def testing_trim_metadata_removed_non_estimate_and_non_included_groups(self):
result = trimMetadata(_fake_metadata_to_trim["variables"], ["B00002"])
expected = {
"B00002_001E": {
"label": "Estimate!!Total:!!Female:!!25 to 29 years",
"concept": "SEX BY AGE",
"group": "B00002",
}
}
self.assertEqual(result, expected)
def __init__(self, base_url):
self.base_url = base_url
metadata = fetch_acs_metadata(self.base_url)["variables"]
metadata = trimMetadata(metadata, MEDIAN_INCOME_BY_RACE_GROUPS.keys())
self.metadata = parseMetadata(
metadata,
[MetadataKey.AGE, MetadataKey.INCOME, MetadataKey.RACE],
self.metadataInitializer,
)
self.state_fips = get_state_fips_mapping(base_url)
self.county_fips = get_county_fips_mapping(base_url)
self.data = {}
def __init__(self, base_url):
self.base_url = base_url
metadata = fetch_acs_metadata(self.base_url)["variables"]
metadata = trimMetadata(metadata, [HEALTH_INSURANCE_BY_SEX_GROUPS_PREFIX])
self.metadata = parseMetadata(
metadata, [MetadataKey.AGE, MetadataKey.SEX], lambda key: dict()
)
for k, v in self.metadata.items():
if MetadataKey.POPULATION not in v:
self.metadata[k][
MetadataKey.POPULATION
] = HealthInsurancePopulation.TOTAL
self.state_fips = get_state_fips_mapping(base_url)
self.county_fips = get_county_fips_mapping(base_url)
self.data = {}
def __init__(self, base_url):
self.base_url = base_url
metadata = fetch_acs_metadata(self.base_url)["variables"]
metadata = trimMetadata(
metadata, HEALTH_INSURANCE_BY_RACE_GROUP_PREFIXES.keys()
)
self.metadata = parseMetadata(
metadata, [MetadataKey.AGE, MetadataKey.RACE], self.metadataInitializer
)
for k, v in self.metadata.items():
if MetadataKey.POPULATION not in v:
self.metadata[k][
MetadataKey.POPULATION
] = HealthInsurancePopulation.TOTAL
self.state_fips = get_state_fips_mapping(base_url)
self.county_fips = get_county_fips_mapping(base_url)
self.data = {}