This graph shows how the impact factor of ^ is computed. The left axis depicts the number of papers published in years X-1 and X-2, and the right axis displays their citations in year X.

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 Excel file contains example data as would be provided by an investigator to a collaborative statistician to analyze. Data are a permuted and edited version of real data provided to the authors during a statistical collaboration. The data are presented as commonly collected by investigators prior to working with a statistician, including several tabs of data in different domains (Set1, Set2, Demographics), colored cells, merged cells, cells with more than one data type, etc. as well as incomplete data and two systems of ID numbers. The file also includes a tab to link the different ID systems as well as tabs that have a "cleaned" version of the data (REVISEDSet1, REVISEDSet2) that would typically be provided after quality control identified some issues with the data that were then resolved by the investigator.

Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

Dataset

This dataset was created by almaas izdihar

Contents

This is the latest monthly (February 2014) statistical publication in relation to the linked HES (Hospital Episode Statistics) and MHMDS (Mental Health Minimum Data Set) data. The two data sets have been linked using specific patient identifiers collected in HES and MHMDS. The linkage allows the data sets to be linked in this manner from 2006-07; however, this report focuses on patients who were present in the two data sets in the period April 2013 to February 2014 only. The bridging file used for this publication was also released on 13 June 2014; it utilises the latest published Provisional (Monthly) HES data and year-to-date MHMDS data relating to the period April 2013 to February 2014. The HES-MHMDS linkage provides the ability to undertake national (within England) analysis along acute patient pathways for mental health service users' interactions with acute secondary care.

Descriptive statistics for the participants with complete data on the main variables in the study.

This dataset reflects is for the Individual Shelter & Rescue Statistics that were reported in 2018 for the 2017 Calendar year. Although PACFA requires this data to be submitted and takes all care possible to ensure the validity of this data, we do not control, and therefore guarantee, the complete accuracy, completeness and availability of data. PACFA believes this information to be within ± 4% margin of error. The CDA-PACFA is not responsible for any issues that may arise from the use of this data.

Colombia CO: Physicians: per 1000 People data was reported at 2.327 Ratio in 2020. This records an increase from the previous number of 2.252 Ratio for 2019. Colombia CO: Physicians: per 1000 People data is updated yearly, averaging 1.334 Ratio from Dec 1960 (Median) to 2020, with 35 observations. The data reached an all-time high of 2.327 Ratio in 2020 and a record low of 0.354 Ratio in 1960. Colombia CO: Physicians: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Health Statistics. Physicians include generalist and specialist medical practitioners.;World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.;Weighted average;This is the Sustainable Development Goal indicator 3.c.1 [https://unstats.un.org/sdgs/metadata/].

Data and statistical analysis scripts for manuscript on wheat root response to nitrate using X-ray CT and OpenSimRoot

X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil - [https://doi.org/10.1002/ppj2.20036]

The ZIP file contains:

• MCT1_Rcode.R - Statistics script for candidate single-timepoint experiment. Requires all CSV data files in the directory. User needs to set working directory to location of this script and the CSV data files before running.
• MCT1... .csv - 3 CSV data files required by the R script.
• MCT2_Rcode.R - Statistics script for time-series experiment. Requires all CSV data files in the directory. User needs to set working directory to location of this script and the CSV data files before running.
• MCT2... .csv - 3 CSV data files required by the R script.
• R_RooThProcessing.R - R code for aggregating root traits from RooTh software.
• Modelling folder - OpenSimRoot with model parameters and root data used in manuscript.

Dataset contains counts and measures for individuals from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 2.

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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).

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The variables for part 1 of the dataset are:

• Census usually resident population count
• Census night population count
• Age (5-year groups)
• Age (life cycle groups)
• Median age
• Birthplace (NZ born/overseas born)
• Birthplace (broad geographic areas)
• Ethnicity (total responses) for level 1 and ‘Other Ethnicity’ grouped by ‘New Zealander’ and ‘Other Ethnicity nec’
• Māori descent indicator
• Languages spoken (total responses)
• Official language indicator
• Gender
• Cisgender and transgender status – census usually resident population count aged 15 years and over
• Sex at birth
• Rainbow/LGBTIQ+ indicator for the census usually resident population count aged 15 years and over
• Sexual identity for the census usually resident population count aged 15 years and over
• Legally registered relationship status for the census usually resident population count aged 15 years and over
• Partnership status in current relationship for the census usually resident population count aged 15 years and over
• Number of children born for the sex at birth female census usually resident population count aged 15 years and over
• Average number of children born for the sex at birth female census usually resident population count aged 15 years and over
• Religious affiliation (total responses)
• Cigarette smoking behaviour for the census usually resident population count aged 15 years and over
• Disability indicator for the census usually resident population count aged 5 years and over
• Difficulty communicating for the census usually resident population count aged 5 years and over
• Difficulty hearing for the census usually resident population count aged 5 years and over
• Difficulty remembering or concentrating for the census usually resident population count aged 5 years and over
• Difficulty seeing for the census usually resident population count aged 5 years and over
• Difficulty walking for the census usually resident population count aged 5 years and over
• Difficulty washing for the census usually resident population count aged 5 years and over.

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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.

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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.

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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.

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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.

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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.

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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).

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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.

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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.

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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.

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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.

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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.

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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”.

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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.

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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.

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Percentages

To calculate percentages, divide the figure for the category of interest by the figure for 'Total stated' where this applies.

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Symbol

-997 Not available

-999 Confidential

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Inconsistencies in definitions

Please note that there may be differences in definitions between census classifications and those used for other data collections.

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.

To fully implement and monitor progress on the Sustainable Development Goals, decision makers everywhere need data and statistics that are accurate, timely, sufficiently disaggregated, relevant, accessible and easy to use. The Open SDG Data Hub promotes the exploration, analysis, and use of authoritative SDG data sources for evidence-based decision-making and advocacy. Its goal is to enable data providers, managers and users to discover, understand, and communicate patterns and interrelationships in the wealth of SDG data and statistics that are now available.The global Sustainable Development Goal indicators API gives programmatic access to the global indicators database using the OpenAPI specification. The database, maintained by the Statistics Division, released on 20 June 2018 contains over 1 million observations. However, this is not the number of unique observations, as several indicators and their data are repeated. For the complete list of the indicators that are repeated in the indicator framework please see https://unstats.un.org/sdgs/indicators/indicators-list/ .

Ahoy, data enthusiasts! Join us for a hands-on workshop where you will hoist your sails and navigate through the Statistics Canada website, uncovering hidden treasures in the form of data tables. With the wind at your back, you’ll master the art of downloading these invaluable Stats Can datasets while braving the occasional squall of data cleaning challenges using Excel with your trusty captains Vivek and Lucia at the helm.

Historical dataset showing Africa immigration statistics by year from N/A to N/A.

aAll data sets were collected from a single crystal.bValues in the parentheses are for the highest-resolution shell.

This publication provides the timeliest picture available of people using NHS funded secondary mental health, learning disabilities and autism services in England, excluding those who are solely in contact with Talking Therapies. This information will be of use to people needing access to information quickly for operational decision making and other purposes. More detailed information on the quality and completeness of these statistics is available in the Data Quality section, as well as within the Data Coverage and Data Quality VODIM and Integrity files available under 'Resources'. Please note, the methodology for MHS30f - Attended contacts in the RP with community mental health services for adult and older adults with severe mental illness has been updated to account for both the team ID recorded in the contact and referral tables. This is inline with other metrics that are similar. This brings this metric inline with other similar metrics but there maybe minor methodological differences that mean that summing the totals from other metrics may not match the values presented in this metric.

IE: Adjusted Net Enrollment Rate: Primary: % of Primary School Age Children data was reported at 99.678 % in 2015. This records an increase from the previous number of 99.236 % for 2014. IE: Adjusted Net Enrollment Rate: Primary: % of Primary School Age Children data is updated yearly, averaging 94.999 % from Dec 1971 (Median) to 2015, with 42 observations. The data reached an all-time high of 99.942 % in 2007 and a record low of 84.722 % in 1986. IE: Adjusted Net Enrollment Rate: Primary: % of Primary School Age Children data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ireland – Table IE.World Bank.WDI: Education Statistics. Adjusted net enrollment is the number of pupils of the school-age group for primary education, enrolled either in primary or secondary education, expressed as a percentage of the total population in that age group.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).