| econ_tracker_unemp_data | R Documentation |
Unemployment insurance claims data from the Department of Labor (national and state-level) and numerous individual state agencies (county-level).
econ_tracker_unemp_city_data() econ_tracker_unemp_county_data() econ_tracker_unemp_state_data() econ_tracker_unemp_national_data()
All datasets contain the following columns in addition to the location details. Dates specify the last day of the week ending for the reported data.
initclaims_rate_regular: Number of initial claims per 100 people in the 2019 labor force, Regular UI only
initclaims_count_regular: Count of initial claims, Regular UI only
initclaims_rate_pua: Number of initial claims per 100 people in the 2019 labor force, PUA (Pandemic Unemployment Assistance) only
initclaims_count_pua: Count of initial claims, PUA (Pandemic Unemployment Assistance) only
initclaims_rate_combined: Number of initial claims per 100 people in the 2019 labor force, combining Regular and PUA claims
initclaims_count_combined: Count of initial claims, combining Regular and PUA claims
contclaims_rate_regular: Number of continued claims per 100 people in the 2019 labor force, Regular UI only
contclaims_count_regular: Count of continued claims, Regular UI only
contclaims_rate_pua: Number of continued claims per 100 people in the 2019 labor force, PUA (Pandemic Unemployment Assistance) only
contclaims_count_pua: Count of continued claims, PUA (Pandemic Unemployment Assistance) only
contclaims_rate_peuc: Number of continued claims per 100 people in the 2019 labor force, PEUC (Pandemic Emergency Unemployment Compensation) only
contclaims_count_peuc: Count of continued claims, PEUC (Pandemic Emergency Unemployment Compensation) only
contclaims_rate_combined: Number of continued claims per 100 people in the 2019 labor force, combining Regular, PUA and PEUC claims
contclaims_count_combined: Count of continued claims, combining Regular, PUA and PEUC claims
https://github.com/OpportunityInsights/EconomicTracker
Other data-import:
acaps_government_measures_data(),
acaps_secondary_impact_data(),
apple_mobility_data(),
beoutbreakprepared_data(),
cci_us_vaccine_data(),
cdc_aggregated_projections(),
cdc_excess_deaths(),
cdc_social_vulnerability_index(),
coronadatascraper_data(),
coronanet_government_response_data(),
cov_glue_lineage_data(),
cov_glue_newick_data(),
cov_glue_snp_lineage(),
covidtracker_data(),
descartes_mobility_data(),
ecdc_data(),
econ_tracker_consumer_spending,
econ_tracker_employment,
economist_excess_deaths(),
financial_times_excess_deaths(),
google_mobility_data(),
government_policy_timeline(),
jhu_data(),
jhu_us_data(),
kff_icu_beds(),
nytimes_county_data(),
oecd_unemployment_data(),
owid_data(),
param_estimates_published(),
test_and_trace_data(),
us_county_geo_details(),
us_county_health_rankings(),
us_healthcare_capacity(),
us_hospital_details(),
us_state_distancing_policy(),
usa_facts_data(),
who_cases()
Other economics:
acaps_secondary_impact_data(),
econ_tracker_consumer_spending,
econ_tracker_employment,
us_county_health_rankings()
# City Level data res = econ_tracker_unemp_city_data() head(res) # County Level data res = econ_tracker_unemp_county_data() head(res) # State Level data res = econ_tracker_unemp_state_data() head(res) # National Level data res = econ_tracker_unemp_national_data() head(res)
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