursery, and outpatient surgery beds. This field is required as of 2/2/2022. See Appendix D for the definition of laboratory-confirmed COVID-19.
"previous_day_admission_pediatric_covid_confirmed_0_4", -- Enter the number of patients, by age group, who were admitted to an inpatient or ICU bed on the previous calendar day who had laboratory-confirmed COVID19 at the time of admission. The summary of age breakdowns should be identical to #18a. This includes patients ages 0-4, 5-11, and 12-17 years old admitted to any inpatient bed, regardless of whether the bed is designated as pediatric vs. adult. This field is required as of 2/2/2022. See Appendix D for the definition of laboratory-confirmed COVID-19.
"previous_day_admission_adult_covid_confirmed_70_79_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 confirmed age 70-79 years
"previous_day_admission_influenza_confirmed_coverage", -- Previous day admission influenza confirmed coverage
"previous_day_admission_adult_covid_suspected_30_39", -- Number of patients admitted to adult inpatient bed on previous calendar day with suspected COVID-19, age 30-39 years
"previous_day_admission_adult_covid_confirmed_unknown", -- Number of patients admitted to adult inpatient bed on previous calendar day with confirmed COVID-19, age unknown
"staffed_pediatric_icu_bed_occupancy", -- Total number of set-up and staffed pediatric ICU beds occupied by a patient. This count excludes NICU, newborn nursery, and outpatient surgery beds. This is subset of #4c and #6a. This field is required as of 2/2/2022. Note: All occupied pediatric ICU beds should be considered, regardless of the unit on which the bed is housed. This includes ICU beds located in non-ICU locations, such as mixed acuity units.
"staffed_icu_pediatric_patients_confirmed_covid", -- Total number of pediatric ICU beds occupied by laboratory confirmed positive COVID-19 patients. This is a subset of #6c, occupied pediatric ICU beds. This count excludes NICU, newborn nursery, and outpatient surgery beds. This field is required as of 2/2/2022. See Appendix D for the definition of laboratory-confirmed COVID-19.
"previous_day_admission_pediatric_covid_confirmed_unknown", -- Enter the number of patients, by age group, who were admitted to an inpatient or ICU bed on the previous calendar day who had laboratory-confirmed COVID19 at the time of admission. The summary of age breakdowns should be identical to #18a. This includes patients ages 0-4, 5-11, and 12-17 years old admitted to any inpatient bed, regardless of whether the bed is designated as pediatric vs. adult. This field is required as of 2/2/2022. See Appendix D for the definition of laboratory-confirmed COVID-19.
"previous_day_admission_pediatric_covid_confirmed_5_11_coverage", -- Enter the number of patients, by age group, who were admitted to an inpatient or ICU bed on the previous calendar day who had laboratory-confirmed COVID19 at the time of admission (coverage). The summary of age breakdowns should be identical to #18a. This includes patients ages 0-4, 5-11, and 12-17 years old admitted to any inpatient bed, regardless of whether the bed is designated as pediatric vs. adult. This field is required as of 2/2/2022. See Appendix D for the definition of laboratory-confirmed COVID-19.
"previous_day_admission_pediatric_covid_confirmed_5_11", -- Enter the number of patients, by age group, who were admitted to an inpatient or ICU bed on the previous calendar day who had laboratory-confirmed COVID19 at the time of admission. The summary of age breakdowns should be identical to #18a. This includes patients ages 0-4, 5-11, and 12-17 years old admitted to any inpatient bed, regardless of whether the bed is designated as pediatric vs. adult. This field is required as of 2/2/2022. See Appendix D for the definition of laboratory-confirmed COVID-19.
"previous_day_admission_pediatric_covid_confirmed_12_17_coverage", -- Enter the number of patients, by age group, who were admitted to an inpatient or ICU bed on the previous calendar day who had laboratory-confirmed COVID19 at the time of admission (coverage). The summary of age breakdowns should be identical to #18a. This includes patients ages 0-4, 5-11, and 12-17 years old admitted to any inpatient bed, regardless of whether the bed is designated as pediatric vs. adult. This field is required as of 2/2/2022. See Appendix D for the definition of laboratory-confirmed COVID-19.
"previous_day_admission_pediatric_covid_confirmed_12_17", -- Enter the number of patients, by age group, who were admitted to an inpatient or ICU bed on the previous calendar day who had laboratory-confirmed COVID19 at the time of admission. The summary of age breakdowns should be identical to #18a. This includes patients ages 0-4, 5-11, and 12-17 years old admitted to any inpatient bed, regardless of whether the bed is designated as pediatric vs. adult. This field is required as of 2/2/2022. See Appendix D for the definition of laboratory-confirmed COVID-19.
"total_patients_hospitalized_confirmed_influenza_coverage", -- total patients hospitalized confirmed influenza coverage
"total_patients_hospitalized_confirmed_influenza_and_covid_cover", -- total patients hospitalized confirmed influenza and COVID coverage
"total_patients_hospitalized_confirmed_influenza_and_covid", -- total patients hospitalized confirmed influenza and covid
"total_patients_hospitalized_confirmed_influenza", -- total patients hospitalized confirmed influenza
"previous_day_deaths_influenza_coverage", -- Previous Day Deaths Influenza Coverage
"previous_day_deaths_influenza", -- Previous Day Deaths Influenza
"previous_day_deaths_covid_and_influenza_coverage", -- Previous Day Deaths covid and influenza coverage
"previous_day_deaths_covid_and_influenza", -- Previous day deaths covid and influenza
"previous_day_admission_influenza_confirmed", -- Previous day admission influenza confirmed
"icu_patients_confirmed_influenza_coverage", -- Number of ICU patients confirmed with influenza coverage
"icu_patients_confirmed_influenza", -- Number of ICU patients confirmed with influenza
"previous_week_therapeutic_c_bamlanivimab_etesevimab_courses_use", -- previous week onhand therapeutic c
"previous_week_therapeutic_b_bamlanivimab_courses_used", -- previous week onhand supply therapeutic b
"previous_week_therapeutic_a_casirivimab_imdevimab_courses_used", -- previous week onhand supply therapeutic a
"on_hand_supply_therapeutic_c_bamlanivimab_etesevimab_courses", -- onhand supply therapeutic c
"on_hand_supply_therapeutic_b_bamlanivimab_courses", -- onhand supply therapeutic b
"on_hand_supply_therapeutic_a_casirivimab_imdevimab_courses", -- onhand supply therapeutic a
"deaths_covid", -- Number of patients with suspected or confirmed COVID-19 who died on the previous calendar day in the hospital, ED, or overflow location
"previous_day_admission_adult_covid_suspected_80_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 suspected age 80+ years
"previous_day_admission_adult_covid_suspected_70_79_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 suspected age 70-79 years
"previous_day_admission_adult_covid_suspected_70_79", -- Number of patients admitted to adult inpatient bed on previous calendar day with suspected COVID-19, age 70-79 years
"previous_day_admission_adult_covid_suspected_60_69_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 suspected age 60-69 years
"previous_day_admission_adult_covid_suspected_60_69", -- Number of patients admitted to adult inpatient bed on previous calendar day with suspected COVID-19, age 60-69 years
"previous_day_admission_adult_covid_suspected_40_49_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 suspected age 40-49 years
"previous_day_admission_adult_covid_suspected_40_49", -- Number of patients admitted to adult inpatient bed on previous calendar day with suspected COVID-19, age 40-49 years
"previous_day_admission_adult_covid_suspected_20_29_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 suspected age 20-29 years
"previous_day_admission_adult_covid_suspected_20_29", -- Number of patients admitted to adult inpatient bed on previous calendar day with suspected COVID-19, age 20-29 years
"previous_day_admission_adult_covid_confirmed_80_", -- Number of patients admitted to adult inpatient bed on previous calendar day with confirmed COVID-19, age 80 years and older
"previous_day_admission_adult_covid_confirmed_70_79", -- Number of patients admitted to adult inpatient bed on previous calendar day with confirmed COVID-19, age 70-79 years
"previous_day_admission_adult_covid_confirmed_60_69_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 confirmed age 60-69 years
"previous_day_admission_adult_covid_confirmed_60_69", -- Number of patients admitted to adult inpatient bed on previous calendar day with confirmed COVID-19, age 60-69 years
"previous_day_admission_adult_covid_confirmed_50_59_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 confirmed age 50-59 years
"previous_day_admission_adult_covid_confirmed_50_59", -- Number of patients admitted to adult inpatient bed on previous calendar day with confirmed COVID-19, age 50-59 years
"previous_day_admission_adult_covid_confirmed_40_49", -- Number of patients admitted to adult inpatient bed on previous calendar day with confirmed COVID-19, age 40-49 years
"previous_day_admission_adult_covid_confirmed_30_39_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 confirmed age 30-39 years
"previous_day_admission_adult_covid_confirmed_30_39", -- Number of patients admitted to adult inpatient bed on previous calendar day with confirmed COVID-19, age 30-39 years
"previous_day_admission_adult_covid_confirmed_18_19_coverage", -- Number of hospitals reporting previous day admission adult COVID-19 confirmed age 18-19 years
"previous_day_admission_adult_covid_confirmed_18_19", -- Number of patients admitted to adult inpatient bed on previous calendar day with confirmed COVID-19, age 18-19 years
"adult_icu_bed_utilization_numerator", -- 58. Sum of "staffed_adult_icu_bed_occupancy" for hospitals reporting both "staffed_adult_icu_bed_occupancy" and "total_staffed_adult_icu_beds".
"adult_icu_bed_utilization_coverage", -- 57. Number of hospitals reporting both both "staffed_adult_icu_bed_occupancy" and "total_staffed_adult_icu_beds".
"adult_icu_bed_covid_utilization_denominator", -- 55. Sum of "total_staffed_adult_icu_beds" for hospitals reporting both "staffed_icu_adult_patients_confirmed_and_suspected_covid" and "total_staffed_adult_icu_beds".
"adult_icu_bed_covid_utilization_coverage", -- 53. Number of hospitals reporting both both "staffed_icu_adult_patients_confirmed_and_suspected_covid" and "total_staffed_adult_icu_beds".
"inpatient_bed_covid_utilization_denominator", -- 51. Sum of "inpatient_beds" for hospitals reporting both "inpatient_beds_used_covid" and "inpatient_beds".
"inpatient_bed_covid_utilization_numerator", -- 50. Sum of "inpatient_beds_used_covid" for hospitals reporting both "inpatient_beds_used_covid" and "inpatient_beds".
"inpatient_bed_covid_utilization_coverage", -- 49. Number of hospitals reporting both "inpatient_beds_used_covid" and "inpatient_beds".
"percent_of_inpatients_with_covid_denominator", -- 47. Sum of "inpatient_beds_used" for hospitals reporting both "inpatient_beds_used_covid" and "inpatient_beds_used".
"percent_of_inpatients_with_covid_numerator", -- 46. Sum of "inpatient_beds_used_covid" for hospitals reporting both "inpatient_beds_used_covid" and "inpatient_beds_used".
"percent_of_inpatients_with_covid_coverage", -- 45. Number of hospitals reporting both "inpatient_beds_used_covid" and "inpatient_beds_used".
"inpatient_beds_utilization_denominator", -- 43. Sum of "inpatient_beds" for hospitals reporting both "inpatient_beds_used" and "inpatient_beds"
"inpatient_beds_utilization_coverage", -- 41. Number of hospitals reporting both "inpatient_beds_used" and "inpatient_beds"
"inpatient_beds_utilization", -- 40. Percentage of inpatient beds that are being utilized in this state. This number only accounts for hospitals in the state that report both "inpatient_beds_used" and "inpatient_beds" fields.
"total_staffed_adult_icu_beds_coverage", -- 39. Number of hospitals reporting "total_staffed_adult_icu_beds" in this state
"total_staffed_adult_icu_beds", -- 38. Reported total number of staffed inpatient adult ICU beds in this state
"total_pediatric_patients_hospitalized_confirmed_covid_coverage", -- 37. Number of hospitals reporting "total_pediatric_patients_hospitalized_confirmed_covid" in this state
"total_pediatric_patients_hospitalized_confirmed_and_suspect_000", -- 35. Number of hospitals reporting "total_pediatric_patients_hospitalized_confirmed_and_suspected_covid" in this state
"total_pediatric_patients_hospitalized_confirmed_and_suspect_001", -- 34. Reported patients currently hospitalized in a pediatric inpatient bed, including NICU, newborn, and nursery, who are suspected or laboratory-confirmed-positive for COVID-19. This include those in observation beds.
"total_adult_patients_hospitalized_confirmed_covid_coverage", -- 33. Number of hospitals reporting "total_adult_patients_hospitalized_confirmed_covid" in this state
"total_adult_patients_hospitalized_confirmed_covid", -- 32. Reported patients currently hospitalized in an adult inpatient bed who have laboratory-confirmed COVID-19. This include those in observation beds.
"total_adult_patients_hospitalized_confirmed_and_suspected_c_000", -- 31. Number of hospitals reporting "total_adult_patients_hospitalized_confirmed_and_suspected_covid" in this state
"total_adult_patients_hospitalized_confirmed_and_suspected_c_001", -- 30. Reported patients currently hospitalized in an adult inpatient bed who have laboratory-confirmed or suspected COVID-19. This include those in observation beds.
"staffed_icu_adult_patients_confirmed_covid_coverage", -- 29. Number of hospitals reporting "staffed_icu_adult_patients_confirmed_covid" in this state
"staffed_icu_adult_patients_confirmed_covid", -- 28. Reported patients currently hospitalized in an adult ICU bed who have confirmed COVID-19 in this state
"staffed_icu_adult_patients_confirmed_and_suspected_covid_covera", -- 27. Number of hospitals reporting "staffed_icu_adult_patients_confirmed_and_suspected_covid" in this state
"staffed_icu_adult_patients_confirmed_and_suspected_covid", -- 26. Reported patients currently hospitalized in an adult ICU bed who have suspected or confirmed COVID-19 in this state
"staffed_adult_icu_bed_occupancy", -- 24. Reported total number of staffed inpatient adult ICU beds that are occupied in this state
"previous_day_admission_pediatric_covid_suspected_coverage", -- 23. Number of hospitals reporting "previous_day_admission_pediatric_covid_suspected" in this state
"previous_day_admission_pediatric_covid_suspected", -- 22. Number of pediatric patients who were admitted to an inpatient bed, including NICU, PICU, newborn, and nursery, on the previous calendar day who had suspected COVID-19 at the time of admission in this state
"previous_day_admission_pediatric_covid_confirmed_coverage", -- 21. Number of hospitals reporting "previous_day_admission_pediatric_covid_confirmed" in this state
"previous_day_admission_pediatric_covid_confirmed", -- 20. Number of pediatric patients who were admitted to an inpatient bed, including NICU, PICU, newborn, and nursery, on the previous calendar day who had confirmed COVID-19 at the time of admission in this state
"previous_day_admission_adult_covid_suspected_coverage", -- 19. Number of hospitals reporting "previous_day_admission_adult_covid_suspected" in this state
"previous_day_admission_adult_covid_confirmed_coverage", -- 17. Number of hospitals reporting "previous_day_admission_adult_covid_confirmed" in this state
"previous_day_admission_adult_covid_confirmed", -- 16. Number of patients who were admitted to an adult inpatient bed on the previous calendar day who had confirmed COVID-19 at the time of admission in this state
"inpatient_beds_used_covid_coverage", -- 15. Number of hospitals reporting "inpatient_beds_used_covid" in this state
"inpatient_beds_used_covid", -- 14. Reported patients currently hospitalized in an inpatient bed who have suspected or confirmed COVID-19 in this state
"inpatient_beds_used_coverage", -- 13. Number of hospitals reporting "inpatient_beds_used" in this state
"inpatient_beds_used", -- 12. Reported total number of staffed inpatient beds that are occupied in this state
"inpatient_beds_coverage", -- 11. Number of hospitals reporting "inpatient_beds" in this state
"inpatient_beds", -- 10. Reported total number of staffed inpatient beds including all overflow and surge/expansion beds used for inpatients (includes all ICU beds) in this state
"hospital_onset_covid_coverage", -- 9. Number of hospitals reporting "hospital_onset_covid" in this state
"critical_staffing_shortage_anticipated_within_week_not_reported", -- 7. Number of hospitals not reporting staffing shortage within week status in this state.
"critical_staffing_shortage_anticipated_within_week_no", -- 6. Number of hospitals reporting that they do not anticipate a critical staffing shortage within a week in this state.
"critical_staffing_shortage_anticipated_within_week_yes", -- 5. Number of hospitals reporting that they anticipate a critical staffing shortage within a week in this state.
"critical_staffing_shortage_today_no", -- 3. Number of hospitals reporting as not having a critical staffing shortage today in this state.
"critical_staffing_shortage_today_yes", -- 2. Number of hospitals reporting a critical staffing shortage today in this state.
"state", -- 1. The two digit state code
"critical_staffing_shortage_today_not_reported", -- 4. Number of hospitals not reporting staffing shortage today status in this state.
"previous_day_admission_adult_covid_suspected_unknown", -- Number of patients admitted to adult inpatient bed on previous calendar day with suspected COVID-19, age unknown
"geocoded_state",
":@computed_region_pqdx_y6mm"
FROM
"healthdata-gov/covid19-reported-patient-impact-and-hospital-6xf2-c3ie:latest"."covid19_reported_patient_impact_and_hospital"
LIMIT 100;Connecting to the DDN is easy. All you need is an existing SQL client that can connect to Postgres. As long as you have a SQL client ready, you'll be able to query healthdata-gov/covid19-reported-patient-impact-and-hospital-6xf2-c3ie with SQL in under 60 seconds.
Query Your Local Engine
Install Splitgraph Locally
bash -c "$(curl -sL https://github.com/splitgraph/splitgraph/releases/latest/download/install.sh)"Read the installation docs.
Splitgraph Cloud is built around Splitgraph Core (GitHub), which includes a local Splitgraph Engine packaged as a Docker image. Splitgraph Cloud is basically a scaled-up version of that local Engine. When you query the Data Delivery Network or the REST API, we mount the relevant datasets in an Engine on our servers and execute your query on it.
It's possible to run this engine locally. You'll need a Mac, Windows or Linux system to install sgr, and a Docker installation to run the engine. You don't need to know how to actually use Docker; sgrcan manage the image, container and volume for you.
There are a few ways to ingest data into the local engine.
For external repositories, the Splitgraph Engine can "mount" upstream data sources by using sgr mount. This feature is built around Postgres Foreign Data Wrappers (FDW). You can write custom "mount handlers" for any upstream data source. For an example, we blogged about making a custom mount handler for HackerNews stories.
For hosted datasets (like this repository), where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.
Cloning Data
Because healthdata-gov/covid19-reported-patient-impact-and-hospital-6xf2-c3ie:latest is a Splitgraph Image, you can clone the data from Spltgraph Cloud to your local engine, where you can query it like any other Postgres database, using any of your existing tools.
First, install Splitgraph if you haven't already.
Clone the metadata with sgr clone
This will be quick, and does not download the actual data.
sgr clone healthdata-gov/covid19-reported-patient-impact-and-hospital-6xf2-c3ieCheckout the data
Once you've cloned the data, you need to "checkout" the tag that you want. For example, to checkout the latest tag:
sgr checkout healthdata-gov/covid19-reported-patient-impact-and-hospital-6xf2-c3ie:latestThis will download all the objects for the latest tag of healthdata-gov/covid19-reported-patient-impact-and-hospital-6xf2-c3ie and load them into the Splitgraph Engine. Depending on your connection speed and the size of the data, you will need to wait for the checkout to complete. Once it's complete, you will be able to query the data like you would any other Postgres database.
Alternatively, use "layered checkout" to avoid downloading all the data
The data in healthdata-gov/covid19-reported-patient-impact-and-hospital-6xf2-c3ie:latest is 0 bytes. If this is too big to download all at once, or perhaps you only need to query a subset of it, you can use a layered checkout.:
sgr checkout --layered healthdata-gov/covid19-reported-patient-impact-and-hospital-6xf2-c3ie:latestThis will not download all the data, but it will create a schema comprised of foreign tables, that you can query as you would any other data. Splitgraph will lazily download the required objects as you query the data. In some cases, this might be faster or more efficient than a regular checkout.
Read the layered querying documentation to learn about when and why you might want to use layered queries.
Query the data with your existing tools
Once you've loaded the data into your local Splitgraph Engine, you can query it with any of your existing tools. As far as they're concerned, healthdata-gov/covid19-reported-patient-impact-and-hospital-6xf2-c3ie is just another Postgres schema.