Money Supply M0 in Canada increased to 211967 CAD Million in September from 197753 CAD Million in August of 2025. This dataset provides - Canada Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Government of Canada Spend Data by Department dataset is a summary of procurement expenditure data by department. It is derived from expenditure data submitted annually from over 55 departments and agencies, and is grouped by commodity broken down by family, group, category and subcategory. The data covers about 95 per cent of government’s total expenditure on goods and services. This dataset details the Spend Data from April 2010 through to March 2016, and was compiled through a collaboration of efforts from participating departments and agencies; however since 2017, Public Services and Procurement Canada no longer receives the information centrally, and is therefore unable to continue the publication of this dataset. >Note: the framework used by the Government of Canada to classify commodities has evolved over time. When comparing the breakout of expenditures as reported in this dataset vs those in the earlier Archived, Government of Canada Spend Data dataset, the totals reported across the commodity framework will at times be different for FY2010/2011, FY2011/2012, FY12/13 and FY2013/2014. This is because the data specific to those fiscal years was re-calculated in FY2014/2015 for the release of this newer dataset (in January 2015), using the commodity reporting structure and organisation naming conventions that were current at that time. The overall totals reported for each fiscal year and each department would have remained the same across both reporting frameworks.

The Department of Public Services and Procurement Canada, in its role as Receiver General for Canada (RG), is responsible for the management and safeguarding of all federal government money. Many departments accept payments, and are required by legislation to ensure funds are deposited into the central Consolidated Revenue Fund at the Bank of Canada as quickly as possible. Departments work in conjunction with the Receiver General to establish appropriate banking facilities for their lines of business. Deposit facilities can include deposit accounts at nearby financial institution branches, credit card acceptance capabilities and online payment acceptance among others. Note that banking facilities can be established in both foreign and domestic locations. This dataset entitled “Departmental Deposit Facilities” provides details, extracted from the Government Banking System, of the banking facilities established by the Receiver General for federal departments. Updates will be posted quarterly.

Money Supply M2 in Canada increased to 2738161 CAD Million in September from 2736766 CAD Million in August of 2025. This dataset provides - Canada Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Note: as of 15 Feb 2024, this dataset has been archived and will no longer be updated. A new dataset Losses of public money or property as per the Public Accounts of Canada has been created, combining the data for all losses of public money or public property into one bilingual CSV file. This new combined losses dataset contains all existing data from the previously separated losses files, and will continue to be updated on an annual basis in conjunction with the publication of the Public Accounts of Canada. --- At the end of each fiscal year, government-wide financial information is published in the Public Accounts. This dataset, based on the Volume 3 of the Public Accounts, provides, by ministry, details for Losses of revenues due to fraud or willful misrepresentation that were discovered or detected during the reporting fiscal year. Information on losses of public money and property is required under the Treasury Board directive on losses of money or property. This dataset is from the Public Accounts of Canada and is not the official record of information. The official version of record can be found on the Receiver General website for the most recent fiscal year and the Library and Archives website for historical years.

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

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

Survey of Household Spending (SHS), average household spending, Canada, regions and provinces.

Money Supply M3 in Canada increased to 3933656 CAD Million in September from 3904228 CAD Million in August of 2025. This dataset provides - Canada Money Supply M3 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Little Canada, MN, 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, Little Canada did not include 7-person households. Across the different household sizes in Little Canada the mean income is $100,789, and the standard deviation is $44,773. The coefficient of variation (CV) is 44.42%. 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 $40,881. It then further increased to $110,552 for 6-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/little-canada-mn-median-household-income-by-household-size.jpeg" alt="Little Canada, MN 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 Little Canada median household income. You can refer the same here

The Canada Trademarks Dataset

18 Journal of Empirical Legal Studies 908 (2021), prepublication draft available at https://papers.ssrn.com/abstract=3782655, published version available at https://onlinelibrary.wiley.com/share/author/CHG3HC6GTFMMRU8UJFRR?target=10.1111/jels.12303

Dataset Selection and Arrangement (c) 2021 Jeremy Sheff

Python and Stata Scripts (c) 2021 Jeremy Sheff

Contains data licensed by Her Majesty the Queen in right of Canada, as represented by the Minister of Industry, the minister responsible for the administration of the Canadian Intellectual Property Office.

This individual-application-level dataset includes records of all applications for registered trademarks in Canada since approximately 1980, and of many preserved applications and registrations dating back to the beginning of Canada’s trademark registry in 1865, totaling over 1.6 million application records. It includes comprehensive bibliographic and lifecycle data; trademark characteristics; goods and services claims; identification of applicants, attorneys, and other interested parties (including address data); detailed prosecution history event data; and data on application, registration, and use claims in countries other than Canada. The dataset has been constructed from public records made available by the Canadian Intellectual Property Office. Both the dataset and the code used to build and analyze it are presented for public use on open-access terms.

Scripts are licensed for reuse subject to the Creative Commons Attribution License 4.0 (CC-BY-4.0), https://creativecommons.org/licenses/by/4.0/. Data files are licensed for reuse subject to the Creative Commons Attribution License 4.0 (CC-BY-4.0), https://creativecommons.org/licenses/by/4.0/, and also subject to additional conditions imposed by the Canadian Intellectual Property Office (CIPO) as described below.

Terms of Use:

As per the terms of use of CIPO's government data, all users are required to include the above-quoted attribution to CIPO in any reproductions of this dataset. They are further required to cease using any record within the datasets that has been modified by CIPO and for which CIPO has issued a notice on its website in accordance with its Terms and Conditions, and to use the datasets in compliance with applicable laws. These requirements are in addition to the terms of the CC-BY-4.0 license, which require attribution to the author (among other terms). For further information on CIPO’s terms and conditions, see https://www.ic.gc.ca/eic/site/cipointernet-internetopic.nsf/eng/wr01935.html. For further information on the CC-BY-4.0 license, see https://creativecommons.org/licenses/by/4.0/.

The following attribution statement, if included by users of this dataset, is satisfactory to the author, but the author makes no representations as to whether it may be satisfactory to CIPO:

The Canada Trademarks Dataset is (c) 2021 by Jeremy Sheff and licensed under a CC-BY-4.0 license, subject to additional terms imposed by the Canadian Intellectual Property Office. It contains data licensed by Her Majesty the Queen in right of Canada, as represented by the Minister of Industry, the minister responsible for the administration of the Canadian Intellectual Property Office. For further information, see https://creativecommons.org/licenses/by/4.0/ and https://www.ic.gc.ca/eic/site/cipointernet-internetopic.nsf/eng/wr01935.html.

Details of Repository Contents:

This repository includes a number of .zip archives which expand into folders containing either scripts for construction and analysis of the dataset or data files comprising the dataset itself. These folders are as follows:

• /csv: contains the .csv versions of the data files
• /do: contains Stata do-files used to convert the .csv files to .dta format and perform the statistical analyses set forth in the paper reporting this dataset
• /dta: contains the .dta versions of the data files
• /py: contains the python scripts used to download CIPO’s historical trademarks data via SFTP and generate the .csv data files

If users wish to construct rather than download the datafiles, the first script that they should run is /py/sftp_secure.py. This script will prompt the user to enter their IP Horizons SFTP credentials; these can be obtained by registering with CIPO at https://ised-isde.survey-sondage.ca/f/s.aspx?s=59f3b3a4-2fb5-49a4-b064-645a5e3a752d&lang=EN&ds=SFTP. The script will also prompt the user to identify a target directory for the data downloads. Because the data archives are quite large, users are advised to create a target directory in advance and ensure they have at least 70GB of available storage on the media in which the directory is located.

The sftp_secure.py script will generate a new subfolder in the user’s target directory called /XML_raw. Users should note the full path of this directory, which they will be prompted to provide when running the remaining python scripts. Each of the remaining scripts, the filenames of which begin with “iterparse”, corresponds to one of the data files in the dataset, as indicated in the script’s filename. After running one of these scripts, the user’s target directory should include a /csv subdirectory containing the data file corresponding to the script; after running all the iterparse scripts the user’s /csv directory should be identical to the /csv directory in this repository. Users are invited to modify these scripts as they see fit, subject to the terms of the licenses set forth above.

With respect to the Stata do-files, only one of them is relevant to construction of the dataset itself. This is /do/CA_TM_csv_cleanup.do, which converts the .csv versions of the data files to .dta format, and uses Stata’s labeling functionality to reduce the size of the resulting files while preserving information. The other do-files generate the analyses and graphics presented in the paper describing the dataset (Jeremy N. Sheff, The Canada Trademarks Dataset, 18 J. Empirical Leg. Studies (forthcoming 2021)), available at https://papers.ssrn.com/abstract=3782655). These do-files are also licensed for reuse subject to the terms of the CC-BY-4.0 license, and users are invited to adapt the scripts to their needs.

The python and Stata scripts included in this repository are separately maintained and updated on Github at https://github.com/jnsheff/CanadaTM.

This repository also includes a copy of the current version of CIPO's data dictionary for its historical XML trademarks archive as of the date of construction of this dataset.

Survey of Household Spending (SHS), average household spending by household type.

The Department of Public Works and Government Services Canada, in its role as Receiver General for Canada, is responsible for the management and safeguarding of all federal government money. These funds, which are used in the disbursement of all Government of Canada expenditures, investments and transfers are held in the Consolidated Revenue Fund, at the Bank of Canada. Funds may be collected by a department or a service provider and deposited to a concentrator account at a financial institution. Concentrator account balances are transferred each day to the Bank of Canada. Alternatively, funds may be deposited directly to the Consolidated Revenue Fund. This dataset provides details, as of April 1st, 2010, of all deposits made to the Consolidated Revenue Fund. Updates will be posted quarterly. Consolidated Revenue Fund Outflows are available in a separate dataset.

Government Revenues in Canada decreased to 37733 CAD Million in August from 42607 CAD Million in July of 2025. This dataset provides - Canada Government Revenues- actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset contains product prices from Amazon Canada, with a focus on price prediction. With a good amount of data on what price points sell the most, you can train machine learning models to predict the optimal price for a product based on its features and product name.

If you find this dataset useful, make sure to show your appreciation by upvoting! ❤️✨

Inspirations

This dataset is a superset of my Amazon Canada product price dataset. Another inspiration is this competition that awareded 100K Prize Money

What To Do?

• Your objective is to create a prediction model that will assist sellers in pricing their products within the optimal price range to generate the most sales.
• The dataset includes various data points, such as the number of reviews, rating, best seller status, and items sold last month.
• You can select specific factors (e.g., over 100 reviews = optimal price for the product) and then divide the dataset into products priced optimally vs products priced unoptimally.
• By utilizing techniques like vectorizing product names and features, you can train a model to provide the optimal price for a product, which sellers or businesses might find valuable.

How to know if a product sells?

• I would prefer to use the number of reviews as a metric to determine if a product sells. More reviews = more sales, right?
• According to one source only 1-2% of buyers leave a review
• So if we multiply the reviews for a product by 50x, then we would get a good understanding how many units has sold.
• If we then multiple the product price by number of units sold, we'd get the total revenue generated by the product

How is this useful?

• Sellers and businesses can leverage your model to determine the optimal price for their products, thereby maximizing sales.
• Businesses can assess the profitability of a product and plan their supply chain accordingly.

Average and median market, total and after-tax income of individuals by visible minority group, Indigenous group and immigration status, Canada and provinces.

Money Supply M1 in Canada increased to 1716375 CAD Million in September from 1710881 CAD Million in August of 2025. This dataset provides - Canada Money Supply M1 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Total domestic expenditures on research and development (R&D) as percentage of gross domestic product (GDP). This table is included in Section D: Postsecondary education: Research and development of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.

The Canada Emergency Response Benefit Act passed on March 25, 2020 to provide income support for Canadian workers whose employment income has been disrupted by COVID-19. Through the Canada Emergency Response Benefit (CERB) the Government of Canada is providing a taxable benefit of $2,000 every 4 weeks for up to 16 weeks to eligible workers who have lost income or stopped working due to COVID-19. Applications for CERB are being made via Canada Revenue Agency (CRA) and Service Canada (SC). Employment and Social Development Canada (ESDC) has compiled data on various metrics related to applications submitted and distributed through both Departments.

The dataset used in this analysis is derived from food price data spanning the years 2017 to 2023. The primary source for this dataset is Statistics Canada, the national statistical agency of Canada. The dataset covers a range of food prices, offering insights into trends and patterns over the specified period. For more detailed information or access to the original dataset, please visit the official Statistics Canada website at : https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1810024502