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 New Canada town. 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 New Canada town, the median income for all workers aged 15 years and older, regardless of work hours, was $52,250 for males and $27,500 for females.

These income figures highlight a substantial gender-based income gap in New Canada town. Women, regardless of work hours, earn 53 cents for each dollar earned by men. This significant gender pay gap, approximately 47%, underscores concerning gender-based income inequality in the town of New Canada town.

- Full-time workers, aged 15 years and older: In New Canada town, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,125, while females earned $51,375, leading to a 19% gender pay gap among full-time workers. This illustrates that women earn 81 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in New Canada town.

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 New Canada town median household income by race. You can refer the same here

Average hourly and weekly wage rate, and median hourly and weekly wage rate by North American Industry Classification System (NAICS), type of work, gender, and age group.

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 Little Canada. 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 Little Canada, the median income for all workers aged 15 years and older, regardless of work hours, was $49,764 for males and $40,129 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 19% between the median incomes of males and females in Little Canada. With women, regardless of work hours, earning 81 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Little Canada.

- Full-time workers, aged 15 years and older: In Little Canada, among full-time, year-round workers aged 15 years and older, males earned a median income of $69,643, while females earned $59,934, resulting in a 14% gender pay gap among full-time workers. This illustrates that women earn 86 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 Little Canada.

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 Little Canada.

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 Little Canada median household income by race. You can refer the same here

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Canadian, OK, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Canadian, OK reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Canadian households based on income levels.

Key observations

• For Family Households: In Canadian, the majority of family households, representing NA%, earn NA, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising NA%, have incomes falling NA, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Canadian, the majority of non-family households, accounting for NA%, have income NA, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising NA%, earn NA, representing a smaller, yet notable, portion of non-family households in the community.

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:

• 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
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Canadian, OK (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Canadian, OK
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Canadian, OK
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Canadian, OK

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 Canadian median household income. You can refer the same here

🏦 Synthetic Loan Approval Dataset

A Realistic, High-Quality Dataset for Credit Risk Modelling

🎯 Why This Dataset?

Most loan datasets on Kaggle have unrealistic patterns where:

1. ❌ Credit scores don't matter
2. ❌ Approval logic is backwards
3. ❌ Models learn nonsense patterns

Unlike most loan datasets available online, this one is built on real banking criteria from US and Canadian financial institutions. Drawing from 3 years of hands-on finance industry experience, the dataset incorporates realistic correlations and business logic that reflect how actual lending decisions are made. This makes it perfect for data scientists looking to build portfolio projects that showcase not just coding ability, but genuine understanding of credit risk modelling.

📊 Dataset Overview

Metric	Value
Total Records	50,000
Features	20 (customer_id + 18 predictors + 1 target)
Target Distribution	55% Approved, 45% Rejected
Missing Values	0 (Complete dataset)
Product Types	Credit Card, Personal Loan, Line of Credit
Market	United States & Canada
Use Case	Binary Classification (Approved/Rejected)

🔑 Key Features

Identifier:

-Customer ID (unique identifier for each application)

Demographics:

-Age, Occupation Status, Years Employed

Financial Profile:

-Annual Income, Credit Score, Credit History Length -Savings/Assets, Current Debt

Credit Behaviour:

-Defaults on File, Delinquencies, Derogatory Marks

Loan Request:

-Product Type, Loan Intent, Loan Amount, Interest Rate

Calculated Ratios:

-Debt-to-Income, Loan-to-Income, Payment-to-Income

💡 What Makes This Dataset Special?

1️⃣ Real-World Approval Logic The dataset implements actual banking criteria: - DTI ratio > 50% = automatic rejection - Defaults on file = instant reject - Credit score bands match real lending thresholds - Employment verification for loans ≥$20K

2️⃣ Realistic Correlations - Higher income → Better credit scores - Older applicants → Longer credit history - Students → Lower income, special treatment for small loans - Loan intent affects approval (Education best, Debt Consolidation worst)

3️⃣ Product-Specific Rules - Credit Cards: More lenient, higher limits - Personal Loans: Standard criteria, up to $100K - Line of Credit: Capped at $50K, manual review for high amounts

4️⃣ Edge Cases Included - Young applicants (age 18) building first credit - Students with thin credit files - Self-employed with variable income - High debt-to-income ratios - Multiple delinquencies

🎓 Perfect For - Machine Learning Practice: Binary classification with real patterns - Credit Risk Modelling: Learn actual lending criteria - Portfolio Projects: Build impressive, explainable models - Feature Engineering: Rich dataset with meaningful relationships - Business Analytics: Understand financial decision-making

📈 Quick Stats

Approval Rates by Product - Credit Card: 60.4% more lenient) - Personal Loan: 46.9 (standard) - Line of Credit: 52.6% (moderate)

Loan Intent (Best → Worst Approval Odds) 1. Education (63% approved) 2. Personal (58% approved) 3. Medical/Home (52% approved) 4. Business (48% approved) 5. Debt Consolidation (40% approved)

Credit Score Distribution - Mean: 644 - Range: 300-850 - Realistic bell curve around 600-700

Income Distribution - Mean: $50,063 - Median: $41,608 - Range: $15K - $250K

🎯 Expected Model Performance

With proper feature engineering and tuning: - Accuracy: 75-85% - ROC-AUC: 0.80-0.90 - F1-Score: 0.75-0.85

Important: Feature importance should show: 1. Credit Score (most important) 2. Debt-to-Income Ratio 3. Delinquencies 4. Loan Amount 5. Income

If your model shows different patterns, something's wrong!

🏆 Use Cases & Projects

Beginner - Binary classification with XGBoost/Random Forest - EDA and visualization practice - Feature importance analysis

Intermediate - Custom threshold optimization (profit maximization) - Cost-sensitive learning (false positive vs false negative) - Ensemble methods and stacking

Advanced - Explainable AI (SHAP, LIME) - Fairness analysis across demographics - Production-ready API with FastAPI/Flask - Streamlit deployment with business rules

⚠️ Important Notes

This is SYNTHETIC Data - Generated based on real banking criteria - No real customer data was used - Safe for public sharing and portfolio use

Limitations - Simplified approval logic (real banks use 100+ factors) - No temporal component (no time series) - Single country/currency assumed (USD) - No external factors (economy, market conditions)

Educational Purpose This dataset is designed for: - Learning credit risk modeling - Portfolio projects - ML practice - Understanding lending criteria

NOT for: - Actual lending decisions - Financial advice - Production use without validation

🤝 Contributing

Found an issue? Have suggestions? - Open an issue on GitHub - Suggest i...

About this dataset

Context

The dataset presents median household incomes for various household sizes in New Canada, Maine, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, New Canada town did not include 6, or 7-person households. Across the different household sizes in New Canada town the mean income is $103,835, and the standard deviation is $59,699. The coefficient of variation (CV) is 57.49%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $16,552. It then further increased to $136,465 for 5-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/new-canada-me-median-household-income-by-household-size.jpeg" alt="New Canada, Maine median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

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

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 Canada town 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 New Canada town. 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 New Canada town. 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 New Canada town, the median household income stands at $96,442 for householders within the 45 to 64 years age group, followed by $82,031 for the 25 to 44 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $43,750.

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 New Canada town median household income by age. You can refer the same here

Average weekly earnings by North American Industry Classification System (NAICS), type of employee and overtime status, last 5 years.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Little Canada. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Little Canada. 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 2022

In terms of income distribution across age cohorts, in Little Canada, householders within the 25 to 44 years age group have the highest median household income at $77,780, followed by those in the 45 to 64 years age group with an income of $77,181. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $62,243. Notably, householders within the under 25 years age group, had the lowest median household income at $36,828.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 2022 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 Little Canada median household income by age. You can refer the same here

Wages in Manufacturing in Canada decreased to 32.13 CAD/Hour in September from 32.52 CAD/Hour in August of 2025. This dataset provides - Canada Average Hourly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

The datasets contain the computer code and data required to determine the cost and economic impacts of phosphorus recovery from municipal wastewater in Canada and the United States. The datasets supply data to (i) calculate the efficiency and cost of phosphorus recovery from the aqueous phase of digestate and sewage sludge for wastewater resource recovery facilities (WRRFs) as shown in Figure 1; (ii) estimate the average annual per capita phosphorus recovery cost and the household affordability index (HAI) across the second-level territory divisions (census divisions (Canada) and counties (United States)) when excluding and including the offset cost derived from avoiding potential environmental damage caused by phosphorus releases as shown in Figure 2; (iii) supply the distribution of population in urban and rural areas, the treatment level of the WRRFs, and the phosphorus recovery points as a function of the WRRF scale in the studied regions of Canada and the United States as shown in Figure 3; and (iv) describe the distribution of the average phosphorus recovery cost, annual per capita phosphorus recovery costs, and the HAI per studied regions as shown in Figure 4. Data describing the WRRFs’ location and characteristics across the studied regions of Canada and the United States are retrieved from the HydroWASTE database (https://www.hydrosheds.org/products/hydrowaste), including their spatial coordinates, treatment level, treatment design capacity, and population served. The HydroWASTE database reports the WRRF treatment level as primary, secondary, and advanced treatment. Since the U.S. Environmental Protection Agency does not define numeric nutrient water quality criteria for secondary wastewater treatment effluents, we consider that only the WRRFs with advanced treatments have specific processes for removing phosphorus from the liquid effluent. To perform the analysis at the second-level divisions, data on total population, distribution of population in urban and rural areas, total income, and average annual income per capita are retrieved at the census division and county level for Canada and the United States, respectively. Data for the year 2020 is considered since it is the most recent information available for both countries. The first-level divisions level corresponds to census divisions of the United States, which provide territorial divisions similar in terms of development, demographic characteristics, and economic activities, being extensively used for collecting and analyzing data throughout the United States. A table of the states included in each United States census division can be found in the Supplementary Information file. The equivalent of the United States census divisions for Canada is the Canadian provinces and territories, although it must be noted that, unlike the case of the United States, their definition is guided by administrative and political considerations instead of statistical criteria.

Indexes of real expenditure per capita in the United States relative to those in Canada for categories of gross domestic income (GDI), Canada=100, on an International Comparison Project Classification (ICP) basis.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in New Canada, Maine, 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 15,315, while the mean income for the highest quintile (20% of households with the highest income) is 187,307. 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 324,073, which is 173.02% higher compared to the highest quintile, and 2116.05% higher compared to the lowest quintile.

https://i.neilsberg.com/ch/new-canada-me-mean-household-income-by-quintiles.jpeg" alt="Mean household income by quintiles in New Canada, Maine (in 2022 inflation-adjusted dollars))">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 2022 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 New Canada town median household income. You can refer the same here

Major wage settlements, including number of agreements, number of employees, average duration of agreements, first year average percentage wage adjustment, and annual average percentage wage adjustment, by jurisdiction, industry, sector, and cost of living adjustment (COLA), annually, from 1977 to 2020.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for canada in the U.S.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

This service shows the median household after-tax income in 2015 for Canada, by 2016 census division. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.

After-tax income - refers to total income less income taxes of the statistical unit during a specified reference period (for additional information refer to Total Income – 2016 Census Dictionary and After-tax Income – 2016 Census Dictionary). The median income of a specified group is the amount that divides the income distribution of that group into two halves.

Census division (CD) is the general term for provincially legislated areas (such as county, municipalité régionale de comté and regional district) or their equivalents. In other provinces and the territories where laws do not provide for such areas, Statistics Canada defines equivalent areas for statistical reporting purposes in cooperation with these provinces and territories. Census divisions are intermediate geographic areas between the province/territory level and the municipality (census subdivision).

To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.

Besides the variable described here, the dataset contains the id, name, type, province, population, land area and the number of private households for each census division.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for little canada, mn in the U.S.

Data on teachers' salaries in US dollars are presented.