georgiacivicdata.dimension#

georgiacivicdata.dimension(name, *, district=None, school=None, county=None, q=None, columns=None, n_max=None, backend=None, **filters)#

Get the rows of a lookup table.

Returns one of the platform's six lookup tables, the reference lists every dataset's codes point to. They hold much more than names, and the API never adds it to dataset rows:

"districts": district name, former names, type, Census id, county, address, coordinates, active flag.
"schools": school name, former names, level, grade span, county, NCES id, address, phone, website, coordinates, locale (city, suburb, town, rural), charter and active flags.
"counties": the 159 county names (without "County").
"tracts": 2020 Census tracts with county, land area and population.
"block_groups": 2020 block groups with tract, county, land area, population, housing units and households.
"demographics": each demographic group's label and category.

Use it to analyze results by locale, map schools, or browse what exists ("every school in Fulton County"). Unfiltered tables are cached for the session.

Joining schools. School codes repeat across districts, so join on district_code and school_code together:

schools = gcd.dimension(
    "schools", columns=["district_code", "school_code", "locale"]
)
grad.merge(schools, on=["district_code", "school_code"], how="left")

Parameters:

name (str) -- The lookup table: "districts", "schools", "counties", "tracts", "block_groups" or "demographics".
district (str or list of str, optional) -- Places by name, matched exactly against current and former names (ignoring case, accents and a trailing "County") and turned into codes. Each applies only to tables with that code column.
school (str or list of str, optional) -- Places by name, matched exactly against current and former names (ignoring case, accents and a trailing "County") and turned into codes. Each applies only to tables with that code column.
county (str or list of str, optional) -- Places by name, matched exactly against current and former names (ignoring case, accents and a trailing "County") and turned into codes. Each applies only to tables with that code column.
q (str, optional) -- Partial text search over the table's name columns, ignoring case and accents (q="eastside"). Unlike the name arguments, it matches part of a name and returns every hit, so it is the tool for browsing.
columns (str or list of str, optional) -- The columns to return. Default: all.
n_max (int, optional) -- The most rows to return. Default None: all.
backend ({"pandas", "polars"}, optional) -- The kind of data frame to return. Default: the backend option ("pandas" unless changed with set_option()).
**filters -- Named filters on the table's key, enum and boolean columns, and county_fips, district_code or tract_geoid where the table has them. Each takes a value or a list (values are OR'd; filters are AND'd), for example active=True, district_type="state_charter" or county_fips="13121".

Returns:

pandas.DataFrame or polars.DataFrame -- One row per district, school, county, tract, block group or demographic group, ordered by the table's primary key and typed from its schema: codes (district_code, school_code, county_fips, tract_geoid, block_group_geoid, demographic) and text columns are strings, coordinates and areas floats, counts and directory_year integers, active and charter booleans. See columns() for each table's columns.