Eastern Cape

Selected building statistics of the private sector as reported by local government institutions. 

Data cited at: https://dataportal.opendataforafrica.org/rtufdnc/social This Dataset describes the list of common indicators from census datasets of African countries.

This release contains results of the monthly Survey of Consumer (Retail) Prices. The purpose of the survey is to collect and provide information regarding changes in the overall level of prices of all goods and services bought by the average household. This publication contains the CPI (Inflation) rates. The P0141 contains information on all urban areas and the Additional tables contains information for provinces, Primary urban areas, Secondary urban areas and rural areas. Average prices are calculated from data surveyed for the compilation of the consumer price index (CPI). Of the 412 items in the current CPI basket, 162 are included in the list of average prices. Selected items have average prices for two different sizes.

These Community Mobility Reports aim to provide insights into what has changed in response to policies aimed at combating COVID-19. The reports chart movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

This dataset compiles crimes committed at national and provincial levels in South Africa. Contact crime refers to crimes in which the victims are the targets of violence or instances where the victims are in the vicinity of property that criminals target and are subjected to the use of or threats of violence by perpetrators.

This statistical release contains information regarding the number of electricity units produced and consumed in South Africa, the number of units purchased and sold outside South Africa and the number of units distributed by Eskom according to province on a monthly basis. ARC: https://www.statssa.gov.za/?page_id=2643&PPN=P4141&SCH=73493

Data citation: Data retrieved from the Area Database of the Global Data Lab, https://globaldatalab.org/areadata/, version v4.2.Smits, J. GDL Area Database. Sub-national development indicators for research and policy making. GDL Working Paper 16-101 (2016).

The Global Consumption Database is a one-stop source of data on household consumption patterns in developing countries. It is designed to serve a wide range of users—from researchers seeking data for analytical studies to businesses seeking a better understanding of the markets into which they are expanding or those they are already serving.   The data are based on national household surveys, which collect information for a group of households representative of the entire country. For each of the countries covered, the resulting datasets have been used to calculate the share of the population at different levels of consumption.   Four levels of consumption are used to segment the market in each country: lowest, low, middle, and higher. They are based on global income distribution data, which rank the global population by income per capita. The lowest consumption segment corresponds to the bottom half of the global distribution, or the 50th percentile and below; the low consumption segment to the 51th–75th percentiles; the middle consumption segment to the 76th–90th percentiles; and the higher consumption segment to the 91st percentile and above.   The Global Consumption Database is the most comprehensive data source to date on consumer spending patterns in developing countries. It builds on the 2007 report The Next 4 Billion, published by IFC (a member of the World Bank Group) and the World Resources Institute.

This Dataset shows the modelled parasite rate for Plasmodium falciparum for the years 2000-2015 for all African countries where it is endemic. The Dataset shows the percentage of 2-10 year olds infected by the parasite for each year.

This dataset contains results of a Quarterly Labor Force Survey first conducted in January 2008, specifically designed to measure the dynamics of the South African labor market, producing indicators such as employment, unemployment and inactivity. It measures a variety of issues related to the labor market, including the official unemployment rate.

We define our day as midnight-to-midnight, Pacific time. Cities represent usage in greater metropolitan areas and are stably defined during this period. In many countries/regions and cities, relative volume has increased since January 13th, consistent with normal, seasonal usage of Apple Maps. Day of week effects are important to normalize as you use this data. Data that is sent from users’ devices to the Maps service is associated with random, rotating identifiers so Apple doesn’t have a profile of your movements and searches. Apple Maps has no demographic information about our users, so we can’t make any statements about the representativeness of our usage against the overall population. This information will be available for a limited time during the COVID‑19 pandemic.

Population and living conditions of South Africa, 2015

Postharvest loss profiles (PHL profiles) quantify the expected loss – as a percentage – at each point along the postharvest chain. This loss data is collected by reviewing scientific literature and is broken down by crop, type of farm and climate type (based on the Köppen-Geiger climate classification). These profiles provide percentage loss figures for the various crops throughout the value chain under varying conditions and are updated as new research becomes available."   For complete reference information and definitions, Please visit: https://www.aphlis.net/en/page/20/data-tables#/datatables?year=20&tab=references&metric=prc

Data cited at: https://southafrica.opendataforafrica.org/topryig

The Regional database contains annual data from 1995 to the most recent available year (generally 2022 for demographic and labor market data, 2021 for regional accounts, innovation and social statistics). 

The Regional database contains annual data from 1995 to the most recent available year (generally 2018 for demographic and labor market data, 2017 for regional accounts, innovation and social statistics). The data collection is undertaken by the Center for Entrepreneurship, SMEs, Regions and Cities (CFE). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and via downloads from the web-sites of National Statistical Offices and Eurostat

The Regional Database contains annual data from 1995 to the most recent available year. The data collection is undertaken by the Directorate of Public Governance and Territorial Development, within the Regional Development Policy division (GOV/RDP). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and through access to the web-sites of National Statistical Offices and Eurostat. The WPTI is responsible for developing regional (subnational) and urban statistics and providing analysis to support policy evaluations. The Regional Database includes statistics on the regional distribution of resources, regional disparities, and how regions contribute to national growth and the well-being of society. Under this framework, the Regional Database is one of the pillars for providing indicators to the publication OECD Regions at a Glance (link).

The Regional Database contains annual data from 1995 to the most recent available year (generally 2016 for demographic, 2015 for labor market data and 2014 for regional accounts, innovation and social statistics).

The Regional Database contains annual data from 1995 to the most recent available year (generally 2014 for demographic and labour market data, 2013 for regional accounts, innovation and social statistics).   In any analytical study conducted at sub-national levels, the choice of the territorial unit is of prime importance. The territorial grids (TL2 and TL3) used in this database are officially established and relatively stable in all member countries, and are used by many as a framework for implementing regional policies. This classification - which, for European countries, is largely consistent with the Eurostat classification - facilitates greater comparability of regions at the same territorial level. The differences with the Eurostat NUTS classification concern Belgium, Greece and the Netherlands where the NUTS 2 level correspond to the OECD TL3 and Germany where the NUTS1 corresponds to the OECD TL2 and the OECD TL3 corresponds to 97 spatial planning regions (Groups of Kreise). For the United Kingdom the Eurostat NUTS1 corresponds to the OECD TL2. Due to limited data availability, labour market indicators in Canada are presented for a different grid (groups of TL3 regions). Since these breakdowns are not part of the OECD official territorial grids, for the sake of simplicity they are labelled as Non Official Grids (NOG).

Data cited at: https://southafrica.opendataforafrica.org/SEDSA2016

Data cited at: https://southafrica.opendataforafrica.org/yrjlblg

This dataset provides data on literacy rates, primary and secondary school attendance rates access to improved water and sanitation, household access to electricity, and household ownership of radio and television. Unlike other datasets, notably the World Bank’s World Development Indicators (WDI), this dataset provides data at the subnational level, specifically the first administrative district level. Furthermore, the data is comparable both within and across countries. This subnational level of data allows for assessment of education and household characteristics at a more relevant level for allocation of resources and targeting development interventions.

Data cited at: https://southafrica.opendataforafrica.org/ybphjdg

Data cited at: The Water Footprint Network https://waterfootprint.org/en/ Topic: Product water footprint statistics Publication: https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/ Reference: Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577-1600. License: https://creativecommons.org/licenses/by-sa/3.0/    

Data cited at: The Water Footprint Network https://waterfootprint.org/en/ Topic: Product water footprint statistics Publication: https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/ Reference: Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577-1600. License: https://creativecommons.org/licenses/by-sa/3.0/