This table contains 45 series, with data for years 2014 - 2014 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) State of origin (15 items: New York; Washington; Michigan; California; ...) Traveller characteristics (3 items: Trips; Nights; Spending in Canada).

This table contains 45 series, with data for years 2014 - 2014 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) State visited (15 items: Florida; New York; Washington; California; ...) Travel characteristics (3 items: Visits; Nights; Spending in country).

Monthly and annual Canadian arrivals of one or more nights to the U.S. are provided by Statistics Canada for analysis and reporting. A limited amount of U.S. resident travel to Canada is also reported at a monthly level. Monthly level data are reported by mode of transportation with a 3-4 month lag time. Annual data are made available to Tourism Industries at the end of May and a written report with graphics and spreadsheets is generally available in the late summer. The annual report analyzes travelers by province of origin, season of travel, mode of transportation, etc.

This table contains 45 series, with data for years 2014 - 2014 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Countries visited (15 items: United States; Mexico; United Kingdom; France; ...) Travel characteristics (3 items: Visits; Nights; Spending in country).

This table contains 3549 series, with data for years 1972 - 2018 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...) Country of residence (273 items: Total non-resident travellers, countries other than the United States; North America, Central America and Caribbean, total; Anguilla; Antigua and Barbuda; ...).

Number of vehicles travelling between Canada and the United States, by trip characteristics, length of stay and type of transportation. Data available monthly.

The Bureau of Transportation Statistics (BTS) Border Crossing Data provide summary statistics for inbound crossings at the U.S.-Canada and the U.S.-Mexico border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Border crossing data are collected at ports of entry by U.S. Customs and Border Protection (CBP). The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States.

This dataset provides a rich source of structured information that can be analyzed to uncover patterns, trends, and correlations in border crossing activities. The geographic coordinates allow for spatial analysis, such as mapping the distribution of crossings or integrating with other geographical datasets to study regional economic impacts, environmental effects, or the efficiency of border infrastructure.

From a data science perspective, several analyses could be performed with this dataset:

• Trend Analysis: By examining the "Value" field over time, data scientists can identify trends in border crossings for different types of vehicles or pedestrians. This could reveal whether certain types of crossings are becoming more or less frequent, which could be indicative of broader economic or social trends.
• Spatial Analysis: Using the latitude and longitude information, the dataset allows for detailed geographic analyses, such as identifying which states or regions see the most cross-border traffic or how traffic patterns change along the border.
• Comparative Analysis: By comparing the different measures of crossings (e.g., Trucks vs. Personal Vehicles), researchers can draw insights into the nature of cross-border movements.

About this dataset

Context

The dataset tabulates the population of Little Canada by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Little Canada. The dataset can be utilized to understand the population distribution of Little Canada by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Little Canada. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Little Canada.

Key observations

Largest age group (population): Male # 15-19 years (515) | Female # 60-64 years (543). 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.

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

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.

Variables / Data Columns

• Age Group: This column displays the age group for the Little Canada population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Little Canada is shown in the following column.
• Population (Female): The female population in the Little Canada is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Little Canada for each 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 Population by Gender. You can refer the same here

Context

Airports from https://openflights.org

Content

Airport ID Unique OpenFlights identifier for this airport. Name Name of airport. May or may not contain the City name. City Main city served by airport. May be spelled differently from Name. Country Country or territory where airport is located. See countries.dat to cross-reference to ISO 3166-1 codes. IATA 3-letter IATA code. Null if not assigned/unknown. ICAO 4-letter ICAO code. Null if not assigned. Latitude Decimal degrees, usually to six significant digits. Negative is South, positive is North. Longitude Decimal degrees, usually to six significant digits. Negative is West, positive is East. Altitude In feet. Timezone Hours offset from UTC. Fractional hours are expressed as decimals, eg. India is 5.5. DST Daylight savings time. One of E (Europe), A (US/Canada), S (South America), O (Australia), Z (New Zealand), N (None) or U (Unknown). See also: Help: Time Tz database time zone Timezone in "tz" (Olson) format, eg. "America/Los_Angeles". Type Type of the airport. Value "airport" for air terminals, "station" for train stations, "port" for ferry terminals and "unknown" if not known. In airports.csv, only type=airport is included. Source Source of this data. "OurAirports" for data sourced from OurAirports, "Legacy" for old data not matched to OurAirports (mostly DAFIF), "User" for unverified user contributions. In airports.csv, only source=OurAirports is included. The data is UTF-8 (Unicode) encoded.

Note: Rules for daylight savings time change from year to year and from country to country. The current data is an approximation for 2009, built on a country level. Most airports in DST-less regions in countries that generally observe DST (eg. AL, HI in the USA, NT, QL in Australia, parts of Canada) are marked incorrectly.

Acknowledgements

https://openflights.org

Inspiration

I imported this data set to be able to perform analytics on Airport data combined with other large data sets.

About this dataset

Context

The dataset tabulates the population of Canadian by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Canadian. The dataset can be utilized to understand the population distribution of Canadian by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Canadian. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Canadian.

Key observations

Largest age group (population): Male # 30-34 years (12) | Female # 0-4 years (22). 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.

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

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.

Variables / Data Columns

• Age Group: This column displays the age group for the Canadian population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Canadian is shown in the following column.
• Population (Female): The female population in the Canadian is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Canadian for each 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 Canadian Population by Gender. You can refer the same here

About this dataset

Context

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

Key observations

There is a majority of female population, with 60.74% 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 Canadian is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Canadian 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 Canadian Population by Race & Ethnicity. You can refer the same here

On the continental scale, climate is an important determinant of the distributions of plant taxa and ecoregions. To quantify and depict the relations between specific climate variables and these distributions, we placed modern climate and plant taxa distribution data on an approximately 25-kilometer (km) equal-area grid with 27,984 points that cover Canada and the continental United States (Thompson and others, 2015). The gridded climatic data include annual and monthly temperature and precipitation, as well as bioclimatic variables (growing degree days, mean temperatures of the coldest and warmest months, and a moisture index) based on 1961-1990 30-year mean values from the University of East Anglia (UK) Climatic Research Unit (CRU) CL 2.0 dataset (New and others, 2002), and absolute minimum and maximum temperatures for 1951-1980 interpolated from climate-station data (WeatherDisc Associates, 1989). As described below, these data were used to produce portions of the "Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America" (hereafter referred to as "the Atlas"; Thompson and others, 1999a, 1999b, 2000, 2006, 2007, 2012a, 2015). Evolution of the Atlas Over the 16 Years Between Volumes A & B and G: The Atlas evolved through time as technology improved and our knowledge expanded. The climate data employed in the first five Atlas volumes were replaced by more standard and better documented data in the last two volumes (Volumes F and G; Thompson and others, 2012a, 2015). Similarly, the plant distribution data used in Volumes A through D (Thompson and others, 1999a, 1999b, 2000, 2006) were improved for the latter volumes. However, the digitized ecoregion boundaries used in Volume E (Thompson and others, 2007) remain unchanged. Also, as we and others used the data in Atlas Volumes A through E, we came to realize that the plant distribution and climate data for areas south of the US-Mexico border were not of sufficient quality or resolution for our needs and these data are not included in this data release. The data in this data release are provided in comma-separated values (.csv) files. We also provide netCDF (.nc) files containing the climate and bioclimatic data, grouped taxa and species presence-absence data, and ecoregion assignment data for each grid point (but not the country, state, province, and county assignment data for each grid point, which are available in the .csv files). The netCDF files contain updated Albers conical equal-area projection details and more precise grid-point locations. When the original approximately 25-km equal-area grid was created (ca. 1990), it was designed to be registered with existing data sets, and only 3 decimal places were recorded for the grid-point latitude and longitude values (these original 3-decimal place latitude and longitude values are in the .csv files). In addition, the Albers conical equal-area projection used for the grid was modified to match projection irregularities of the U.S. Forest Service atlases (e.g., Little, 1971, 1976, 1977) from which plant taxa distribution data were digitized. For the netCDF files, we have updated the Albers conical equal-area projection parameters and recalculated the grid-point latitudes and longitudes to 6 decimal places. The additional precision in the location data produces maximum differences between the 6-decimal place and the original 3-decimal place values of up to 0.00266 degrees longitude (approximately 143.8 m along the projection x-axis of the grid) and up to 0.00123 degrees latitude (approximately 84.2 m along the projection y-axis of the grid). The maximum straight-line distance between a three-decimal-point and six-decimal-point grid-point location is 144.2 m. Note that we have not regridded the elevation, climate, grouped taxa and species presence-absence data, or ecoregion data to the locations defined by the new 6-decimal place latitude and longitude data. For example, the climate data described in the Atlas publications were interpolated to the grid-point locations defined by the original 3-decimal place latitude and longitude values. Interpolating the data to the 6-decimal place latitude and longitude values would in many cases not result in changes to the reported values and for other grid points the changes would be small and insignificant. Similarly, if the digitized Little (1971, 1976, 1977) taxa distribution maps were regridded using the 6-decimal place latitude and longitude values, the changes to the gridded distributions would be minor, with a small number of grid points along the edge of a taxa's digitized distribution potentially changing value from taxa "present" to taxa "absent" (or vice versa). These changes should be considered within the spatial margin of error for the taxa distributions, which are based on hand-drawn maps with the distributions evidently generalized, or represented by a small, filled circle, and these distributions were subsequently hand digitized. Users wanting to use data that exactly match the data in the Atlas volumes should use the 3-decimal place latitude and longitude data provided in the .csv files in this data release to represent the center point of each grid cell. Users for whom an offset of up to 144.2 m from the original grid-point location is acceptable (e.g., users investigating continental-scale questions) or who want to easily visualize the data may want to use the data associated with the 6-decimal place latitude and longitude values in the netCDF files. The variable names in the netCDF files generally match those in the data release .csv files, except where the .csv file variable name contains a forward slash, colon, period, or comma (i.e., "/", ":", ".", or ","). In the netCDF file variable short names, the forward slashes are replaced with an underscore symbol (i.e., "_") and the colons, periods, and commas are deleted. In the netCDF file variable long names, the punctuation in the name matches that in the .csv file variable names. The "country", "state, province, or territory", and "county" data in the .csv files are not included in the netCDF files. Data included in this release: - Geographic scope. The gridded data cover an area that we labelled as "CANUSA", which includes Canada and the USA (excluding Hawaii, Puerto Rico, and other oceanic islands). Note that the maps displayed in the Atlas volumes are cropped at their northern edge and do not display the full northern extent of the data included in this data release. - Elevation. The elevation data were regridded from the ETOPO5 data set (National Geophysical Data Center, 1993). There were 35 coastal grid points in our CANUSA study area grid for which the regridded elevations were below sea level and these grid points were assigned missing elevation values (i.e., elevation = 9999). The grid points with missing elevation values occur in five coastal areas: (1) near San Diego (California, USA; 1 grid point), (2) Vancouver Island (British Columbia, Canada) and the Olympic Peninsula (Washington, USA; 2 grid points), (3) the Haida Gwaii (formerly Queen Charlotte Islands, British Columbia, Canada) and southeast Alaska (USA, 9 grid points), (4) the Canadian Arctic Archipelago (22 grid points), and (5) Newfoundland (Canada; 1 grid point). - Climate. The gridded climatic data provided here are based on the 1961-1990 30-year mean values from the University of East Anglia (UK) Climatic Research Unit (CRU) CL 2.0 dataset (New and others, 2002), and include annual and monthly temperature and precipitation. The CRU CL 2.0 data were interpolated onto the approximately 25-km grid using geographically-weighted regression, incorporating local lapse-rate estimation and correction. Additional bioclimatic variables (growing degree days on a 5 degrees Celsius base, mean temperatures of the coldest and warmest months, and a moisture index calculated as actual evapotranspiration divided by potential evapotranspiration) were calculated using the interpolated CRU CL 2.0 data. Also included are absolute minimum and maximum temperatures for 1951-1980 interpolated in a similar fashion from climate-station data (WeatherDisc Associates, 1989). These climate and bioclimate data were used in Atlas volumes F and G (see Thompson and others, 2015, for a description of the methods used to create the gridded climate data). Note that for grid points with missing elevation values (i.e., elevation values equal to 9999), climate data were created using an elevation value of -120 meters. Users may want to exclude these climate data from their analyses (see the Usage Notes section in the data release readme file). - Plant distributions. The gridded plant distribution data align with Atlas volume G (Thompson and others, 2015). Plant distribution data on the grid include 690 species, as well as 67 groups of related species and genera, and are based on U.S. Forest Service atlases (e.g., Little, 1971, 1976, 1977), regional atlases (e.g., Benson and Darrow, 1981), and new maps based on information available from herbaria and other online and published sources (for a list of sources, see Tables 3 and 4 in Thompson and others, 2015). See the "Notes" column in Table 1 (https://pubs.usgs.gov/pp/p1650-g/table1.html) and Table 2 (https://pubs.usgs.gov/pp/p1650-g/table2.html) in Thompson and others (2015) for important details regarding the species and grouped taxa distributions. - Ecoregions. The ecoregion gridded data are the same as in Atlas volumes D and E (Thompson and others, 2006, 2007), and include three different systems, Bailey's ecoregions (Bailey, 1997, 1998), WWF's ecoregions (Ricketts and others, 1999), and Kuchler's potential natural vegetation regions (Kuchler, 1985), that are each based on distinctive approaches to categorizing ecoregions. For the Bailey and WWF ecoregions for North America and the Kuchler potential natural vegetation regions for the contiguous United States (i.e.,

Our Activity dataset reveals real-world behavior through detailed foot traffic metrics around POIs in the US, Canada, and Mexico — all GDPR-compliant and non-PII.

By capturing total visits, unique visitors, and frequency of visits, our dataset enables a precise view of how consumers move, behave, and engage with locations over time — helping brands uncover demand, evaluate performance, and outpace competitors.

Key data points include: - Total visits, unique visitors, and visit frequency - Daily, weekly, monthly, and quarterly aggregation - Movement patterns around and within trade areas - Cleaned, normalized, and updated daily - Non-PII, GDPR-compliant location intelligence

Ideal for demand sensing, competitive benchmarking, and performance analysis, this dataset helps retail, real estate, and investment teams unlock powerful insights across North America.

About this dataset

Context

The dataset tabulates the population of New Canada town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for New Canada town. The dataset can be utilized to understand the population distribution of New Canada town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in New Canada town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for New Canada town.

Key observations

Largest age group (population): Male # 10-14 years (45) | Female # 10-14 years (56). 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.

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

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.

Variables / Data Columns

• Age Group: This column displays the age group for the New Canada town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the New Canada town is shown in the following column.
• Population (Female): The female population in the New Canada town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in New Canada town for each 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 Population by Gender. You can refer the same here

International travel by non-Canadians visitors coming to Canada for a trip, by Canadians returning from a visit abroad and by other non-tourism travellers (e.g. crew), by port of entry (e.g. airport, border crossing). This table includes breakdowns by mode of transportation (e.g. plane, automobile (car), boat) and by duration (same-day, overnight). Data come from Frontier Counts, part of the Tourism Statistics Program.

This is the accompanying dataset to the following paper https://www.nature.com/articles/s41597-023-01975-w

Caravan is an open community dataset of meteorological forcing data, catchment attributes, and discharge daat for catchments around the world. Additionally, Caravan provides code to derive meteorological forcing data and catchment attributes from the same data sources in the cloud, making it easy for anyone to extend Caravan to new catchments. The vision of Caravan is to provide the foundation for a truly global open source community resource that will grow over time.

If you use Caravan in your research, it would be appreciated to not only cite Caravan itself, but also the source datasets, to pay respect to the amount of work that was put into the creation of these datasets and that made Caravan possible in the first place.

All current development and additional community extensions can be found at https://github.com/kratzert/Caravan

Channel Log:

23 May 2022: Version 0.2 - Resolved a bug when renaming the LamaH gauge ids from the LamaH ids to the official gauge ids provided as "govnr" in the LamaH dataset attribute files.

24 May 2022: Version 0.3 - Fixed gaps in forcing data in some "camels" (US) basins.

15 June 2022: Version 0.4 - Fixed replacing negative CAMELS US values with NaN (-999 in CAMELS indicates missing observation).

1 December 2022: Version 0.4 - Added 4298 basins in the US, Canada and Mexico (part of HYSETS), now totalling to 6830 basins. Fixed a bug in the computation of catchment attributes that are defined as pour point properties, where sometimes the wrong HydroATLAS polygon was picked. Restructured the attribute files and added some more meta data (station name and country).

16 January 2023: Version 1.0 - Version of the official paper release. No changes in the data but added a static copy of the accompanying code of the paper. For the most up to date version, please check https://github.com/kratzert/Caravan

10 May 2023: Version 1.1 - No data change, just update data description.

17 May 2023: Version 1.2 - Updated a handful of attribute values that were affected by a bug in their derivation. See https://github.com/kratzert/Caravan/issues/22 for details.

16 April 2024: Version 1.4 - Added 9130 gauges from the original source dataset that were initially not included because of the area thresholds (i.e. basins smaller than 100sqkm or larger than 2000sqkm). Also extended the forcing period for all gauges (including the original ones) to 1950-2023. Added two different download options that include timeseries data only as either csv files (Caravan-csv.tar.xz) or netcdf files (Caravan-nc.tar.xz). Including the large basins also required an update in the earth engine code

16 Jan 2025: Version 1.5 - Added FAO Penman-Monteith PET (potential_evaporation_sum_FAO_PENMAN_MONTEITH) and renamed the ERA5-LAND potential_evaporation band to potential_evaporation_sum_ERA5_LAND. Also added all PET-related climated indices derived with the Penman-Monteith PET band (suffix "_FAO_PM") and renamed the old PET-related indices accordingly (suffix "_ERA5_LAND").

This table contains 11559 series, with data for years 1972 - 2017 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (273 items: Canada; Newfoundland and Labrador; Argentia, Newfoundland and Labrador; Botwood, Newfoundland and Labrador; ...); Traveller characteristics (91 items: Total international travellers; Total non-resident travellers; United States residents entering Canada; United States residents entering Canada, automobile; ...).

About this dataset

Context

The dataset tabulates the population of Canadian by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Canadian. The dataset can be utilized to understand the population distribution of Canadian by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Canadian. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Canadian.

Key observations

Largest age group (population): Male # 15-19 years (176) | Female # 10-14 years (112). 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.

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

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.

Variables / Data Columns

• Age Group: This column displays the age group for the Canadian population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Canadian is shown in the following column.
• Population (Female): The female population in the Canadian is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Canadian for each 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 Canadian Population by Gender. You can refer the same here

Welcome to the data repository for requesting access to the Statcan Dialogue Dataset! Before requesting access, you can visit our website or read our EACL 2023 paper Requesting Access In order to use our dataset, you must agree to the terms of use and restrictions before requesting access (see below). We will manually review each request and grant access or reach out to you for further information. To facilitate the process, make sure that: Your Dataverse account is linked to your professional/research website, which we may review to ensure the dataset will be used for the intended purpose Your request is made with an academic (e.g. .edu) or professional email (e.g. @servicenow.com). To do this, your have to set your primary email to your academic/professional email, or create a new Dataverse account. If your academic institution does not end with .edu, or you are part of a professional group that does not have an email address, please contact us (see email in paper). Abstract: We introduce the StatCan Dialogue Dataset consisting of 19,379 conversation turns between agents working at Statistics Canada and online users looking for published data tables. The conversations stem from genuine intents, are held in English or French, and lead to agents retrieving one of over 5000 complex data tables. Based on this dataset, we propose two tasks: (1) automatic retrieval of relevant tables based on a on-going conversation, and (2) automatic generation of appropriate agent responses at each turn. We investigate the difficulty of each task by establishing strong baselines. Our experiments on a temporal data split reveal that all models struggle to generalize to future conversations, as we observe a significant drop in performance across both tasks when we move from the validation to the test set. In addition, we find that response generation models struggle to decide when to return a table. Considering that the tasks pose significant challenges to existing models, we encourage the community to develop models for our task, which can be directly used to help knowledge workers find relevant tables for live chat users.

This is a listing of Indigenous periodicals (newspapers, newsletters, magazines, and journals), arranged by title. It primarily includes material published in Canada, but also encompasses some titles from American states bordering Canada. The scope aims to include publications by Indigenous communities and organizations, and to exclude known material produced by governments and non-Indigenous organizations. The inventory represents known publications across Canada based on sources from OCLC, and known listings of these publications within the community. All items in the list are held in Canadian libraries, archives, and museums. The accuracy of these lists is unknown and not validated by Indigenous communities to our knowledge. The source data lists reflect the work of academic institutions describing the materials in their holdings. Indigenous communities may be listed as the primary creator, but this can only be validated upon investigation with the source materials and with Indigenous communities. The intent is threefold: to promote a list of Indigenous publications, and where they can be consulted or searched; to track digitization work by Canadian institutions and groups and facilitate digitization efforts in collaboration with relevant Indigenous communities; and to enable easy additions to, and corrections of, the list. It is important to note that this is not a search tool for the contents of the publications, but merely an inventory of titles, along with locations of the print and digital holdings. Data headings are Title, Title Family, In Scope, Status, Source of Information, Publisher/Issuing Org., Place of Publication, Province/State, Country, Print Run/Holdings, Notes, ISSN, OCLC Identifiers, Online, Format, Digitization Status, Canadian Repository Holdings, Language. For definitions of the headings, see The Dataset Document Workbook. This list stems from efforts by the Indigenous Historical Publications Working Group, working on behalf of the Council of Prairie and Pacific University Libraries (COPPUL). Input by Indigenous individuals, communities, organizations and publishers, as well as all researchers, libraries, archives, and museums is eagerly sought and welcomed. Please contact us for more information, comments, or to provide updates.