Financial overview and grant giving statistics of My Neighbor to Love Coalition

Analysis of data from the Community Life Survey looking at how 16- to 24-year-olds engage with their local area, compared with adults aged 25 and over. The data covers England only.

This operations dashboard shows historic and current data related to this performance measure.The performance measure dashboard is available at 1.05 Feeling of Safety in Your Neighborhood. Data Dictionary (update pending)Dashboard embed also used by Tempe's Strategic Management and Diversity Office.

This data set contains DOT construction project information. The data is refreshed nightly from multiple data sources, therefore the data becomes stale rather quickly.

About this dataset

Context

The dataset tabulates the population of Parks by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Parks across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 52.97% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Parks is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Parks total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Parks Population by Gender. You can refer the same here

The mission of the Tempe Police Department is to reduce harm in our community, and an important component of this mission is to ensure citizens and visitors feel safe in Tempe. One of the Police Department’s five Key Initiatives is to address crime and fear of crime. This is achieved through responding to citizen calls for police service, addressing crime throughout the city, and working with the community to prevent crime. The Police Department uses data from the annual Community Survey and the Business Survey and other data sources to study crime trends and implement strategies to enhance safety and the feeling of safety in Tempe. Data for this performance measure is drawn from a monthly survey of Tempe residents conducted by Elucd.This data contains monthly survey results on residents feelings of safety in their neighborhood, ranging between 0 and 100.The performance measure page is available at 1.05 Feeling of Safety in Your Neighborhood.Additional InformationSource: This measure comes from a question asked of residents in the monthly sentiment survey conducted by Elucd. Contact (author): Contact E-Mail (author): Contact (maintainer): Brooks LoutonContact E-Mail (maintainer): Brooks_Louton@tempe.govData Source Type: ExcelPreparation Method: ManualPublish Frequency: AnnuallyPublish Method: ManualData Dictionary

Tempe’s trust data for this measure is collected every month and comes from the “Safety” result from the monthly administered Police Sentiment Survey. There is one question which feeds into these results: "When it comes to the threat of crime, how safe do you feel in your neighborhood?" Benchmark data is from cohorts of communities with similar characteristics, such as size, population density, and region. This data is collected every month and quarter via a recurring report. This page provides data for the Feeling of Safety in Your Neighborhood performance measure. The performance measure dashboard is available at 1.05 Feeling of Safety in Your Neighborhood. Additional Information Source: Zencity Contact: Adam SamuelsContact email: Adam_Samuels@tempe.govData Source Type: Excel, CSVPreparation Method: Take the "Safety" score from the Police Sentiment Survey. This score includes the average of the top two results from the question underneath this area on the report. These months are then averaged to get the quarterly score.Publish Frequency: MonthlyPublish Method: Manual Data Dictionary

About this dataset

Context

The dataset tabulates the Dexter population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Dexter. The dataset can be utilized to understand the population distribution of Dexter by age. For example, using this dataset, we can identify the largest age group in Dexter.

Key observations

The largest age group in Dexter, MI was for the group of age 10-14 years with a population of 450 (9.93%), according to the 2021 American Community Survey. At the same time, the smallest age group in Dexter, MI was the 60-64 years with a population of 55 (1.21%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Dexter is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Dexter total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Dexter Population by Age. You can refer the same here

This is a monthly report on publicly funded community services for people of all ages using data from the Community Services Data Set (CSDS) reported in England for July 2021. It has been developed to help achieve better outcomes and provide data that will be used to commission services in a way that improves health, reduces inequalities, and supports service improvement and clinical quality. This report uses the new version of the dataset, CSDS v1.5. As an uplift from v1.0, the v1.5 dataset collects additional data on a person's care plan details, employment status and social & personal circumstances. These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. More information about experimental statistics can be found on the UK Statistics Authority website. A supplementary file including health visiting metrics now accompanies this publication. Due to the coronavirus illness (COVID-19) disruption, the quality and coverage of some of our statistics has been affected, for example, by an increase in non-submissions for some datasets. We are also seeing some different patterns in the submitted data. For example, fewer patients are being referred to hospital and more appointments being carried out via phone/telemedicine/email. Therefore, data should be interpreted with care over the COVID-19 period.

The survey charting neighbour relations and disputes was funded by the Academy of Finland ('The Future of Living and Housing' programme, 'Neighbour Disputes and Housing in Finland' project). Concerning interaction with neighbours, the respondents were asked how often they visited, spent time with, helped and had conversations with their neighbours as well as how many neighbours they greeted and talked to when encountering them. Social networks were surveyed with questions about how many friends the respondents had in different groups (relatives, study/work community, neighbourhood, hobbies, other group) as well as the number of people in these groups they had difficulty getting along with. The respondents' perceptions of their neighbours, their neighbourhood, and themselves as neighbours were charted by asking to what extent they agreed with a number of statements (e.g. "My neighbours can generally be trusted", "There is a number of different social problems in my neighbourhood", "If my neighbour causes disturbances, I will speak to them directly about it"). Some statements were presented to probe opinions on what good neighbour relations should be like ("Nowadays people care less about their neighbours than they used to"). Regarding disturbances and nuisance caused by neighbours, the respondents were asked what kind of problems they had experienced (e.g. noise from renovation, loud parties, cigarette smoke, gossiping, boundary disputes), how easily they intervened with problems in the neighbourhood, and what their reaction would be if they were told that they cause disturbances to the neighbours. Neighbour disputes and their resolution was charted with questions about the frequency of disputes between the neighbours, own involvement in the disputes, ways used to attempt to resolve the dispute, whether the respondents had ever moved house because of difficult neighbours, and whether the respondents had ever contacted or planned to contact the authorities because of a neighbour dispute. Those respondents who had planned to contact or had contacted the authorities were asked at which point in a neighbour dispute they would contact them. Background variables included the respondent's age, gender, household composition, economic activity, education, monthly gross income, self-perceived health status and quality of life as well as housing tenure, type of accommodation, years lived in the accommodation, type of neighbourhood, and municipality type.

About this dataset

Context

The dataset tabulates the population of Huntington Woods by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Huntington Woods across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.67% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Huntington Woods is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Huntington Woods total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Huntington Woods Population by Gender. You can refer the same here

Financial overview and grant giving statistics of Our Community Credit Union

About this dataset

Context

The dataset tabulates the population of Lockport town by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Lockport town across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.3% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Lockport town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Lockport town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Lockport town Population by Gender. You can refer the same here

Financial overview and grant giving statistics of My Fathers House Community Services Inc.

Financial overview and grant giving statistics of Our Village Community Center

A. SUMMARY This dataset includes COVID-19 tests by resident neighborhood and specimen collection date (the day the test was collected). Specifically, this dataset includes tests of San Francisco residents who listed a San Francisco home address at the time of testing. These resident addresses were then geo-located and mapped to neighborhoods. The resident address associated with each test is hand-entered and susceptible to errors, therefore neighborhood data should be interpreted as an approximation, not a precise nor comprehensive total.

In recent months, about 5% of tests are missing addresses and therefore cannot be included in any neighborhood totals. In earlier months, more tests were missing address data. Because of this high percentage of tests missing resident address data, this neighborhood testing data for March, April, and May should be interpreted with caution (see below)

Percentage of tests missing address information, by month in 2020 Mar - 33.6% Apr - 25.9% May - 11.1% Jun - 7.2% Jul - 5.8% Aug - 5.4% Sep - 5.1% Oct (Oct 1-12) - 5.1%

To protect the privacy of residents, the City does not disclose the number of tests in neighborhoods with resident populations of fewer than 1,000 people. These neighborhoods are omitted from the data (they include Golden Gate Park, John McLaren Park, and Lands End).

Tests for residents that listed a Skilled Nursing Facility as their home address are not included in this neighborhood-level testing data. Skilled Nursing Facilities have required and repeated testing of residents, which would change neighborhood trends and not reflect the broader neighborhood's testing data.

This data was de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected).

The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco. During this investigation, some test results are found to be for persons living outside of San Francisco and some people in San Francisco may be tested multiple times (which is common). To see the number of new confirmed cases by neighborhood, reference this map: https://sf.gov/data/covid-19-case-maps#new-cases-maps

B. HOW THE DATASET IS CREATED COVID-19 laboratory test data is based on electronic laboratory test reports. Deduplication, quality assurance measures and other data verification processes maximize accuracy of laboratory test information. All testing data is then geo-coded by resident address. Then data is aggregated by analysis neighborhood and specimen collection date.

Data are prepared by close of business Monday through Saturday for public display.

C. UPDATE PROCESS Updates automatically at 05:00 Pacific Time each day. Redundant runs are scheduled at 07:00 and 09:00 in case of pipeline failure.

D. HOW TO USE THIS DATASET San Francisco population estimates for geographic regions can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS).

Due to the high degree of variation in the time needed to complete tests by different labs there is a delay in this reporting. On March 24 the Health Officer ordered all labs in the City to report complete COVID-19 testing information to the local and state health departments.

In order to track trends over time, a data user can analyze this data by "specimen_collection_date".

Calculating Percent Positivity: The positivity rate is the percentage of tests that return a positive result for COVID-19 (positive tests divided by the sum of positive and negative tests). Indeterminate results, which could not conclusively determine whether COVID-19 virus was present, are not included in the calculation of percent positive. Percent positivity indicates how widespread COVID-19 is in San Francisco and it helps public health officials determine if we are testing enough given the number of people who are testing positive. When there are fewer than 20 positives tests for a given neighborhood and time period, the positivity rate is not calculated for the public tracker because rates of small test counts are less reliable.

Calculating Testing Rates: To calculate the testing rate per 10,000 residents, divide the total number of tests collected (positive, negative, and indeterminate results) for neighborhood by the total number of residents who live in that neighborhood (included in the dataset), then multiply by 10,000. When there are fewer than 20 total tests for a given neighborhood and time period, the testing rate is not calculated for the public tracker because rates of small test counts are less reliable.

Read more about how this data is updated and validated daily: https://sf.gov/information/covid-19-data-questions

E. CHANGE LOG

• 1/12/2024 - This dataset will stop updating as of 1/12/2024
• 6/21/2023 - A small number of additional COVID-19 testing records were released as part of our ongoing cleaning efforts.
• 1/31/2023 - updated “acs_population” column to reflect the 2020 Census Bureau American Community Survey (ACS) San Francisco Population estimates.
• 1/31/2023 - implemented system updates to streamline and improve our geo-coded data, resulting in small shifts in our testing data by geography.
• 1/31/2023 - renamed column “last_updated_at” to “data_as_of”.
• 1/31/2023 - removed the “multipolygon” column. To access the multipolygon geometry column for each geography unit, refer to COVID-19 Cases and Deaths Summarized by Geography.
• 4/16/2021 - dataset updated to refresh with a five-day data lag.

About this dataset

Context

The dataset tabulates the population of Red House town by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Red House town across both sexes and to determine which sex constitutes the majority.

Key observations

There is a considerable majority of male population, with 65.52% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Red House town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Red House town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Red House town Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of New Chicago by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of New Chicago across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 51.8% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the New Chicago is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of New Chicago total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 New Chicago Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Greenwood by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Greenwood across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 51.16% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Greenwood is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Greenwood total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Greenwood Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Iron County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Iron County across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 50.09% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Iron County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Iron County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Iron County Population by Gender. You can refer the same here