Per capita values are calculated by dividing the estimated population into total revenues per city, per fiscal year.

Per capita values are calculated by dividing the estimated population into total revenues per county, per fiscal year.

The California Department of Transportation (Caltrans) and the California Energy Commission (CEC) are partnering to implement the federal National Electric Vehicle Infrastructure (NEVI) Program, which allocates $5 billion to the states to create a nationwide, interconnected network of DC fast chargers along the National Highway Systems. California's share will be $384 million over 5 years. This map was developed to help prospective applicants and interested parties identify eligible areas for infrastructure deployment.InstructionsViewers can display corridor groups, corridor segments, electric vehicle (EV) charging stations, Justice40 disadvantaged communities, Tribal lands, California-designated low-income or disadvantaged communities, metropolitan planning organizations, regional transportation planning agencies, California state legislative districts, counties, Caltrans districts, utility districts, and congressional districts in this interactive map. The map initially displays corridor groups and their corridor segments included in the Round 2 NEVI solicitation. Viewers can toggle individual layers on and off using the map layers menu located to the right of the map. Some layers are organized into groups; viewers can toggle all layers within a group or select specific ones. The legend to the left of the map will show the layers that have been turned on. There is a search tool to the right of the map that enables viewers to type in an address and locate the address on the map. A basemap selector allows viewers to view road detail. Additional information on the map can be found under the information icon. Viewers can download the map files by clicking on the Data and Supplemental Links icon. Map layers include:A Corridor groups layer that shows designated corridor groups for California's NEVI funding program. Users can click on a corridor segment to view the start and end of each segment within a corridor group. When selected, a pop-up window will appear that identifies the corridor group number, corridor segment, corridor name, minimum number of charging stations required, minimum number of ports required, and needed locations, if applicable, for the corridor segment. Corridor group labels for enhanced accessibility. Note that labels are only visible at certain ranges (zoom in and out to view labels). A NEVI 2 corridors layer shows corridor groups eligible for Round 2 of California's NEVI funding program. NEVI 2 corridor group labels for enhanced accessibility. Note that labels are only visible at certain ranges (zoom in and out to view labels). NEVI 2 corridor segment labels for enhanced accessibility. Note that labels are only visible at certain ranges (zoom in and out to view labels). A Round 1 solicitation corridor groups layer that shows corridor groups eligible for Round 1 of California's NEVI funding program. A layer showing California and Justice40 disadvantaged or low-income communities. A layer showing California-designated disadvantaged or low-income communities. A layer showing Justice40-designated disadvantaged communities. A layer showing California Federally Recognized Tribal Lands. A layer showing Metropolitan Planning Organizations. A layer showing Regional Transportation Planning Agencies. A layer showing California State Senate Districts. A layer showing California State Assembly Districts. A layer showing California Counties. EV charging stations layers (existing DC fast charging stations that are located within one mile of a NEVI-eligible corridor offramp). One layer shows locations of EV charging stations with DC fast charging capabilities that meet the NEVI power level and four-port minimum requirement and could likely become part of the NEVI network if these stations became compliant with other NEVI program requirements such as data reporting. The other layer shows DC fast charging stations that do not meet NEVI power-level or port count requirements but could be upgraded to be NEVI-compliant. Users can click on EV charging stations and a pop-up window will appear with more information on the station (i.e., station address, total port count, minimum NEVI standard, etc.). These data were last updated in March 2024. Please refer to the Department of Energy's Alternative Fuels Data Center and PlugShare for up-to-date existing and planned DC fast charger site information. A layer showing Caltrans Districts. A layer showing Electric Utilities (IOUs and POUs). A layer showing California Congressional Districts. BackgroundThe $5 billion NEVI Program is part of the $1.2 trillion Infrastructure Investment and Jobs Act (IIJA) signed into law by President Biden in November 2021. IIJA commits significant federal funding to clean transportation and energy programs throughout the U.S. to reduce climate changing greenhouse gas emissions. Caltrans is the designated lead agency for NEVI. The CEC is their designated state energy partner. Caltrans and the CEC have partnered to create California's Deployment Plan for the National Electric Vehicle Infrastructure Program that describes how the state plans to allocate its $384 million share of federal NEVI funds to build out a network of modern, high-powered DC fast chargers along federally designated Alternative Fuel Corridors throughout California. California's latest NEVI Deployment Plan was submitted to the Joint Office of Energy and Transportation on August 1, 2023 and approved on September 29, 2023. The Plans must be updated each year over 5 years.NEVI funds must be used initially on federally-designated Alternative Fuel Corridors (shown on the map).Each NEVI-funded DC fast charge station will have a minimum of four 150 kW Combined Charging System (CCS) connectors. Stations will be located no more than 50 miles apart along freeways and highways and no more than 1 mile from a freeway exit or highway roadway. States are required to emphasize equity, with at least 40 percent of NEVI benefits going to disadvantaged, low income, rural and Tribal communities.Data SourcesData are from the Federal Highway Administration's Alternative Fuel Corridors website, the U.S. Department of Energy's Alternative Fuels Data Center Station Data for Alternative Fuel Corridors (as of September 2022), Argonne National Laboratory's Electric Vehicle Charging Justice40 Map, and the California Air Resources Board's Map of California Climate Investments Priority Populations 2022 CES 4.0. ContactPlease submit questions and comments to mediaoffice@energy.ca.gov

Each year the Government of Alberta forecasts tax revenue and publishes the forecasts in the government’s fiscal plan. This data provides detail on the revenue raised by each tax and includes applicable tax rates. For example, fuel tax revenue is disaggregated by fuel type (i.e., gasoline and diesel, propane, aviation fuel, and railway). The table also includes the amount of revenue generated per unit of tax. For example, it is estimated that for 2014-15 the province collects $63 million for every one cent of fuel tax levied on gasoline.

The Government Estimates report the requirements for public monies from the General Revenue Fund to fund the operations of the Government for the applicable fiscal year. Together with the Offices of the Legislative Assembly Estimates, the estimates documents identify the total requirements for public monies from the General Revenue Fund for the year. The estimates make up part of the Government’s annual budget, which also includes the fiscal plan, the government’s strategic or performance plan, and the ministry business plans.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Kern County: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 9,491(3.37%) households where the householder is under 25 years old, 109,590(38.94%) households with a householder aged between 25 and 44 years, 100,116(35.58%) households with a householder aged between 45 and 64 years, and 62,219(22.11%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the county of Kern County, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Kern County median household income by age. You can refer the same here

On an annual basis (individual hospital fiscal year), individual hospitals and hospital systems report detailed facility-level data on services capacity, inpatient/outpatient utilization, patients, revenues and expenses by type and payer, balance sheet and income statement.

Due to the large size of the complete dataset, a selected set of data representing a wide range of commonly used data items, has been created that can be easily managed and downloaded. The selected data file includes general hospital information, utilization data by payer, revenue data by payer, expense data by natural expense category, financial ratios, and labor information.

There are two groups of data contained in this dataset: 1) Selected Data - Calendar Year: To make it easier to compare hospitals by year, hospital reports with report periods ending within a given calendar year are grouped together. The Pivot Tables for a specific calendar year are also found here. 2) Selected Data - Fiscal Year: Hospital reports with report periods ending within a given fiscal year (July-June) are grouped together.

The principle method for maintaining or restoring resilience to the southern California landscape involves vegetation treatments. There are many variations on treatments involving different kinds of equipment and different activities of managing vegetation. The metric has gathered available information on the costs of the major treatment methods and incorporated this information into a geospatial database. There are no treatments of vegetation in southern California that generate revenue. All treatments included here are represented simply as costs per acre.

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 Riverside. 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 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Riverside, the median income for all workers aged 15 years and older, regardless of work hours, was $42,921 for males and $30,743 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 28% between the median incomes of males and females in Riverside. With women, regardless of work hours, earning 72 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Riverside.

- Full-time workers, aged 15 years and older: In Riverside, among full-time, year-round workers aged 15 years and older, males earned a median income of $57,855, while females earned $50,953, resulting in a 12% gender pay gap among full-time workers. This illustrates that women earn 88 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 Riverside.

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 Riverside.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-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 2023
• 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 Riverside median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Oceanside, CA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 22,966, while the mean income for the highest quintile (20% of households with the highest income) is 271,184. This indicates that the top earners earn 12 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 431,493, which is 159.11% higher compared to the highest quintile, and 1878.83% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

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 Oceanside median household income. You can refer the same here

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Kern County. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Kern County. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Kern County, householders within the 45 to 64 years age group have the highest median household income at $78,350, followed by those in the 25 to 44 years age group with an income of $72,227. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $49,707. Notably, householders within the under 25 years age group, had the lowest median household income at $44,895.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

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 Kern County median household income by age. You can refer the same here

The Quarterly Census of Employment and Wages (QCEW) Program is a Federal-State cooperative program between the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the California EDD’s Labor Market Information Division (LMID). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by California Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit industry codes from the North American Industry Classification System (NAICS) at the national, state, and county levels. At the national level, the QCEW program publishes employment and wage data for nearly every NAICS industry. At the state and local area level, the QCEW program publishes employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. In accordance with the BLS policy, data provided to the Bureau in confidence are used only for specified statistical purposes and are not published. The BLS withholds publication of Unemployment Insurance law-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers. Data from the QCEW program serve as an important input to many BLS programs. The Current Employment Statistics and the Occupational Employment Statistics programs use the QCEW data as the benchmark source for employment. The UI administrative records collected under the QCEW program serve as a sampling frame for the BLS establishment surveys. In addition, the data serve as an input to other federal and state programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses the QCEW data as the base for developing the wage and salary component of personal income. The U.S. Department of Labor’s Employment and Training Administration (ETA) and California's EDD use the QCEW data to administer the Unemployment Insurance program. The QCEW data accurately reflect the extent of coverage of California’s UI laws and are used to measure UI revenues; national, state and local area employment; and total and UI taxable wage trends. The U.S. Department of Labor’s Bureau of Labor Statistics publishes new QCEW data in its County Employment and Wages news release on a quarterly basis. The BLS also publishes a subset of its quarterly data through the Create Customized Tables system, and full quarterly industry detail data at all geographic levels.

Get statistical data on the average net operating income by region and county in Ontario. The data includes:

• total gross farm receipts (excluding sales of forest products) - distribution
• total gross farm receipts (excluding sales of forest products) in the calendar year prior to the census or for the last complete fiscal year prior to the census – farms reporting
• total gross farm receipts (excluding sales of forest products) in the calendar year prior to the census or for the last complete fiscal year prior to the census – amount in dollars
• total farm business operating expenses in the calendar year prior to the census or for the last complete fiscal year prior to the census – amount in dollars
• average net operating income per farm
• net operating income per total dollar of gross farm receipts
• operating expenses as a percentage of total gross farm receipts

Statistical data are compiled to serve as a source of agriculture and food statistics for the province of Ontario. Data are prepared primarily by Statistics and Economics staff of the Ministry of Agriculture, Food and Rural Affairs, in co-operation with the Agriculture Division of Statistics Canada and various government departments and farm marketing boards.

Financial information of colleges, type of revenues by geography and type of funds.

This statistic shows the ranking of the global top 10 biotech and pharmaceutical companies worldwide, based on revenue. The values are based on a 2024 database. U.S. pharmaceutical company Pfizer was ranked first, with a total revenue of around 87 billion U.S. dollars. Biotech and pharmaceutical companiesPharmaceutical companies are best known for manufacturing pharmaceutical drugs. These drugs have the aim to diagnose, to cure, to treat, or to prevent diseases. The pharmaceutical sector represents a huge industry, with the global pharmaceutical market being worth over 1.5 trillion U.S. dollars. The best known top global pharmaceutical players are Pfizer, Merck and Johnson & Johnson from the U.S., Novartis and Roche from Switzerland, Sanofi from France, etc. Most of these companies are involved not only in pure pharmaceutical business, but also manufacture medical technology and consumer health products, vaccines, etc. For example, Johnson & Johnson makes most of its revenues through medical devices, diagnostics and consumer health products. There are both pure play biotechnology companies as well as pharmaceutical companies which among other products also produce biotech products within their biotechnological divisions. Most of the leading global pharmaceutical companies have biopharmaceutical divisions. Although not a pure play biotech firm, Roche from Switzerland is among the companies with the largest revenues from biotechnology products worldwide. In contrast, California-based company Amgen was one of the world’s first large pure play biotech companies. Biotech companies use biotechnology to generate their products, most often medical drugs or agricultural genetic engineering. The latter segment is dominated by companies like Bayer CrpScience and Syngenta. The United Nations Convention on Biological Diversity defines biotechnology as follows: "Any technological application that uses biological systems, living organisms, or derivatives thereof, to make or modify products or processes for specific use." In fact, biotechnology is thousands of years old, used in agriculture, food manufacturing and medicine.

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

Estimates of active non-profit organization (NPO) counts, revenues and employment by North American Industry Classification System (NAICS), by geographic classification and by rural and small town area or urban area.

Home Health Agencies (HHA) provide at home skilled nursing, personal care and therapeutic services. Hospices provide palliative care and alleviate the physical, emotional, social and spiritual discomforts of an individual who is experiencing the last phases of life due to the existence of a terminal disease. In addition, hospices provide supportive care for the primary care giver and the family of the hospice patient. Home health agencies and hospices submit an annual utilization report to the Office at the end of each calendar year. The report includes information on services capacity, visits, utilization, patient characteristics, and capital/equipment expenditures, and gross revenues. The documentation, including report forms, is available for each reporting year.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Ridgecrest, CA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 16,555, while the mean income for the highest quintile (20% of households with the highest income) is 223,933. This indicates that the top earners earn 14 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 311,030, which is 138.89% higher compared to the highest quintile, and 1878.77% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

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 Ridgecrest median household income. You can refer the same here

The principle method for maintaining or restoring resilience to the Central Coast landscape involves vegetation treatments. There are many variations on treatments involving different kinds of equipment and different activities of managing vegetation. The metric has gathered available information on the costs of the major treatment methods and incorporated this information into a geospatial database. There are no treatments of vegetation in the Central Coast that generate revenue. All treatments included here are represented simply as costs per acre.