Public Use Microdata Sample (PUMS) files contain records representing 1-percent or 5-percent samples of the occupied and vacant housing units in the U.S. and the people in the occupied units. Group quarters people also are included. The file contains individual weights for each person and housing unit, which when applied to the individual records, expand the sample to the relevant total. Microdata are for those users who want to create do-it-yourself tabulations. Microdata files show the full range of responses made on individual questionnaires. For example, how one household or one household member answered questions on occupation, place of work, and so forth. The files contain records for a sample of all housing units, with information on the characteristics of each unit and the people in it. For more information about these data, see the PUMS codebooks.

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

Note: Starting on July 13, 2022, the denominator for calculating vaccine coverage has been changed from age 5+ to all ages to reflect new vaccine eligibility criteria. Previously the denominator was changed from age 16+ to age 12+ on May 18, 2021, then changed from age 12+ to age 5+ on November 10, 2021, to reflect previous changes in vaccine eligibility criteria. The previous datasets based on age 16+ and age 5+ denominators have been uploaded as archived tables.

Note: Starting on May 29, 2021 the methodology for calculating on-hand inventory in the shipped/delivered/on-hand dataset has changed. Please see the accompanying data dictionary for details. In addition, this dataset is now down to the ZIP code level.

This data is from the same source as the Vaccine Progress Dashboard at https://covid19.ca.gov/vaccination-progress-data/ which summarizes vaccination data at the county level by county of residence. Where county of residence was not reported in a vaccination record, the county of provider that vaccinated the resident is included. This applies to less than 1% of vaccination records. The sum of county-level vaccinations does not equal statewide total vaccinations due to out-of-state residents vaccinated in California.

This dataset also includes Vaccine Equity Metric score quartiles, which combine the Public Health Alliance of Southern California’s Healthy Places Index (HPI) measure with CDPH-derived scores to estimate factors that impact health, like income, education, and access to health care. Zip codes range from less healthy community conditions in Quartile 1 to more healthy community conditions in Quartile 4.

The Vaccine Equity Metric is for weekly vaccination allocation and reporting purposes only. CDPH-derived quartiles should not be considered as indicative of the HPI score for these zip codes. CDPH-derived quartiles were assigned to zip codes excluded from the HPI score produced by the Public Health Alliance of Southern California due to concerns with statistical reliability and validity in populations smaller than 1,500 or where more than 50% of the population resides in a group setting.

These data do not include doses administered by the following federal agencies who received vaccine allocated directly from CDC: Indian Health Service, Veterans Health Administration, Department of Defense, and the Federal Bureau of Prisons.

Note: Totals for the Vaccine Progress Dashboard and this dataset may not match, as the Dashboard totals doses by Report Date and this dataset totals doses by Administration Date. Dose numbers may also change for a particular Administration Date as data is updated.

Monthly average retail prices for selected products, for Canada and provinces. Prices are presented for the current month and the previous four months. Prices are based on transaction data from Canadian retailers, and are presented in Canadian current dollars.

This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

If you’re a senior with low income, you may qualify for monthly Guaranteed Annual Income System payments.

Maximum payment and allowable private income amounts for the period from July 1, 2025 to June 30, 2026 are:

• $90 monthly for single seniors (maximum monthly payment amount), your annual private income must be less than $4,320
• $180 monthly for senior couples (maximum monthly payment amount), your annual private income must be less than $8,640

The data is organized by private income levels. GAINS payments are provided on top of the Old Age Security (OAS) pension and the Guaranteed Income Supplement (GIS) payments you may receive from the federal government.

Learn more about the Ontario Guaranteed Annual Income System

This data is related to The Retirement Income System in Canada

Ground level ozone (GLO3) was measured at the Alert, Nunavut research station (82º28’N, 62º30’W) from 31 December 1991 to 31 December 2003. These measurements were conducted to: 1. determine a long term trend in background ozone, and 2. to understand the annual appearance of surface level ozone depletions that start in mid-March ( just after the time of polar sunrise) and extend into June. Ozone depletion events have also been correlated with atmospheric mercury depletion events. Many field studies have been carried out at Alert to unravel the reason for this phenomenon. As a result, accurate measurements of ozone have been of crucial importance. GLO3 was measured with a commercial Thermo Environmental Instruments Model 49 instrument based on the principle of ultraviolet absorption by ozone. Calibrations were performed approximately every 2 months and were referenced to the National Institute of Standards and Technology, (NIST) in Gaithersburg, Maryland, U.S.A.. Calibrations were usually within 1% of the mean calibration factor and it is estimated that the final hourly corrected O3 mixing ratios are accurate to within ± 2% or ± 1 ppb, whichever is greater. After 2003, Alert GLO3 data are available from the Canadian Air and Precipitation Monitoring Network (CAPMoN).

This table contains 186 series (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada);  Income quintile (6 items: All quintiles; Lowest income quintile; Second income quintile; Third income quintile; ...);  Socio-demographic characteristics (31 items: All households; One-person households; Single less than 65 years; Single 65 years and older; ...).

This dataset is a contribution to the development of a kelp distribution vector dataset. Bull kelp (Nereocystis leutkeana) and giant kelp (Macrocystis pyrifera) are important canopy-forming kelp species found in marine nearshore habitats on the West coast of Canada. Often referred to as a foundation species, beds of kelp form structural underwater forests that offer habitat for fishes and invertebrates. Despite its far-ranging importance, kelp has experienced a decline in the west coast of North America. The losses have been in response to direct harvest, increase in herbivores through the removal of predators by fisheries or diseases, increase in water turbidity from shoreline development as well as sea temperature change, ocean acidification, and increased storm activates. Understanding these impacts and the level of resilience of different kelp populations requires spatiotemporal baselines of kelp distribution.

The area covered by this dataset includes the BC coast and extends to portions of the Washington and Alaska coasts. This dataset was created using 137 British Admiralty (BA) charts, including insets, with scales ranging from 1:6,080 to 1:500,000, created between 1858 and 1956. All surveys were based on triangulation, in which a sextant or theodolite was used to determine latitude and angles, while a chronometer was used to help determine longitude.

First, each BA chart was scanned by the Canadian Hydrographic Service (CHS) using the CHS Colortrac large format scanner, and saved as a Tagged Image Format at 200 DPI, which was deemed sufficient resolution to properly visualize all the features of interest. Subsequently, the scanned charts were imported into ESRI ArcMap and georeferenced directly to WGS84 using CHS georeferencing standards and principles (charts.gc.ca). In order to minimize error, a hierarchy of control points was used, ranging from high survey order control points to comparing conspicuous stable rock features apparent in satellite imagery.

The georeferencing result was further validated against satellite imagery, CHS charts and fieldsheets, the CHS-Pacific High Water Line (charts.gc.ca), and adjacent and overlapping BA charts. Finally, the kelp features were digitized, and corresponding chart information (scale, chart number, title, survey start year, survey end year, and comments) was added as attributes to each feature.

Given the observed differences in kelp feature representation at different scales, when digitizing kelp features, polygons were used to represent the discrete observations, and as such, they represent presence of kelp and not kelp area. Polygons were created by tracing around the kelp feature, aiming to keep the outline close to the stipe and blades.

The accuracy of the location of the digitized kelp features was defined using a reliability criterion, which considers the location of the digitized kelp feature (polygon) in relation to the local depth in which the feature occurs. For this, we defined a depth threshold of 40 m to represent a low likelihood of kelp habitat in areas deeper than the threshold. An accuracy assessment of the digitized kelp features concluded that 99% of the kelp features occurred in expected areas within a depth of less than 40 m, and only about 1% of the features occurred completely outside of this depth. For more information, visit: https://open.canada.ca/data/en/dataset/bac83470-bc8f-4065-8ef3-bf76463c4ef2

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Chino. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2022

Based on our analysis ACS 2022 1-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Chino, the median income for all workers aged 15 years and older, regardless of work hours, was $48,121 for males and $34,021 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 29% between the median incomes of males and females in Chino. With women, regardless of work hours, earning 71 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Chino.

- Full-time workers, aged 15 years and older: In Chino, among full-time, year-round workers aged 15 years and older, males earned a median income of $64,117, while females earned $63,222, resulting in a 1% gender pay gap among full-time workers. This illustrates that women earn 99 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Chino.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Chino.

https://i.neilsberg.com/ch/chino-ca-income-by-gender.jpeg" alt="Chino, CA gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Chino median household income by gender. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Merced. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2022

Based on our analysis ACS 2022 1-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Merced, the median income for all workers aged 15 years and older, regardless of work hours, was $37,973 for males and $25,924 for females.

These income figures highlight a substantial gender-based income gap in Merced. Women, regardless of work hours, earn 68 cents for each dollar earned by men. This significant gender pay gap, approximately 32%, underscores concerning gender-based income inequality in the city of Merced.

- Full-time workers, aged 15 years and older: In Merced, among full-time, year-round workers aged 15 years and older, males earned a median income of $50,519, while females earned $49,938, resulting in a 1% gender pay gap among full-time workers. This illustrates that women earn 99 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Merced.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Merced.

https://i.neilsberg.com/ch/merced-ca-income-by-gender.jpeg" alt="Merced, CA gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Merced median household income by gender. You can refer the same here