Skip to main content

qcew

A package for retrieving Quarterly Census of Employment and Wages (QCEW) data from the Bureau of Labor Statistics' database.

Requirements

  • Python ≥ 3.8

Installation

Use the package manager pip to install qcew.

pip install qcew

Usage

import qcew

# Get the entire quarterly census of employment and wages database for 2020.
data = qcew.get_qcew_data(
    year="2020",
    annual=False,
    fields=None
)

# Get annual average employment and pay data for the United States from 2001 to 2021.
data = qcew.get_qcew_data_slice(
    slice_type="area",
    qcew_codes=["US000"],
    years=[str(i) for i in range(2001, 2022)],
    annual_data=True,
    fields=[
        "area_fips",
        "own_code",
        "industry_code",
        "year",
        "disclosure_code",
        "annual_avg_emplvl",
        "avg_annual_pay"
        ]
    )

# Get monthly employment data for the state of Hawaii as well as Honolulu County, HI in 2020.
data = qcew.get_qcew_data_slice(
    slice_type="area",
    qcew_codes=[
        "15000", # Hawaii -- Statewide
        "15003", # Honolulu County, HI
        ],
    years=["2020"],
    annual_data=False,
    fields=[
        "area_fips",
        "own_code",
        "industry_code",
        "year",
        "qtr",
        "disclosure_code",
        "month1_emplvl",
        "month2_emplvl",
        "month3_emplvl"
        ]
    )

# Get annual average employment and pay data for the manufacturing sector as a whole from 2010 to 2020.
data = qcew.get_qcew_data_slice(
    slice_type="industry",
    qcew_codes=[
        "31-33", # NAICS code for manufacturing sector.
        ],
    years=[str(i) for i in range(2010, 2021)],
    annual_data=True,
    fields=[
        "area_fips",
        "own_code",
        "industry_code",
        "year",
        "disclosure_code",
        "annual_avg_emplvl",
        "avg_annual_pay"
        ]
    )

# Get monthly employment data for establishments with fewer than 5 employees in the first quarter of 2021.
data = qcew.get_qcew_data_slice(
    slice_type="size",
    qcew_codes=[
        "1", # Size code for establishments with fewer than 5 employees.
        ],
    years=["2021"],
    annual_data=False,
    fields=[
        "area_fips",
        "own_code",
        "industry_code",
        "size_code",
        "year",
        "qtr",
        "disclosure_code",
        "month1_emplvl",
        "month2_emplvl",
        "month3_emplvl"
        ]
    )

License

Distributed under the MIT license. See LICENSE for more information.

Metadata

Release files for qcew 1.0.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for qcew 1.0.4
File Size Uploaded
qcew-1.0.4.tar.gz 6.4 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for qcew 1.0.4
File Interpreter ABI Platform
qcew-1.0.4-py3-none-any.whl Python 3 none any Details

Total release size: 12.8 kB

Release files / qcew-1.0.4.tar.gz

Download URL qcew-1.0.4.tar.gz
Size 6.4 kB
Tags Source
SHA-256 checksum
How to use checksums
8517c8803f83f3e07fbe78fb2f34d0eb07398325942a1e0a40a4f191955393ad
BLAKE2b-256 checksum
How to use checksums
2c6cbcf55e8a553973e2b2ade3c8851073189b71f489b6181982501fadc2e392
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.11.2

Release files / qcew-1.0.4-py3-none-any.whl

Download URL qcew-1.0.4-py3-none-any.whl
Size 6.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
4c1fad617cc5256b28bd2111363920b6eb09dc48cb4d512e35c58f48596b89f6
BLAKE2b-256 checksum
How to use checksums
492fd8c90ca871e6ec69700b4b0aa6f54a5a83b48af92482ce63b7a99262ad1c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.11.2

Release history Release notifications | RSS feed

This release

1.0.4 This release

2 release files

1.0.3

2 release files

1.0.2

2 release files

1.0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page