us_employment

U.S. monthly employment totals by sector

Monthly employment total in a variety of job categories from January 2006 through December 2015, seasonally adjusted and reported in thousands. Downloaded and reformatted on Nov. 11, 2018.

In the mid 2000s the global economy was hit by a crippling recession. One result: Massive job losses across the United States. The downturn in employment, and the slow recovery in hiring that followed, was tracked each month by the Current Employment Statistics program at the U.S. Bureau of Labor Statistics.

Totals are included for the 22 "supersectors" tracked by the BLS. The "nonfarm" total is the category typically used by economists and journalists as a stand-in for the country's employment total.

A calculated "nonfarm_change" column has been appended with the month-to-month change in that supersector's employment. It is useful for illustrating how to make bar charts that report both negative and positive values.

CSV 120 rows 24 fields 18 KB 2 gallery examples 2 examples

Fields

Field	Type	Summary	Missing
`month`Add a description for month	date	Jan 1, 2006 – Dec 1, 2015	Missing 0
`nonfarm`Add a description for nonfarm	integer	129,700 – 143,100 · mean 135,700	Missing 0
`private`Add a description for private	integer	107,200 – 121,000 · mean 113,500	Missing 0
`goods_producing`Add a description for goods_producing	integer	17,630 – 22,630 · mean 19,640	Missing 0
`service_providing`Add a description for service_providing	integer	112,000 – 123,400 · mean 116,000	Missing 0
`private_service_providing`Add a description for private_service_providing	integer	89,510 – 101,300 · mean 93,860	Missing 0
`mining_and_logging`Add a description for mining_and_logging	integer	656 – 904 · mean 777.4	Missing 0
`construction`Add a description for construction	integer	5,427 – 7,726 · mean 6,365	Missing 0
`manufacturing`Add a description for manufacturing	integer	11,450 – 14,230 · mean 12,500	Missing 0
`durable_goods`Add a description for durable_goods	integer	6,985 – 9,028 · mean 7,833	Missing 0
`nondurable_goods`Add a description for nondurable_goods	integer	4,434 – 5,228 · mean 4,668	Missing 0
`trade_transportation_utilties`Add a description for trade_transportation_utilties	integer	24,480 – 27,040 · mean 25,840	Missing 0
`wholesale_trade`Add a description for wholesale_trade	number	5,439 – 6,042 · mean 5,751	Missing 0
`retail_trade`Add a description for retail_trade	number	14,330 – 15,700 · mean 15,070	Missing 0
`transportation_and_warehousing`Add a description for transportation_and_warehousing	number	4,117 – 4,951 · mean 4,469	Missing 0
`utilities`Add a description for utilities	number	546.6 – 563.6 · mean 553.7	Missing 0
`information`Add a description for information	integer	2,634 – 3,055 · mean 2,809	Missing 0
`financial_activities`Add a description for financial_activities	integer	7,676 – 8,394 · mean 7,992	Missing 0
`professional_and_business_services`Add a description for professional_and_business_services	integer	16,390 – 19,890 · mean 17,900	Missing 0
`education_and_health_services`Add a description for education_and_health_services	integer	17,950 – 22,320 · mean 20,130	Missing 0
`leisure_and_hospitality`Add a description for leisure_and_hospitality	integer	12,930 – 15,410 · mean 13,730	Missing 0
`other_services`Add a description for other_services	integer	5,315 – 5,652 · mean 5,460	Missing 0
`government`Add a description for government	integer	21,810 – 23,000 · mean 22,150	Missing 0
`nonfarm_change`Add a description for nonfarm_change	integer	-802 – 522 · mean 66.04	Missing 0

Profiled across all 120 rows. No field descriptions yet. Add them

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Pick two fields. Scroll to zoom, drag to pan. Both fields have values in 120 of 120 rows.Pick two fields. Both fields have values in 120 of 120 rows. Vega-Lite · input binding · scale bindingVega-Lite · input binding

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First 5 of 120 rows5 of 120 rows

month	nonfarm	private	goods_producing	service_providing	private_service_providing	mining_and_logging	construction	manufacturing	durable_goods	nondurable_goods	trade_transportation_utilties	wholesale_trade	retail_trade	transportation_and_warehousing	utilities	information	financial_activities	professional_and_business_services	education_and_health_services	leisure_and_hospitality	other_services	government	nonfarm_change
2006-01-01	135450	113603	22467	112983	91136	656	7601	14210	8982	5228	26162	5840.4	15351.5	4420	549.8	3052	8307	17299	17946	12945	5425	21847	282
2006-02-01	135762	113884	22535	113227	91349	662	7664	14209	8986	5223	26196	5854.8	15361.3	4429.4	550.1	3052	8332	17365	17998	12980	5426	21878	312
2006-03-01	136059	114156	22572	113487	91584	669	7689	14214	9000	5214	26239	5873.3	15388	4429.7	547.5	3055	8348	17438	18045	13034	5425	21903	297
2006-04-01	136227	114308	22631	113596	91677	679	7726	14226	9020	5206	26230	5886.9	15348.5	4445.4	548.9	3046	8369	17462	18070	13074	5426	21919	168
2006-05-01	136258	114332	22597	113661	91735	681	7713	14203	9017	5186	26223	5897.2	15318.1	4459.4	548.3	3039	8376	17512	18100	13052	5433	21926	31

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Examples

Vega and Vega-Lite examples open in the Editor with this dataset loaded. Altair examples link to their Python source.

Provenance

Source

U.S. Bureau of Labor Statistics Current Employment Statistics

License

U.S. Government Dataset (other-pd)

File

data/us-employment.csv · 17,841 bytes · View on GitHub

Use This Dataset

https://cdn.jsdelivr.net/npm/vega-datasets@3/data/us-employment.csv

"data": {"url": "https://cdn.jsdelivr.net/npm/vega-datasets@3/data/us-employment.csv"}

"data": [{
  "name": "us_employment",
  "url": "https://cdn.jsdelivr.net/npm/vega-datasets@3/data/us-employment.csv",
  "format": {"type": "csv", "parse": "auto"}
}]

from altair.datasets import data

us_employment = data.us_employment()

import data from 'vega-datasets';

const us_employment = await data['us-employment.csv']();

Download us-employment.csv

At a Glance

Format: CSV
Size: 18 KB · 120 rows
Source: U.S. Bureau of Labor Statistics Current Employment Statistics
License: Public domain
Release: v3.2.1

Used in the Galleries

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