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Chart and table of population level and growth rate for the state of Louisiana from 1900 to 2024.
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Context
The dataset tabulates the data for the Louisiana population pyramid, which represents the Louisiana population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Louisiana Population by Age. You can refer the same here
This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.
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Resident Population in Louisiana was 4597.74000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, Resident Population in Louisiana reached a record high of 4681.34600 in January of 2016 and a record low of 1384.00000 in January of 1900. Trading Economics provides the current actual value, an historical data chart and related indicators for Resident Population in Louisiana - last updated from the United States Federal Reserve on June of 2025.
The 2023 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2023, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated or updated as part of the the 2023 BAS or the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.
https://www.louisiana-demographics.com/terms_and_conditionshttps://www.louisiana-demographics.com/terms_and_conditions
A dataset listing Louisiana cities by population for 2024.
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U.S. Census Bureau QuickFacts statistics for Rapides Parish, Louisiana. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
The 2015 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2010.
The State of Louisiana experienced widespread flooding during the extreme rainfall events of March and August 2016. The City of Central, Louisiana, which lies above the confluence of the Amite and Comite Rivers, is bordered on the East and West respectively by these rivers. The city had extensive damage from both events, in particular the August 2016 flood in which the river basins received up to 30 inches of documented rainfall. Many streamgages in the area recorded peak of record flood levels from the event. The US Geological Survey (USGS) in cooperation with the City of Central, created a digital flood inundation map library to depict estimated areal extents and depth of flooding along 14.5 and 20.2 mile reach lengths of the Amite and Comite Rivers. The maps were created using a 2-dimensional flow model calibrated to the March and August 2016 events as well as to the current stage-discharge ratings at USGS streamgaging stations 07377300 Amite River at Magnolia, Louisiana and 07378000 Comite River near Comite, Louisiana. The maps range from flood stage to the peak of record stage at the gaging stations. Annual peak flow data was analyzed to determine multiple flooding scenario possibilities between the two gages. This data release provides the ArcGIS files and metadata for these maps. In addition, the maps will be hosted by the USGS on an interactive web mapper accessible to the cooperator and the public at: https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program Use of the maps aids city officials and emergency managers in pre-planning for a flood event in areas such as road and bridge closures, staging of man power and materials, and estimation of affected population. The maps also aid the public in foreseeing their flood risk potential and helps them in their decision making regarding life and property.
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U.S. Census Bureau QuickFacts statistics for Prien CDP, Louisiana. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
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Chart and table of population level and growth rate for the Baton Rouge metro area from 1950 to 2025.
Polygon geometry with attributes displaying the 2010 Census low and moderate income block groups in East Baton Rouge Parish, Louisiana. Metadata
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Chart and table of population level and growth rate for the New Orleans metro area from 1950 to 2025.
A dataset showing the population of 70072 between 2010 and 2020.
A dataset showing the population of 70737 between 2010 and 2020.
IntroductionClimate Central’s Surging Seas: Risk Zone map shows areas vulnerable to near-term flooding from different combinations of sea level rise, storm surge, tides, and tsunamis, or to permanent submersion by long-term sea level rise. Within the U.S., it incorporates the latest, high-resolution, high-accuracy lidar elevation data supplied by NOAA (exceptions: see Sources), displays points of interest, and contains layers displaying social vulnerability, population density, and property value. Outside the U.S., it utilizes satellite-based elevation data from NASA in some locations, and Climate Central’s more accurate CoastalDEM in others (see Methods and Qualifiers). It provides the ability to search by location name or postal code.The accompanying Risk Finder is an interactive data toolkit available for some countries that provides local projections and assessments of exposure to sea level rise and coastal flooding tabulated for many sub-national districts, down to cities and postal codes in the U.S. Exposure assessments always include land and population, and in the U.S. extend to over 100 demographic, economic, infrastructure and environmental variables using data drawn mainly from federal sources, including NOAA, USGS, FEMA, DOT, DOE, DOI, EPA, FCC and the Census.This web tool was highlighted at the launch of The White House's Climate Data Initiative in March 2014. Climate Central's original Surging Seas was featured on NBC, CBS, and PBS U.S. national news, the cover of The New York Times, in hundreds of other stories, and in testimony for the U.S. Senate. The Atlantic Cities named it the most important map of 2012. Both the Risk Zone map and the Risk Finder are grounded in peer-reviewed science.Back to topMethods and QualifiersThis map is based on analysis of digital elevation models mosaicked together for near-total coverage of the global coast. Details and sources for U.S. and international data are below. Elevations are transformed so they are expressed relative to local high tide lines (Mean Higher High Water, or MHHW). A simple elevation threshold-based “bathtub method” is then applied to determine areas below different water levels, relative to MHHW. Within the U.S., areas below the selected water level but apparently not connected to the ocean at that level are shown in a stippled green (as opposed to solid blue) on the map. Outside the U.S., due to data quality issues and data limitations, all areas below the selected level are shown as solid blue, unless separated from the ocean by a ridge at least 20 meters (66 feet) above MHHW, in which case they are shown as not affected (no blue).Areas using lidar-based elevation data: U.S. coastal states except AlaskaElevation data used for parts of this map within the U.S. come almost entirely from ~5-meter horizontal resolution digital elevation models curated and distributed by NOAA in its Coastal Lidar collection, derived from high-accuracy laser-rangefinding measurements. The same data are used in NOAA’s Sea Level Rise Viewer. (High-resolution elevation data for Louisiana, southeast Virginia, and limited other areas comes from the U.S. Geological Survey (USGS)). Areas using CoastalDEM™ elevation data: Antigua and Barbuda, Barbados, Corn Island (Nicaragua), Dominica, Dominican Republic, Grenada, Guyana, Haiti, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, San Blas (Panama), Suriname, The Bahamas, Trinidad and Tobago. CoastalDEM™ is a proprietary high-accuracy bare earth elevation dataset developed especially for low-lying coastal areas by Climate Central. Use our contact form to request more information.Warning for areas using other elevation data (all other areas)Areas of this map not listed above use elevation data on a roughly 90-meter horizontal resolution grid derived from NASA’s Shuttle Radar Topography Mission (SRTM). SRTM provides surface elevations, not bare earth elevations, causing it to commonly overestimate elevations, especially in areas with dense and tall buildings or vegetation. Therefore, the map under-portrays areas that could be submerged at each water level, and exposure is greater than shown (Kulp and Strauss, 2016). However, SRTM includes error in both directions, so some areas showing exposure may not be at risk.SRTM data do not cover latitudes farther north than 60 degrees or farther south than 56 degrees, meaning that sparsely populated parts of Arctic Circle nations are not mapped here, and may show visual artifacts.Areas of this map in Alaska use elevation data on a roughly 60-meter horizontal resolution grid supplied by the U.S. Geological Survey (USGS). This data is referenced to a vertical reference frame from 1929, based on historic sea levels, and with no established conversion to modern reference frames. The data also do not take into account subsequent land uplift and subsidence, widespread in the state. As a consequence, low confidence should be placed in Alaska map portions.Flood control structures (U.S.)Levees, walls, dams or other features may protect some areas, especially at lower elevations. Levees and other flood control structures are included in this map within but not outside of the U.S., due to poor and missing data. Within the U.S., data limitations, such as an incomplete inventory of levees, and a lack of levee height data, still make assessing protection difficult. For this map, levees are assumed high and strong enough for flood protection. However, it is important to note that only 8% of monitored levees in the U.S. are rated in “Acceptable” condition (ASCE). Also note that the map implicitly includes unmapped levees and their heights, if broad enough to be effectively captured directly by the elevation data.For more information on how Surging Seas incorporates levees and elevation data in Louisiana, view our Louisiana levees and DEMs methods PDF. For more information on how Surging Seas incorporates dams in Massachusetts, view the Surging Seas column of the web tools comparison matrix for Massachusetts.ErrorErrors or omissions in elevation or levee data may lead to areas being misclassified. Furthermore, this analysis does not account for future erosion, marsh migration, or construction. As is general best practice, local detail should be verified with a site visit. Sites located in zones below a given water level may or may not be subject to flooding at that level, and sites shown as isolated may or may not be be so. Areas may be connected to water via porous bedrock geology, and also may also be connected via channels, holes, or passages for drainage that the elevation data fails to or cannot pick up. In addition, sea level rise may cause problems even in isolated low zones during rainstorms by inhibiting drainage.ConnectivityAt any water height, there will be isolated, low-lying areas whose elevation falls below the water level, but are protected from coastal flooding by either man-made flood control structures (such as levees), or the natural topography of the surrounding land. In areas using lidar-based elevation data or CoastalDEM (see above), elevation data is accurate enough that non-connected areas can be clearly identified and treated separately in analysis (these areas are colored green on the map). In the U.S., levee data are complete enough to factor levees into determining connectivity as well.However, in other areas, elevation data is much less accurate, and noisy error often produces “speckled” artifacts in the flood maps, commonly in areas that should show complete inundation. Removing non-connected areas in these places could greatly underestimate the potential for flood exposure. For this reason, in these regions, the only areas removed from the map and excluded from analysis are separated from the ocean by a ridge of at least 20 meters (66 feet) above the local high tide line, according to the data, so coastal flooding would almost certainly be impossible (e.g., the Caspian Sea region).Back to topData LayersWater Level | Projections | Legend | Social Vulnerability | Population | Ethnicity | Income | Property | LandmarksWater LevelWater level means feet or meters above the local high tide line (“Mean Higher High Water”) instead of standard elevation. Methods described above explain how each map is generated based on a selected water level. Water can reach different levels in different time frames through combinations of sea level rise, tide and storm surge. Tide gauges shown on the map show related projections (see just below).The highest water levels on this map (10, 20 and 30 meters) provide reference points for possible flood risk from tsunamis, in regions prone to them.
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Chart and table of population level and growth rate for the Shreveport metro area from 1950 to 2025.
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U.S. Census Bureau QuickFacts statistics for West Baton Rouge Parish, Louisiana. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
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U.S. Census Bureau QuickFacts statistics for Gardere CDP, Louisiana. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
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U.S. Census Bureau QuickFacts statistics for Ouachita Parish, Louisiana. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
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Chart and table of population level and growth rate for the state of Louisiana from 1900 to 2024.