This dataset tracks annual diversity score from 2022 to 2023 for Learn DC PCS School District vs. District of Columbia

In 2023, 38.8 percent of residents of the District of Columbia were white. A further 40.9 percent of the population were Black or African American, and 12 percent of D.C. residents were Hispanic or Latino in that same year.

About this dataset

Context

The dataset tabulates the Washington Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Washington, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of Washington.

Key observations

Among the Hispanic population in Washington, regardless of the race, the largest group is of Other Hispanic or Latino origin, with a population of 54,850 (70.54% of the total Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Origin for Hispanic or Latino population include:

• Mexican
• Puerto Rican
• Cuban
• Other Hispanic or Latino

Variables / Data Columns

• Origin: This column displays the origin for Hispanic or Latino population for the Washington
• Population: The population of the specific origin for Hispanic or Latino population in the Washington is shown in this column.
• % of Total Hispanic Population: This column displays the percentage distribution of each Hispanic origin as a proportion of Washington total Hispanic or Latino population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Washington Population by Race & Ethnicity. You can refer the same here

This dataset tracks annual diversity score from 2000 to 2023 for The Seed Pcs Of Washington Dc vs. District Of Columbia and SEED PCS School District

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Washington. The dataset can be utilized to gain insights into gender-based income distribution within the Washington population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Washington, among individuals aged 15 years and older with income, there were 237,294 men and 268.30 thousand women in the workforce. Among them, 146,116 men were engaged in full-time, year-round employment, while 149,395 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 2.65% fell within the income range of under $24,999, while 3.16% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 56.28% of men in full-time roles earned incomes exceeding $100,000, while 47.06% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Washington median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Washington. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2012 and 2022, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In Washington, the median household income for the households where the householder is White increased by $10,137(7.28%), between 2012 and 2022. The median household income, in 2022 inflation-adjusted dollars, was $139,221 in 2012 and $149,358 in 2022.
• Black or African American: In Washington, the median household income for the households where the householder is Black or African American increased by $10,762(21.47%), between 2012 and 2022. The median household income, in 2022 inflation-adjusted dollars, was $50,129 in 2012 and $60,891 in 2022.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

https://i.neilsberg.com/ch/washington-dc-median-household-income-by-race-trends.jpeg" alt="Washington, DC median household income trends across races (2012-2022, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Washington.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• Please note: 2020 1-Year ACS estimates data was not reported by Census Bureau due to impact on survey collection and analysis during COVID-19, thus for large cities (population 65,000 and above) median household income data is not available.
• Please note: All incomes have been adjusted for inflation and are presented in 2022-inflation-adjusted dollars.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Washington median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Washington. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Washington population by race & ethnicity, the population is predominantly Black or African American. This particular racial category constitutes the majority, accounting for 44.66% of the total residents in Washington. Notably, the median household income for Black or African American households is $60,891. Interestingly, despite the Black or African American population being the most populous, it is worth noting that White households actually reports the highest median household income, with a median income of $149,358. This reveals that, while Black or African Americans may be the most numerous in Washington, White households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/washington-dc-median-household-income-by-race.jpeg" alt="Washington median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Washington.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Washington median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Washington. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Washington population by race & ethnicity, the population is predominantly Black or African American. This particular racial category constitutes the majority, accounting for 43.26% of the total residents in Washington. Notably, the median household income for Black or African American households is $60,089. Interestingly, despite the Black or African American population being the most populous, it is worth noting that White households actually reports the highest median household income, with a median income of $166,774. This reveals that, while Black or African Americans may be the most numerous in Washington, White households experience greater economic prosperity in terms of median household income.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Washington.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Washington median household income by race. You can refer the same here

Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: 2022 Wards (State Legislative Districts [Upper Chamber]). Current Vintage: 2019-2023. ACS Table(s): DP05. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

The District of Columbia is home to a very diverse tree canopy, but it is not self-sustaining. In order to promote overall canopy health, ensure tree diversity, and match each new planting to a suitable planting site, the city's Urban Forestry Administration chooses the best available tree from a selection of 130 species and cultivars. The following presentation will introduce readers to the trees that make the District of Columbia's canopy unique.Washington, DC stands apart from most other US cities when it comes to trees. Trees were considered so essential that they were included as an integral part of Pierre L'Enfant's original design. The L'Enfant Plan, drafted in 1791, reserved space in the public right-of-way exclusively for trees and DC remains the "City of Trees." Agency Website.

DC 2050 presents an opportunity for the District to identify future challenges and opportunities and consider how to meet them in the next two decades. The DC Office of Planning (OP) will work with residents, community-based organizations, businesses, and elected officials to develop policies that guide how new buildings are added as the District's population and economy grow over the coming years. Through an inclusive and robust public process, the District’s diverse communities will be invited to imagine the kind of city they want for themselves, their neighbors, and their children. Our approach for DC 2050:Community-centeredEngagement will reach residents who face the greatest barriers to involvement. Policies will be developed and assessed based on their impact on these populations.Data-drivenOP will use data in new ways to help residents learn how the Comprehensive Plan's policies are likely to impact their communities.User-friendlyA shorter, visually-appealing, and well-organized document will set priorities that can be easily understood by residents, property owners, investors, and community-based organizations.Outcome-orientedThe Comprehensive Plan will clearly explain the changes DC residents can expect for the District and their community.

This dataset includes historical and recent information on the freshwater mollusk communities from the middle Olt River (Romania), along with the environmental parameters in the sampling sites and their spatial coordinates, as well as the species' functional traits and niche measures. The historical information dates back to the XIXth century, and comes from old literature and museum collections, the more recent data (1995-2000) and was derived from original research or literature, while the present-day data was collected during a field survey in May 2020. The study area is an 83 km section along the middle Olt River, between the town of Făgăraș (45.8512° N, 24.9733° E) and the Carpathian gorges (45.5317° N, 24.2721° E), in the region of Transylvania, Romania. Parts of this dataset were used in two papers, one currently under consideration for publication in Scientific Reports: Sîrbu, I., Benedek, A.M., Brown, B.L., Sîrbu, M. - Native versus alien communities: canonical ordination and variation partitioning with multiple response and predictor matrices disentangle structural and functional responses (2022), and the other published in 2021: Sîrbu, I., Benedek, A.M. & Sîrbu, M. Variation partitioning in double-constrained multivariate analyses: linking communities, environment, space, functional traits, and ecological niches. Oecologia 197, 43-59 (2021). In Sîrbu et al. (2022), using both historical and recent data, we aimed to: - disentangle and test the effects of hydrotechnical works - especially building of reservoirs (dams for hydroenergetic power) - environment, space, time, and non-native mollusk species on structural and functional dynamics of native freshwater mollusk communities; - investigate the differences in responses of native and alien species to the same predictors, and characterize the reversed effects of predictor ability of communities on external variables; - test effects of non-native species and communities on structural and functional diversity of natives, and - develop a novel approach and method for analyzing and expressing relationships between native and alien communities while accounting also for their responses to environment and space. In Sîrbu et al. (2021), based only on the present-day data, we defined, measured, and partitioned the CENTS space, the acronym coming from Community - Environment - Niche - (functional) Traits - Space. We proposed an algorithm to disentangle and quantify the overlapping effects of E-S (environment and space) and T-N (traits and ecological niche) variable groups on the community, which can be also used for other predictor data tables, such as a table with ecological indicator values or with phylogenetical relationships, and it also may be extended to include more than two data tables for sites or species. Our second objective was to summarize how species relate to resources and their availability in the environment, synthesize this information in a standardized way, and use these novel measures to apply the algorithm mentioned above, including an N data table, measuring the ecological niche features of the species. For this goal, we proposed a new standardized metric of niche complementarity (dissimilarity) for both categorical and continuous resources, which also account for the availability of resources in the environment. We used this metric to define and measure the species' uniqueness and one more aspect of the community diversity, the niche-based diversity (ND). We explored relationships between diversity measures and environment predictors, highlighting the use of ND in impact assessment.

This dataset tracks annual diversity score from 2015 to 2023 for Harmony DC PCS School District vs. District of Columbia

Washington, DC stands apart from most other US cities when it comes to trees. Trees were considered so essential that they were included as an integral part of Pierre L'Enfant's original design. The L'Enfant Plan, drafted in 1791, reserved space in the public right-of-way exclusively for trees and DC remains the "City of Trees." Agency Website.

Demographic and clinical characteristics of DC Cohort participants stratified by availability of sequence data.

This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-bes/543/170. The abstract below was extracted from the Level 0 data package and is included for context: This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The database consists of four tables. Sites, Surveys, Taxalist, and Birds. Sites records thje sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: The tables form a set. Here are the fields and relationship information: Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count seen heard direction time_class

At its core, Washington, DC is an international city. Nearly a quarter of the metropolitan area's (MSA) population is foreign-born.1 In addition, Washington, DC is home to a diverse linguistic landscape, where residents speak 168 languages.2The city provides unparalleled transportation convenience and direct access to a global community, with three international airports offering access to 183 worldwide destinations.With more than 640 international companies having a presence in the metropolitan area and 176 embassies calling the nation's capital home, the international community is woven into the fabric of the city, making it one of the most dynamic cities in the world.

The District of Columbia is the only non-state entity of the United States with a share of electoral votes in U.S. presidential elections. Since the 23rd Amendment to the U.S. Constitution granted Washington D.C. representation in these elections, the nation's capital has had three electoral votes in each election since 1964. In these 16 elections, Washington D.C.'s citizens have chosen the overall winner seven times, giving a success rate of 44 percent, which is the lowest in the country. As of 2024, no U.S. president has ever been born in Washington D.C., although former Vice President and Democratic nominee in the 2000 election, Al Gore, is the only major party candidate to have been born there, during his father's term in the House of Representatives. Always Democratic The District of Columbia has voted for the Democratic Party's nominee in every presidential election that has been contested in the capital. Not only do Democratic nominees perform well in D.C., they win these electoral votes by significant margins; Democrats have won over ninety percent of D.C.'s popular vote in the past four elections, and the worst performance ever by a Democrat was in 1980, where Jimmy Carter only won 75 percent of the popular vote. Factors such as heavy urbanization and ethnic diversity are generally cited as the reasons for D.C.'s strong Democrat voter base. Fifty-first state? The only time when a Democratic nominee did not receive all three electoral votes was in 2000, when one elector abstained from casting her ballot, as a protest of D.C.'s lack of voting representation in Congress. While the District of Columbia can take part in presidential elections, it is a federal district under Congress' jurisdiction, and does not have voting representation in either chamber of Congress. The statehood movement aims to make Washington D.C. the newest state to join the union, possibly under the name "New Columbia" or "Washington, Douglass Commonwealth" (named after the abolitionist, Frederick Douglass), and bring an end to what it sees as "taxation without representation". Generally speaking, lawmakers are split along party lines on whether D.C. should receive statehood or not; with Democrats in favor of the proposition, while Republicans are opposed to the idea (as it would likely bolster the Democrat's numbers in Congress). A survey conducted in June 2020, showed that roughly 40 percent of registered voters support the idea of D.C. statehood, while 41 percent oppose the idea, and the remainder are undecided; the topic gained renewed attention in 2020 when President Trump used the capital's National Guard to disperse peaceful protesters from near the White House during the George Floyd protests.

This dataset tracks annual diversity score from 2006 to 2023 for KIPP DC PCS School District vs. District of Columbia

Scaled diversity values for both DC and DR coding, and for both Antechinus stuartii and A. agilis: study total (γ∼), among-species , within-species , among-populations , and within-populations , with Bartlett’s homogeneity tests of the within stratum components.