National and subnational mid-year population estimates for the UK and its constituent countries by administrative area, age and sex (including components of population change, median age and population density).

Labour market status by ethnic group, UK, published quarterly, non-seasonally adjusted. Labour Force Survey. These are official statistics in development.

The number of Pinterest users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 0.3 million users (+3.14 percent). After the ninth consecutive increasing year, the Pinterest user base is estimated to reach 9.88 million users and therefore a new peak in 2028. Notably, the number of Pinterest users of was continuously increasing over the past years.User figures, shown here regarding the platform pinterest, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

The number of Instagram users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 2.1 million users (+7.02 percent). After the ninth consecutive increasing year, the Instagram user base is estimated to reach 32 million users and therefore a new peak in 2028. Notably, the number of Instagram users of was continuously increasing over the past years.User figures, shown here with regards to the platform instagram, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

This publication covers annual estimates for waste collected by local authorities in England and the regions. These statistics are based on data submitted by all local authorities in England to WasteDataFlow on the waste they collect and manage.

The methodology and recycling explainer documents give background and context to this statistical notice, accompanying datasets and the waste and recycling measures they present.

There is also a further historical note on the definition of local authority collected waste relating to earlier releases.

The entire raw dataset is available in CSV format and can be found here: https://www.data.gov.uk/dataset/0e0c12d8-24f6-461f-b4bc-f6d6a5bf2de5/wastedataflow-local-authority-waste-management" class="govuk-link">WasteDataFlow - Local Authority waste management - data.gov.uk

Historic releases

https://webarchive.nationalarchives.gov.uk/ukgwa/20250102235615/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2022-2023

https://webarchive.nationalarchives.gov.uk/ukgwa/20230802024231/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results-202122" class="govuk-link">2021- 2022

https://webarchive.nationalarchives.gov.uk/ukgwa/20220503105415/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2020 - 2021

https://webarchive.nationalarchives.gov.uk/ukgwa/20210728220801/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2019-2020

https://webarchive.nationalarchives.gov.uk/ukgwa/20200604042448/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2018 - 2019

https://webarchive.nationalarchives.gov.uk/ukgwa/20190903035029/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2017 - 2018

https://webarchive.nationalarchives.gov.uk/ukgwa/20181207030346/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2016 - 2017

https://webarchive.nationalarchives.gov.uk/ukgwa/20170418015547/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2015 - 2016 This includes the ad hoc release entitled “Provisional 2016/17 local authority data on waste collection and treatment for England (April to June and July to September 2016)”.

https://webarchive.nationalarchives.gov.uk/ukgwa/20160512131028/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2014 - 2015

https://webarchive.nationalarchives.gov.uk/ukgwa/20150401112814/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2013 - 2014

https://webarchive.nationalarchives.gov.uk/ukgwa/20140321171631/https://www.gov.uk/government/publications/local-authority-collected-waste-management-annual-results" class="govuk-link">2012 - 2013

Historic datasets

Historic datasets

Data were gathered through citizen science volunteers, who used the i-Tree Canopy tool (https://canopy.itreetools.org/) to assess percentage canopy cover within ward boundaries. A User Guide was provided to the volunteers, with step-by-step instructions and pictorial support (https://cdn.forestresearch.gov.uk/2018/11/canopy_cover_webmap_user_guide_-_updated_march_2021.pdf). i-Tree Canopy randomly distributes points within a study area (ward boundary), overlain on Google aerial imagery. Users examine the points in sequence to determine whether the point lies over a tree canopy or not, classifying each point as either “tree” or “non-tree” accordingly. Typically 350 to 600 points were assessed per ward, leading to a standard error of less than 2%. Percentage tree canopy cover was calculated as (n/N)*100 where n is the number of “tree” points and N is the total number of sample points. Results were returned to Forest Research in the form of percentage canopy cover, standard error, number of points, and the i-Tree Canopy project file. Data quality was monitored through screening of submitted results by Forest Research project staff for all new participants, and at regular intervals for experienced contributors. Most wards were assessed only once. Where a ward was assessed by more than one contributor, the results were combined where possible. Field Attributes;country [Country] The country within which the Ward is located as defined by the Ward code. [E050000xx = England; N08000xxx = Northern Ireland; S1300xxxx = Scotland; W050000xx = Wales] wardcode [Ward code] The unique code associated with the Ward boundary. Ward boundaries are based on OS Boundary-Line data (OS data © Crown copyright and database right 2017). Most Ward boundaries are from the 2017 OS Boundary-Line dataset. However, a few users returned boundaries from the 2018 OS Boundary-Line dataset; the dataset was amended to reflect which boundary was used in the i-Tree Canopy assessment. wardname [Ward name] The name of the Ward boundary. Ward boundaries are based on OS Boundary-Line data (OS data © Crown copyright and database right 2017). Most Ward boundaries are from the 2017 OS Boundary-Line dataset. However, a few users returned boundaries from the 2018 OS Boundary-Line dataset; the dataset was amended to reflect which boundary was used in the i-Tree Canopy assessment. designated [Urban/Rural] Whether the Ward has been identified as an Urban or Rural Ward. Wards were classified as Urban or Rural based on size: wards larger than 1,000 Ha were classed as Rural. status [Status] Current analysis status of the ward. All Wards in the dataset have been Completed.survyear [Survey year] The year the i-Tree Canopy assessment was completed. Data collected between 2018 and 2022. percancov [Percentage canopy cover] The average canopy cover for the ward boundary as calculated by the i-Tree Canopy model. standerr [Standard Error] The Standard Error associated with the average canopy cover value as calculated by the i-Tree Canopy model. numpts [Number of points] Number of points completed for the i-Tree Canopy assessment of the ward. warea [Ward area] The area of the Ward boundary (m2)

This dataset contains all current National Non-Domestic Rating Accounts in Credit. The dataset represents a snapshot in time and is published on a 6 monthly rolling programme on 1 May and 1 November. The data will be published for two years from its inclusion on the website. Each assessment includes the following information: Assessment address, Reference number, Report extract date, Primary Liable party name, Primary Liable Party Contact Address, Billing Year, Entry Amount and Account Start and End Dates The information is reviewed prior to publishing to ensure that any personally identifiable data is removed. However, as all property address information is taken directly from the Valuation Office rating list there may be accounts that contain a personal name where necessary to identify the premise.

This data has been taken from LG Inform at http://lginform.local.gov.uk/ data reference ID 202. It shows the percentage of business rates collected in Plymouth between financial year 2008/2009 and 2015/2016. Percentage of Business rates collected - This is the amount of non-domestic rates collected during the year, expressed as a percentage of the amount of non-domestic rates due. County data is the sum of billing authorities. Source name: Communities and Local Government Collection name: Council tax collection rates Polarity: High is good Polarity is how sentiment is measured "Sentiment is usually considered to have "poles" positive and negative these are often translated into "good" and "bad" sentiment analysis is considered useful to tell us what is good and bad in our information stream

This dataset provides a summary of the Import Inspection statistics for Reduced Goods by Point of Entry (POE) 2013. Reduced goods are those where inspections are permitted at a less than 100% rate, becuase they are considered to be low risk imports. This dataset includes the fields: Type of Inspection (Mandatory - 100% inspection rate for high risk material; Controlled - where the commodity is subject to regulated inspections; Reduced - low-risk import goods for which inspections are permitted at a less than 100% rate), Botanical Name Variety/Type and Country of Origin, Number of consignments, Plant Health Movement Document (PHMD) supplied?, Consignment corrected total for PHMD, Inspection count, Inspected %, Reduced % Jan - Dec 2015, Reduced % Oct - Dec 2014, Reduced % Jan - Dec 2014, Reduced % Jan - Dec 2013 (these were the required check levels for these calendar periods), Reduced inspection rate, Document check count, Doc %, ID check count, ID check %, Failed physical, Failed physical %, Failed doc, Failed doc %, Failed ID, Failed ID %, Total failed, Total failed %. Percentage figures shown are for the reporting period indicated, and deonte the percentage of checks done on a named commodity for the reporting period. Attribution statement:

This data has been taken from LG Inform at http://lginform.local.gov.uk/ data reference ID 31. It shows the percentage of vulnerable people achieving independent living in Plymouth from financial year 2006/2007 to 2010/2011 Percentage of vulnerable people achieving independent living. This is the number of service users (i.e. people who are receiving a Supporting People Service) who have moved on from supported accommodation in a planned way, as a percentage of total service users who have left the service. This was previously reported as NI 141. Source name: Communities and Local Government Collection name: Supporting People Local System (SPLS) Polarity: High is good Polarity is how sentiment is measured "Sentiment is usually considered to have "poles" positive and negative these are often translated into "good" and "bad" sentiment analysis is considered useful to tell us what is good and bad in our information stream

This dataset contains all current National Non-Domestic Accounts in receipt of an exemption. The dataset represents a snapshot in time and is published on a 6 monthly rolling programme on 1 May and 1 November. The data will be published for two years from its inclusion on the website. Each assessment includes the following information: Assessment address, Reference number, Report extract date, Primary Liable party name, Primary Liable Party Contact Address,Relief Type and Relief Start Date. The information is reviewed prior to publishing to ensure that any personally identifiable data is removed. However, as all property address information is taken directly from the Valuation Office rating list there may be accounts that contain a personal name where necessary to identify the premise.

The number of LinkedIn users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 1.5 million users (+4.51 percent). After the eighth consecutive increasing year, the LinkedIn user base is estimated to reach 34.7 million users and therefore a new peak in 2028. User figures, shown here with regards to the platform LinkedIn, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

This dataset provides a summary of the Import Inspection Statistics for Controlled Plant Goods by Point of Entry (POE) 2013. Controlled goods are those which are subject to formal plant health controls when imported, including the provision of a phytosanitary certificate. 'Phytosanitary Certificates' are produced by APHA (or an overseas equivalent agency) to certify that a plant commodity is healthy prior to export. This dataset includes the fields: Type of Inspection (Mandatory - 100% inspection rate for high risk material; Controlled - where the commodity is subject to regulated inspections; Reduced - low-risk import goods for which inspections are permitted at a less than 100% rate), Import Inspection Location Name, Botanical Name, Number of consignments, Plant Health Movement Document (PHMD) supplied?, Consignment corrected total for PHMD, Inspection count, Inspected %, Document check count, Doc %, ID check count, ID check %, Failed physical, Failed physical %, Failed doc, Failed doc %, Failed ID, Failed ID %, Total failed, Total failed %. 'PHMD' are required where goods have cleared customs in one EU country and are moving through into a different EU country. Percentage figures shown are for the reporting period indicated, and deonte the percentage of checks done on a named commodity for the reporting period. Attribution statement: ©Crown Copyright, APHA 2016

This report presents findings from the third (wave 3) in a series of follow up reports to the 2017 Mental Health of Children and Young People (MHCYP) survey, conducted in 2022. The sample includes 2,866 of the children and young people who took part in the MHCYP 2017 survey. The mental health of children and young people aged 7 to 24 years living in England in 2022 is examined, as well as their household circumstances, and their experiences of education, employment and services and of life in their families and communities. Comparisons are made with 2017, 2020 (wave 1) and 2021 (wave 2), where possible, to monitor changes over time.

Police recorded crime figures by Police Force Area and Community Safety Partnership areas (which equate in the majority of instances, to local authorities).

This file contains the National Statistics Postcode Lookup (NSPL) for the United Kingdom as at May 2022 in Comma Separated Variable (CSV) and ASCII text (TXT) formats. To download the zip file click the Download button. The NSPL relates both current and terminated postcodes to a range of current statutory geographies via ‘best-fit’ allocation from the 2011 Census Output Areas (national parks and Workplace Zones are exempt from ‘best-fit’ and use ‘exact-fit’ allocations). It supports the production of area based statistics from postcoded data. The NSPL is produced by ONS Geography, who provide geographic support to the Office for National Statistics (ONS) and geographic services used by other organisations. The NSPL is issued quarterly. (File size - 196 MB).

Archive of 1971 census aggregate data for England, Wales and Scotland, as made available originally on the Casweb (https://casweb.ukdataservice.ac.uk) platform.