Data from several censuses and surveys are available for download from this site. Using the Advanced Search option presented on the homepage, users can easily begin searching for data for their geographic area. The US Census Bureau recommends starting by selecting Geographies to narrow down the area of interest. From there, users can either search by Topic, Race & Ethnic Groups, Industry Codes or EEO Occupation Code. Once a dataset has been selected, users are presented with a variety of options, such as Modify Table, Add/Remove Geographies, Bookmark/Save, Print, Download and Create a Map. Data can be downloaded as a shapefile, PDF, Excel Spreadsheet or Rich Text Format (.rtf).

The Census Program Data Viewer (CPDV) is an advanced web-based data visualization tool that helps make statistical information more interpretable by presenting key indicators in a statistical dashboard. It also enables users to easily compare indicator values and identify relationships between indicators.

Students will explore U.S. census data to see the spatial differences in the United States’ population. The activity uses a web-based map and is tied to the AP Human Geography benchmarks. Learning outcomes:· Unit 2, A1: Geographical analysis of population (density, distribute and scale)· Unit 2, A3: Geographical analysis of population (composition: age, sex, income, education and ethnicity)· Unit 2, A4: Geographical analysis of population (patterns of fertility, mortality and health)Find more advanced human geography geoinquiries and explore all geoinquiries at http://www.esri.com/geoinquiries

Amazonia has been under considerable development pressure as croplands and pasture are established in areas formerly occupied by tropical forest and cerrado. Although this region is an important part of several important planetary biogeochemical cycles, the location and impact of human land use are not well understood. In particular, there is no existing satellite-based map of agriculture across the Amazon or Tocantins river drainage basins. Recent efforts have classified land cover across this vast region, although they disagree on the location and amount of cropland and do not directly address pasture, a land use that has grown in importance in the last 2 decades. Here we present an analysis of land cover and land use practices over the Amazon and Tocantins basins of South America. In this study, we demonstrate how satellite imagery and agricultural censuses can be merged in order to provide a geographically explicit, fine- scale description of land cover and land use practices. The result depicts the fraction of each 5-min (9 x 9 km) grid cell that was devoted to agricultural activity during the mid-1990s. The resultant map retains many of the characteristics of the agricultural census data, but with a much finer spatial resolution. During the mid-1990s, cultivated area is estimated to have been 1.7 x 10(7) ha (2.5% of the basin), natural pasture is estimated at 3.3 x 10(7) ha (4.9% of the basin), and planted pasture is estimated to cover 3.3 x 10(7) ha (4.9% of the basin). Perhaps more important than the quantities, however, is that these data sets provide a new blend of ground- based and satellite-based spatially explicit data. This snapshot can be used as a basis to project either forward or backward in time, as a new check of finer scale land use classifications or as a driver of ecosystem models.

Employment Service (ES) is one component of the suite of services known as Employment Ontario (EO). ES provides Ontarians with access to all the employment services and supports they need in one location, so they can find and keep a job, apply for training, and plan a career that’s right for them. The goal of the ES program is to help Ontarians find sustainable employment.

Employment Service is delivered by third-party service providers at service delivery sites (SDS) across Ontario on behalf of the Ministry of Labour, Training and Skills Development (MLTSD). The services provided by ES are tailored to meet the individual needs of each client and can be provided one-on-one or in a group setting.

Employment Service has two broad categories: unassisted and assisted services.Unassisted services, or the Resource and Information (RI) service component, provides individuals with information on local training and employment opportunities, community service supports, and resources to support independent or “unassisted” job search. These services can be delivered through structured orientation or information sessions (on or off site), e-learning sessions, or one-to-one sessions up to two days in duration. The RI component also helps employers to attract and recruit employees and skilled labour by posting positions and offering opportunities to participate in job fairs and other community events.

This service component is available to all Ontarians as there are no eligibility or access requirements.

Assisted services are offered to individuals who display the need for more intensive, structured, and/or one-on-one employment supports, and includes the following components: job search assistance (including individualized assistance in career goal setting, skills assessment, and interview preparation) job matching, placement and incentives (which match client skills and interests with employment opportunities, and include placement into employment, on-the-job training opportunities, and incentives to employers to hire ES clients), and job training/retention (which supports longer-term attachment to or advancement in the labour market or completion of training)

Each assisted services client has a service plan, which is developed with the assistance of the service provider. This service plan lists all of the ES components that the client accesses, and the service provider monitors, evaluates, and adjusts this plan over the duration of the service plan. When an assisted services client completes the ES components of his/her service plan, the service provider closes the service plan (i.e. exit). As closed service plans cannot be reopened, if the client subsequently returns to access the assisted services of Employment Service (either at the same service delivery site or a different service delivery site), a new service plan is created.

To be eligible for assisted services, clients must be unemployed (defined as working less than an average of twenty hours a week) and not participating in full-time education or training. Clients are also assessed on a number of suitability indicators covering economic, social and other barriers to employment, and service providers are to prioritize serving those clients with multiple suitability indicators.Definitions for fields in this layer are available in the abbreviated Technical Dictionary.

Yearly census of Gulf Stream Warm Core Ring formation from 1980 to 2017. This continuous census file contains the formation and demise times and locations, and the area at formation for all 961 WCRs formed between 1980 and 2017 that lived for a week or more. Each row represents a unique Warm Core Ring and is identified by a unique alphanumeric code 'WEyyyymmddA', where 'WE' represents a Warm Eddy (as identified in the analysis charts); 'yyyymmdd' is the year, month and day of formation; and the last character 'A' represents the sequential sighting of the eddies in a particular year. For example, the first ring in 2017 having a trailing alphabet of 'E' indicates that four rings were carried over from 2016 which are still observed on January 1, 2017. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson acquisition_description=The census data is an analysis product from a set of charts prepared by Jenifer Clark (JC). An example chart is shown in Figure 1a of Gangopadhyay et al. (2019). The collection of charts of the GS and surrounding waters has been annotated with satellite data indicating temperature. Using infra-red (IR) imagery, satellite altimetry data, and surface in-situ temperature data, oceanographic analyses were produced for this region in the form of 2-3 day composite charts in a consistent manner. These charts show the location, extent and temperature signature of currents (GS, shelf-slope front), warm and cold-core rings (WCRs and CCRs), other eddies, shingles, intrusions, and other water mass boundaries in the Gulf of Maine, over Georges Bank and in the Middle Atlantic Bight.

The basis data source of those charts was individual IR\u00a0temperature\u00a0images from the NOAA polar-orbiting satellites (NOAA-5 in the early 1980s to NOAA-18 recently) at 6-12 hourly intervals. These images were captured by the Advanced Very High Resolution Radiometer (AVHRR) and AVHRR2 instruments, both of\u00a0which had a resolution of 1.1 km over the last four decades. Each individual image has a different lookup table (or colormap) for temperature that resolves 256 distinct sets of intensity, hue, and saturation of color within the available and retrievable IR signal range.\u00a0 This allows for accurate identification of the small-scale features in each image. The analyst locates all of the small scale features in each individual satellite SST image within a three-day period. The locations and boundaries of the features (GS, WCR, CCR , and other smaller scale entities) are remapped onto a 3-day composite image for that period.\u00a0The 3-day composite image has a fixed and broad (5-30\u00b0C) range of temperature with similar 256-set indexing, which by itself could not resolve the features. Note that individual images with high-resolution within a narrower band of temperature range also have clouds, which are eliminated (or at least minimized) during the process of generating the 3-day composites.\u00a0 The 3-day composite helps to visualize the whole GS and its rings in a broader region (like Figure 1a); while the individual images help resolve the features at a very high resolution. The 3-day composite images are regularly produced by NOAA and/or the Johns Hopkins University Applied Physics Lab (fermi) group (see http://fermi.jhuapl.edu for more details). awards_0_award_nid=810174 awards_0_award_number=OCE-0815679 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0815679 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=David L. Garrison awards_0_program_manager_nid=50534 awards_1_award_nid=810186 awards_1_award_number=OCE-1657853 awards_1_data_url=https://www.nsf.gov/awardsearch/showAward?AWD_ID=1657853 awards_1_funder_name=NSF Division of Ocean Sciences awards_1_funding_acronym=NSF OCE awards_1_funding_source_nid=355 awards_1_program_manager=Dr Baris M. Uz awards_1_program_manager_nid=713922 awards_2_award_nid=810188 awards_2_award_number=NOAA-NA11NOS0120038 awards_2_funder_name=National Oceanic and Atmospheric Administration awards_2_funding_acronym=NOAA awards_2_funding_source_nid=352 cdm_data_type=Other comment=Warm Core Ring Census, 1980-2017 A. Gangopadhyay (UMass-Dartmouth), G. Gawarkiewicz (WHOI) Yearly census of Warm Core Ring formation from 1980 to 2017 in the N. Atlantic version date: 2020-05-06 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 dataset_current_state=Final and no updates defaultDataQuery=&time<now doi=10.26008/1912/bco-dmo.810182.1 Easternmost_Easting=-54.96 geospatial_lat_max=43.82 geospatial_lat_min=35.78 geospatial_lat_units=degrees_north geospatial_lon_max=-54.96 geospatial_lon_min=-75.0 geospatial_lon_units=degrees_east infoUrl=https://www.bco-dmo.org/dataset/810182 institution=BCO-DMO metadata_source=https://www.bco-dmo.org/api/dataset/810182 Northernmost_Northing=43.82 param_mapping={'810182': {'Latitude_F': 'flag - latitude', 'Longitude_F': 'flag - longitude'}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/810182/parameters people_0_affiliation=University of Massachusetts Dartmouth people_0_affiliation_acronym=UMass Dartmouth people_0_person_name=Avijit Gangopadhyay people_0_person_nid=810178 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=Woods Hole Oceanographic Institution people_1_affiliation_acronym=WHOI people_1_person_name=Glen Gawarkiewicz people_1_person_nid=734777 people_1_role=Co-Principal Investigator people_1_role_type=originator people_2_affiliation=Woods Hole Oceanographic Institution people_2_affiliation_acronym=WHOI BCO-DMO people_2_person_name=Nancy Copley people_2_person_nid=50396 people_2_role=BCO-DMO Data Manager people_2_role_type=related project=GLOBEC_PRS_Freshwater Inputs projects_0_acronym=GLOBEC_PRS_Freshwater Inputs projects_0_description=This research addresses several mechanisms by which freshwater influx might impact the primary production of Calanus finmarchicus in the northern North Atlantic Ocean. Variability in the winter North Atlantic Oscillation index is related to changes in various physical and biological parameters across the entire North Atlantic, but the mechanisms underlying those relationships are not well known. Understanding basin-to-regional connections is important for interpreting patterns of variability observed on both sides of the Atlantic during the core GLOBEC study period (1993-1999) and from earlier observations, and inferring process, whether local or remote, from those observed patterns. The proposed research is focused on: (1) comparing and contrasting the impact of freshwater influx to the eastern and western sides of the North Atlantic, (2) understanding the development and maintenance of a possible three-gyre configuration of Calanus finmarchicus distribution in the North Atlantic, and (3) predicting the projected trends and variations in the North Atlantic Ocean based on IPCC projections for upcoming decades. This project seeks a synthetic understanding of how basin- and global-scales changes in climate force physical processes that in turn determine local- and regional-scale biological communities, with a particular focus on freshwater forcing of circulation, mixing, and marine ecosystems within the North Atlantic Ocean. It is pan-regional in scope, building upon the successes of the U.S. GLOBEC program in the Western North Atlantic (and its other regions) to address climate variability issues spanning the entire northern North Atlantic Ocean. Its research approaches include: synthesis of datasets across the North Atlantic, multi-scale coupled physical/biological modeling, and comparative regional studies. In all these respects it responds directly to the U.S. GLOBEC Pan-Regional Synthesis Announcement of Opportunity. Two graduate students will participate in this project. Results will be disseminated by peer-reviewed scientific publications, presentations at national conferences, and to other Pan-Regional GLOBEC investigators. Model output will be made available via the Rutgers OPeNDAP server. The investigators will give public lectures in Schools of Massachusetts, Maine and New Jersey on the importance of NAO and its impact on the regional ecosystem as part of an ongoing K-12 outreach program. The forecast scenarios for the next two decades will increase awareness of Climate Change. Dr. Fei Chai is a New Investigator to the GLOBEC program and will bring considerable expertise from his associations in the Pacific and in the Climate Change communities. Finally, this project sets the stage for post-GLOBEC end-to-end studies in the North Atlantic (e.g., the BASIN program). projects_0_end_date=2013-06 projects_0_geolocation=North Atlantic projects_0_name=Collaborative Research: GLOBEC Pan Regional Synthesis: The Effect of Varying Freshwater Inputs on Regional Ecosystems in the North Atlantic projects_0_project_nid=810175 projects_0_start_date=2008-07 sourceUrl=(local files) Southernmost_Northing=35.78 standard_name_vocabulary=CF Standard Name Table v55 version=1 Westernmost_Easting=-75.0 xml_source=osprey2erddap.update_xml() v1.5

Premium B2C Consumer Database - 269+ Million US Records

Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

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Geographic Coverage: Complete US (all 50 states)

Compliance Status: CCPA compliant with consent management

Targeting Categories Available

Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

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Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

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The Land and Water Development Division of FAO is developing a global information system of water and agriculture with the objective to provide users with comprehensive information on the state of agricultural water management across the world. Such a system should help in assessing the role of irrigation in global food production and the relation between irrigation and water scarcity. The system combines classical country-based statistics on all aspects of agricultural water management (water resources and use, irrigation, drainage, etc.), known as AQUASTAT, and a set of maps, data and models combined through a Geographical Information System (GIS). Africa is the first continent for which the information system has been completed.

The Atlas of Water Resources and Irrigation in Africa is available on CD-ROM published as part of FAO Land and Water Digital Media Series (#13). GIS coverages from the Atlas can be downloaded from the FAO-UN GeoNetwork Portal to Spatial Data and Information at [http://www.fao.org/geonetwork/srv/en/main.search]. The coverages are also available as interactive maps.

The CD-ROM contains all the information collected and processed concerning the African continent, namely:

1. A set of digital tables and maps on water resources and irrigation at continental level and by river basin (major basins and sub-basins) resulting from simulations on the water balance model.
2. A set of GIS coverages and Avenue scripts on water resources and irrigation (Annex 1) intended for advanced users willing to adapt the model to their specific needs.
3. A georeferenced database of African dams in Microsoft® Excel.
4. AQUASTAT country profiles for the 53 countries of Africa.

GIS coverages and interactive maps from FAO-UN GeoNetwork include:

1. Hydrological Basins in Africa
2. Inland Water Bodies in Africa
3. Rivers of Africa
4. Database of African Dams
5. Irrigation Cropping Pattern Zones in Africa

The programme was partly financed by the Dutch Directorate-General for International Cooperation through the Associate Professional Officer Programme. The geographical modelling tool was initially developed with technical assistance of the Center for Research in Water Resources of the University of Texas in Austin under the joint FAO/UNESCO project Water Balance of Africa.

Dataset, GDB, and Online Map created by Renee Haley, NMCDC, May 2023 DATA ACQUISITION PROCESS

Scope and purpose of project: New Mexico is struggling to maintain its healthcare workforce, particularly in Rural areas. This project was undertaken with the intent of looking at flows of healthcare workers into and out of New Mexico at the most granular geographic level possible. This dataset, in combination with others (such as housing cost and availability data) may help us understand where our healthcare workforce is relocating and why.

The most relevant and detailed data on workforce indicators in the United States is housed by the Census Bureau's Longitudinal Employer-Household Dynamics, LEHD, System. Information on this system is available here:

https://lehd.ces.census.gov/

The Job-to-Job flows explorer within this system was used to download the data. Information on the J2J explorer can ve found here:

https://j2jexplorer.ces.census.gov/explore.html#1432012

The dataset was built from data queried with the LED Extraction Tool, which allows for the query of more intersectional and detailed data than the explorer. This is a link to the LED extraction tool:

https://ledextract.ces.census.gov/

The geographies used are US Metro areas as determined by the Census, (N=389). The shapefile is named lehd_shp_gb.zip, and can be downloaded under this section of the following webpage: 5.5. Job-to-Job Flow Geographies, 5.5.1. Metropolitan (Complete). A link to the download site is available below:

https://lehd.ces.census.gov/data/schema/j2j_latest/lehd_shapefiles.html

DATA CLEANING PROCESS

This dataset was built from 8 non intersectional datasets downloaded from the LED Extraction Tool.

Separate datasets were downloaded in order to obtain detailed information on the race, ethnicity, and educational attainment levels of healthcare workers and where they are migrating.

Datasets included information for the four separate quarters of 2021. It was not possible to download annual data, only quarterly. Quarterly data was summed in a later step to derive annual totals for 2021.

4 datasets for healthcare workers moving OUT OF New Mexico, with details on race, ethnicity, and educational attainment, were downloaded. 1 contained information on educational attainment, 2 contained information on 7 racial categories identifying as non- Hispanic, 3 contained information on those same 7 categories also identifying as Hispanic, and 4 contained information for workers identifying as white and Hispanic.

4 datasets for healthcare worker moving INTO New Mexico, with details on race, ethnicity, and educational attainment, were downloaded with the same details outlined above.

Each dataset was cleaned according to Data Template which kept key attributes and discarded excess information. Within each dataset, the J2J Indicators reflecting 6 different types of job migration were totaled in order to simplify analysis, as this information was not needed in detail.

After cleaning, each set of 4 datasets for workers moving INTO New Mexico were joined. The process was repeated for workers moving OUT OF New Mexico. This resulted 2 main datasets.

These 2 main datasets still listed all of the variables by each quarter of 2021. Because of this the data was split in JMP, so that attributes of educational attainment, race and ethnicity, of workers migrating by quarter were moved from rows to columns. After this, summary columns for the year of 2021 were derived. This resulted in totals columns for workers identifying as: 6 separate races and all ethnicities, all races and Hispanic, white-Hispanic, and workers of 6 different education levels, reflecting how many workers of each indicator migrated to and from metro areas in New Mexico in 2021.

The data split transposed duplicate rows reflecting differing worker attributes within the same metro area, resulting in one row for each metro area and reflecting the attributes in columns, thus resulting in a mappable dataset.

The 2 datasets were joined (on Metro Area) resulting in one master file containing information on healthcare workers entering and leaving New Mexico.

Rows (N=389) reflect all of the metro areas across the US, and each state. Rows include the 5 metro areas within New Mexico, and New Mexico State.

Columns (N=99) contain information on worker race, ethnicity and educational attainment, specific to each metro area in New Mexico.

78 of these rows reflect workers of specific attributes moving OUT OF the 5 specific Metro Areas in New Mexico and totals for NM State. This level of detail is intended for analyzing who is leaving what area of New Mexico, where they are going to, and why.

13 Columns reflect each worker attribute for healthcare workers moving INTO New Mexico by race, ethnicity and education level. Because all 5 metro areas and New Mexico state are contained in the rows, this information for incoming workers is available by metro area and at the state level - there is less possability for mapping these attributes since it was not realistic or possible to create a dataset reflecting all of these variables for every healthcare worker from every metro area in the US also coming into New Mexico (that dataset would have over 1,000 columns and be unmappable). Therefore this dataset is easier to utilize in looking at why workers are leaving the state but also includes detailed information on who is coming in.

The remaining 8 columns contain geographic information.

GIS AND MAPPING PROCESS

The master file was opened in Arc GIS Pro and the Shapefile of US Metro Areas was also imported

The excel file was joined to the shapefile by Metro Area Name as they matched exactly

The resulting layer was exported as a GDB in order to retain null values which would turn to zeros if exported as a shapefile.

This GDB was uploaded to Arc GIS Online, Aliases were inserted as column header names, and the layer was visualized as desired.

SYSTEMS USED

MS Excel was used for data cleaning, summing NM state totals, and summing quarterly to annual data.

JMP was used to transpose, join, and split data.

ARC GIS Desktop was used to create the shapefile uploaded to NMCDC's online platform.

VARIABLE AND RECODING NOTES

Summary of variables selected for datasets downloaded focused on educational attainment:

J2J Flows by Educational Attainment

Summary of variables selected for datasets downloaded focused on race and ethnicity:

J2J Flows by Race and Ethnicity

Note: Variables in Datasets 1 through 4 downloaded twice, once for workers coming into New Mexico and once for those leaving NM. VARIABLE: LEHD VARIABLE DEFINITION LEHD VARIABLE NOTES DETAILS OR URL FOR RAW DATA DOWNLOAD

Geography Type - State Origin and Destination State

Data downloaded for worker migration into and out of all US States

Geography Type - Metropolitan Areas Origin and Dest Metro Area

Data downloaded for worker migration into and out of all US Metro Areas

NAICS sectors North American Industry Classification System Under Firm Characteristics Only downloaded for Healthcare and Social Assistance Sectors

Other Firm Characteristics No Firm Age / Size Detail Under Firm Characteristics Downloaded data on all firm ages, sizes, and other details.

Worker Characteristics Education, Race, Ethnicity

Non Intersectional data aside from Race / Ethnicity data.

Sex Gender

0 - All Sexes Selected

Age Age

A00 All Ages (14-99)

Education Education Level E0, E1, E2, E3, 34, E5 E0 - All Education Categories, E1 - Less than high school, E2 - High school or equivalent, no college, E3 - Some college or Associate’s degree, E4 - Bachelor's degree or advanced degree, E5 - Educational attainment not available (workers aged 24 or younger)

Dataset 1 All Education Levels, E1, E2, E3, E4, and E5

RACE

A0, A1, A2, A3, A4, A5 OPTIONS: A0 All Races, A1 White Alone, A2 Black or African American Alone, A3 American Indian or Alaska Native Alone, A4 Asian Alone, A5 Native Hawaiian or Other Pacific Islander Alone, SDA7 Two or More Race Groups

ETHNICITY

A0, A1, A2 OPTIONS: A0 All Ethnicities, A1 Not Hispanic or Latino, A2 Hispanic or Latino

Dataset 2 All Races (A0) and All Ethnicities (A0)

Dataset 3 6 Races (A1 through A5) and All Ethnicities (A0)

Dataset 4 White (A1) and Hispanic or Latino (A1)

Quarter Quarter and Year

Data from all quarters of 2021 to sum into annual numbers; yearly data was not available

Employer type Sector: Private or Governmental

Query included all healthcare sector workflows from all employer types and firm sizes from every quarter of 2021

J2J indicator categories Detailed types of job migration

All options were selected for all datasets and totaled: AQHire, AQHireS, EE, EES, J2J, J2JS. Counts were selected vs. earnings, and data was not seasonally adjusted (unavailable).

NOTES AND RESOURCES

The following resources and documentation were used to navigate the LEHD and J2J Worker Flows system and to answer questions about variables:

https://lehd.ces.census.gov/data/schema/j2j_latest/lehd_public_use_schema.html

https://www.census.gov/history/www/programs/geography/metropolitan_areas.html

https://lehd.ces.census.gov/data/schema/j2j_latest/lehd_csv_naming.html

Statewide (New

The data included in this dataset are bird and mammal observations from aboard research cruises. There are six tables of data: a transect log and observation log pairing for each of the three types of cruises. California Cooperative Oceanic Fisheries Investigations (CalCOFI) cruises are conducted quarterly off the coast of southern and central California. National Marine Fisheries (NMFS) cruises are a part of the Rockfish Recruitment Survey off the coast of southern and central California. Data were also collected aboard North Pacific Continuous Plankton Recorder (NPCPR) cruises from June 2002 through May 2006. Observations of birds and mammals include both number and behavior in addition to temporal and spatial information recorded along the cruise transect. Data are collected in order to research the interdependent aspects of the marine environment, including the effects of natural and human based climate change, and the broad implications and influences of ocean currents, weather patterns, fishing practices and coastal development on marine food webs and ecosystem processes.

Species and behavior definitions for data codes are available in the "Supplemental Documents" section.

The statistic shows the life expectancy at birth in India from 2013 to 2023. The average life expectancy at birth in India in 2023 was 72 years. Standard of living in India India is one of the so-called BRIC countries, an acronym which stands for Brazil, Russia, India and China, the four states considered the major emerging market countries. They are all in a similar advanced economic state and are expected to advance even further. India is also among the twenty leading countries with the largest gross domestic product / GDP, and the twenty countries with the largest proportion of global gross domestic product / GDP based on Purchasing Power Parity (PPP). Its unemployment rate has been stable over the past few years; India is also among the leading import and export countries worldwide. This alone should put India in a relatively comfortable position economically speaking, however, parts of the population of India are struggling with poverty and health problems. When looking at a comparison of the median age of the population in selected countries – i.e. one half of the population is older and the other half is younger –, it can be seen that the median age of the Indian population is about twenty years less than that of the Germans or Japanese. In fact, the median age in India is significantly lower than the median age of the population of the other emerging BRIC countries – Russia, China and Brazil. Additionally, the total population of India has been steadily increasing. Regarding life expectancy, India is neither among the countries with the highest, nor among those with the lowest life expectancy at birth. The majority of the Indian population is aged between 15 and 64 years, with only about 5 percent being older than 64.