Get benchmark data on various farm types using business risk management program information in Ontario. Farm types include:

• apple
• grapes
• beef cow calf
• beef feedlot
• dairy goat
• field crops
• greenhouse cucumbers
• greenhouse flowers
• greenhouse peppers
• greenhouse tomatoes
• sheep
• swine farrow to finish
• swine finish

Includes data related to:

• number of farms
• financial measures
• financial ratios
• production

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.

This area has been identified as important for species movement. Analysis was completed on the natural heritage features of the fragmented areas of this region. This region has considerable development pressures in Ontario and New York State.

Official GEO title: Algonquin to Adirondack (A2A) Landscape Analysis

*[A2A]: Algonquin to Adirondack

This dataset includes the R-script, final dataset, and the accompanying codebook that was used to conduct analysis of elementary school student infections in Ontario, Canada for the 2020-21 school year. Analysis appears in the pre-print by Srivastava et al. (2022), 'Effects of socio-economic factors on elementary school student COVID-19 infections in Ontario, Canada', medRxiv. https://doi.org/10.1101/2022.02.04.22270413

About this dataset

Context

The dataset tabulates the median household income in Ontario. It can be utilized to understand the trend in median household income and to analyze the income distribution in Ontario by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Ontario, OR Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Ontario, OR: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Ontario, OR
• Ontario, OR households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Ontario median household income. You can refer the same here

The Analysis of Regional Wood Supply (ARWoodS) data is updated annually to incorporate changes to wood supply, projected wood supply use, and planned and actual harvest levels. The data is used to identify critical regional and provincial wood supply issues. Examples of data: * available harvest volume (supply) * current and projected wood supply use * planned harvest volume * historical (actual) wood use ARWoodS is produced by the Ministry of Natural Resources and Forestry (MNRF) as part of the Provincial Wood Supply Strategy. *[ARWoodS]: Analysis of Regional Wood Supply

Includes regional and ministry-wide assessments of emergencies at the Ministry of the Attorney General. Emergencies include commercial power failure, severe weather, civil protest and others.

Sap samples from sugar maple trees across the Canadian province of Ontario were collected in 2019. These samples were minimally prepared and analyzed in both positive ESI and negative ESI by C18 and HILIC chromatography. This was done to uncover the chemical changes that occurred in the sap over the season. This will serve as the base for future analysis of maple syrup where compounds that may be responsible for specific organoleptic properties can be linked back to precursors found here in the sap.

This dataset contains the Mplus analysis files for the multi-level modelling analysis of student COVID-19 school infections in Ontario for the 2020-21 school year that appears in the paper, 'Effects of socio-economic factors on elementary school student infections in Ontario, Canada (Srivastava et al., 2022, medRxiv). Model 1 calculates the proportion of variance attributable to Level 1 (school level) and Level 2 (area level). Model 2 includes Level 1 and Level 2 predictors. Models 1 and 2 are computed for cumulative cases and cumulative incidence (per 1000 students). Both .inp and .out files can be read using a .txt editor.

The spatial extent of service territory boundaries for Ontario's local distribution companies (LDCs). ENERGY's data consumers require visualization of the service territory boundaries of local distribution companies (LDCs) to support policy development.

Status

On going: data is being continually updated

Maintenance and Update Frequency

Monthly: data is updated each month

Contact

Governance Strategy and Analytics Branch, analyticsfinance@ontario.ca

The dataset presented here offers a collection of both matchup data and code for preprocessing, processing, and postprocessing satellite imagery, along with tools for data visualization. The primary objective of this research was to conduct a time-series analysis of Remote Sensing (RS)-derived chlorophyll-a (Chl-a) maps of Western Lake Ontario and Hamilton Harbour. This analysis spans a decade, from 2013 to 2023, utilizing imagery from the Landsat 8 and 9 satellites. The matchup data are presented in the "Matchup_Data.xlsx" file. Simultaneously, the "RS_Data.xlsx" file contains the description of the RS data used. The included codebase, housed in the "Code" directory, facilitates the entire spectrum of data handling—from preprocessing raw satellite data to generating insightful visual representations. Final Estimated Chl-a maps, in the format of PNG, as well as an animated time-series video of the maps are also available in the Data folder.