pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync
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Query the Data Delivery Network

Query the DDN

The 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 rate_of_neonatal_hospital_stays_with_withdrawal table in this repository, by referencing it like:

"pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync:latest"."rate_of_neonatal_hospital_stays_with_withdrawal"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "number_of_neonatal_hospital_1", -- Indicates if the number of neonatal hospital stays with a diagnosis of withdrawal symptoms from maternal use of drugs of addiction in the first 28 days of life has been suppressed to protect confidentiality. Counts less than 11 are not provided.
    "year", -- Calendar year for measurement (January 1–December 31).
    "time_period", -- Period for measurement (annual, federal fiscal year, or quarterly, if available).
    "number_of_neonatal_hospital", -- Number of neonatal hospital stays with a diagnosis of withdrawal symptoms from maternal use of drugs of addiction in the first 28 days of life. This count is provided by the Pennsylvania Health Care Cost Containment Council (PHC4).
    "geocoded_column", -- Georeferenced Latitude and Longitude column for use in visualization such as maps.
    "geographic_name", -- Name of geographic area.
    "geographic_area", -- Region for measure, either total for Commonwealth or individual county.
    "county_code_number", -- Pennsylvania county code provided as a number (1-67 for counties, 0 for Commonwealth).
    "total_number_of_birth_1", -- Indicates if the number of birth hospitalizations has been suppressed to protect confidentiality. Counts less than 11 are not provided.
    "age", -- Age of neonates (newborn child) (all less than 28 days of age in this dataset).
    "time_period_dates", -- Start and end dates of time period.
    ":@computed_region_nmsq_hqvv",
    ":@computed_region_d3gw_znnf",
    "county_fips_code", -- Last 3 digits of the 5-digit Federal Information Processing Standard (FIPS) code that designate the county association. Each state has its own 2-digit number and each county within the state has its own 3-digit number which are combined into a 5-digit number to uniquely identify every US county.
    "total_number_of_birth", -- Count of birth hospitalizations in specified timeframe.
    "rate_of_neonatal_hospital", -- Rate of neonatal hospital stays in which there is a diagnosis of withdrawal symptoms from maternal use of drugs of addiction in the first 28 days of life, relative to the total number of birth hospitalizations.
    ":@computed_region_rayf_jjgk",
    "gender", -- Gender of neonates or newborn child
    "total_number_of_birth_2", -- Describes number of birth hospitalizations.
    ":@computed_region_amqz_jbr4",
    ":@computed_region_r6rf_p9et",
    "type_of_rate", -- Description of neonatal hospital stays with withdrawal symptoms.
    "number_of_neonatal_hospital_2", -- Number of neonatal hospital stays with a diagnosis of withdrawal symptoms using ICD-10 code P96.1 in the first 28 days of life.
    "county_code_text", -- Pennsylvania county code provided as text (1-67 for counties sorted alphabetically, 0 for Commonwealth).
    "latitude_longitude", -- Latitude and longitude coordinates in degrees for a centroid point for geographic area.
    "state_fips_code" -- These are the first 2 digits of the 5-digit Federal Information Processing Standard (FIPS) code that designate the State association. Each State has its own 2-digit number and each County within the state has its own 3-digit number which are combined into a 5-digit number to uniquely identify every US county. For more technical details : Federal Information Processing Standards Publications (FIPS PUBS) are issued by the National Institute of Standards and Technology (NIST) after approval by the Secretary of Commerce pursuant to Section 111 (d) of the Federal Property and Administrative Services Act of 1949 as amended by the Computer Security Act of 1987, Public Law 100-235. Federal Information Processing Standard (FIPS) 6-4, Counties and Equivalent Entities of the U.S., Its Possessions, and Associated Areas -- 90 Aug 31 , provides the names and codes that represent the counties and other entities treated as equivalent legal and/or statistical subdivisions of the 50 States, the District of Columbia, and the possessions and freely associated areas of the United States. Counties are considered to be the "first-order subdivisions" of each State and statistically equivalent entity, regardless of their local designations (county, parish, borough, etc.). Information gathered from census data - https://www.census.gov/library/reference/code-lists/ansi.html
FROM
    "pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync:latest"."rate_of_neonatal_hospital_stays_with_withdrawal"
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 pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync 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 pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync: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 pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync

Checkout 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 pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync:latest

This will download all the objects for the latest tag of pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync 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 pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync: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 pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync:latest

This 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, pa-gov/rate-of-neonatal-hospital-stays-with-withdrawal-39ba-sync is just another Postgres schema.

Related Documentation:

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