Financial overview and grant giving statistics of Nor-Je-Nes Inc.
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Welcome to the Premier League Match Statistics dataset! ⚽ This guide will help you understand the structure of the dataset, key variables, and how to make the most of the data for analysis and predictions.
This dataset contains detailed match statistics from the English Premier League, including final scores, player statistics, team performance, goals, yellow cards, red cards, and more. It is ideal for analyzing team performance, predicting match outcomes, and exploring trends in football. This dataset is valuable for football enthusiasts, data analysts, and predictive model developer.
This dataset provides comprehensive match statistics from the English Premier League, including team performance, player stats, goals, assists, yellow/red cards, and more. It is ideal for football enthusiasts, analysts, and machine learning projects.
The dataset consists of multiple columns, each representing different aspects of a match:
Column Name | Description |
---|---|
Match_ID | Unique identifier for each match |
Date | Match date (YYYY-MM-DD format) |
Home_Team | Name of the home team |
Away_Team | Name of the away team |
Home_Goals | Goals scored by the home team |
Away_Goals | Goals scored by the away team |
Possession_% | Possession percentage of each team |
Shots_On_Target | Number of shots on target |
Yellow_Cards | Number of yellow cards given |
Red_Cards | Number of red cards given |
Player_of_Match | Best-performing player of the match |
Additional columns may provide more in-depth insights.
Here are some ideas to explore using this dataset:
✅ Analyze team performance trends over different seasons.
✅ Predict match outcomes using machine learning models.
✅ Identify key players based on goals, assists, and ratings.
✅ Explore disciplinary records (yellow/red cards) for fair play analysis.
Monthly data on federally administered Supplemental Security Income payments.
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The focus of Fingal County Council’s Community Development Office (CDO) is to develop engaged and integrated communities across Fingal, and successfully delivering the fantastic amenity is testament to that collaboration between the CDO and the local communities. The CDO team will continue to actively engage with the local volunteer board to ensure the highest standards of governance and management of the Community Centers for the enjoyment of current and future generations across the County of FingalThe day-to-day operation of the facility will be undertaken on the Council’s behalf by a local voluntary Board of Management who represent many groups in the area and Facility Management Company.visit www.fingal.ie/search?keywords=community+centres for further information.
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The Japanese Encephalitis (JE) Vaccines market is a critical segment within the global healthcare industry, primarily aimed at combating the viral infection caused by the Japanese encephalitis virus (JEV), which is endemic in various parts of Asia and the Western Pacific. This vaccine plays a crucial role in public
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Social Media Marketing Statistics: Social media marketing is a key part of any digital marketing plan today. With over 50% of the world’s population using social media, brands need to be active on these platforms. But it’s not just about making profiles and posting content. Effective social media marketing involves keeping up with changing algorithms and trends and understanding the behaviors of your target audience. Social media’s interactive and engaging nature helps businesses connect with their audience in ways they couldn’t before.
This opens up new opportunities for engaging with people, building the brand, and doing direct marketing. We shall shed more light on Social Media Marketing Statistics through this article.
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Dataset contains counts and measures for individuals from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 2.
The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification (unless otherwise stated).
The variables for part 1 of the dataset are:
Download lookup file for part 1 from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.
Footnotes
Te Whata
Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.
Geographical boundaries
Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.
Subnational census usually resident population
The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.
Population counts
Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts.
Caution using time series
Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).
Study participation time series
In the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.
About the 2023 Census dataset
For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.
Data quality
The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.
Concept descriptions and quality ratings
Data quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.
Disability indicator
This data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.
Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.
Using data for good
Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.
Confidentiality
The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.
Measures
Measures like averages, medians, and other quantiles are calculated from unrounded counts, with input noise added to or subtracted from each contributing value during measures calculations. Averages and medians based on less than six units (e.g. individuals, dwellings, households, families, or extended families) are suppressed. This suppression threshold changes for other quantiles. Where the cells have been suppressed, a placeholder value has been used.
Percentages
To calculate percentages, divide the figure for the category of interest by the figure for 'Total stated' where this applies.
Symbol
-997 Not available
-999 Confidential
Inconsistencies in definitions
Please note that there may be differences in definitions between census classifications and those used for other data collections.
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These files contain all statistics calculated in the publication: trough width (in magnetic latitude degrees), positions of both polar and equatorward trough boundaries, TEC gradients along both boundaries, and minimum depth of the trough. Trough detection rate was calculated from these files using the number of valid values out of NaNs (see MorphologyPlots.ipynb). File format is .pickle as they contain Python VARIABLES and can be loaded and modified using the Python pickle library (see MorphologyPlots.ipynp to see loading).Each file is named as follows:NH or SH for hemisphere _ (stat type) _ geomagnetic condition + seasonGeomagnetic conditions go as: q = quiet, m = moderate, a = activeSeasons go as: w = winter, p = spring, s = summer, f = fallExample: NH_EqDiff_qw = Northern hemisphere equatorward TEC difference (gradient), quiet wintertimePLEASE NOTE: SEASON labels are according to NORTHERN HEMISPHERE, Southern hemisphere seasons are swapped! If one desires to look at the SH in winter, they must load the files ending with s for summer, etc.
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Avg Hourly Earnings: sa: FA: Activities Related to Real Estate data was reported at 27.240 USD in May 2018. This records an increase from the previous number of 27.090 USD for Apr 2018. Avg Hourly Earnings: sa: FA: Activities Related to Real Estate data is updated monthly, averaging 23.010 USD from Mar 2006 (Median) to May 2018, with 147 observations. The data reached an all-time high of 27.240 USD in May 2018 and a record low of 19.250 USD in Mar 2006. Avg Hourly Earnings: sa: FA: Activities Related to Real Estate data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G033: Current Employment Statistics Survey: Average Weekly and Hourly Earnings: Seasonally Adjusted.
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BY: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data was reported at 1.000 Ratio in 2014. This records an increase from the previous number of 0.000 Ratio for 2013. BY: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data is updated yearly, averaging 20.000 Ratio from Dec 1985 (Median) to 2014, with 26 observations. The data reached an all-time high of 30.000 Ratio in 1991 and a record low of 0.000 Ratio in 2013. BY: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Belarus – Table BY.World Bank.WDI: Social: Health Statistics. Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births.;The country data compiled, adjusted and used in the estimation model by the Maternal Mortality Estimation Inter-Agency Group (MMEIG). The country data were compiled from the following sources: civil registration and vital statistics; specialized studies on maternal mortality; population based surveys and censuses; other available data sources including data from surveillance sites.;;
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These datasets correspond to the daily statistics of the website data.gouv.fr cut out by year. The data comes from stats.data.gouv.fr and is compiled at the end of each year. Starting in 2020, the statistics of the site and the API are now separated. This dataset only applies to the site from 2020. Data before 2020 and from 2020 are not comparable. Documentation of the different columns is available here.
Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).
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Imports: Services: ME: Travel: Education Related data was reported at 112.000 USD mn in 2016. This records an increase from the previous number of 109.000 USD mn for 2015. Imports: Services: ME: Travel: Education Related data is updated yearly, averaging 58.500 USD mn from Dec 1999 (Median) to 2016, with 18 observations. The data reached an all-time high of 112.000 USD mn in 2016 and a record low of 18.000 USD mn in 2004. Imports: Services: ME: Travel: Education Related data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.JA032: Trade Statistics: Services: Middle East.
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To help you get the biggest takeaways from all of these digital marketing stats, I want to share some trends in marketing that’s working for businesses right now.
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Imports: First 10 days: YoY: Passenger Cars data was reported at 41.700 % in Apr 2025. This records a decrease from the previous number of 43.400 % for Mar 2025. Imports: First 10 days: YoY: Passenger Cars data is updated monthly, averaging 1.100 % from Jan 2017 (Median) to Apr 2025, with 100 observations. The data reached an all-time high of 209.900 % in May 2021 and a record low of -63.600 % in Jul 2020. Imports: First 10 days: YoY: Passenger Cars data remains active status in CEIC and is reported by Korea Customs Service. The data is categorized under Global Database’s South Korea – Table KR.JA003: Trade Statistics: First 10 Days. [COVID-19-IMPACT]
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Turkey Vital Statistics: Dependency Ratio data was reported at 47.245 NA in 2017. This records an increase from the previous number of 47.158 NA for 2016. Turkey Vital Statistics: Dependency Ratio data is updated yearly, averaging 48.030 NA from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 50.360 NA in 2007 and a record low of 47.158 NA in 2016. Turkey Vital Statistics: Dependency Ratio data remains active status in CEIC and is reported by Turkish Statistical Institute. The data is categorized under Global Database’s Turkey – Table TR.G003: Vital Statistics.
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In 2020, TikTok brought in $33.4 billion in revenue.
Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).
This dataset is a polygon coverage of counties limited to the extent of the Pond Creek coal bed resource areas and attributed with statistics on the thickness of the Pond Creek coal zone, its elevation, and overburden thickness, in feet. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C.
Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).
Financial overview and grant giving statistics of Nor-Je-Nes Inc.