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 New Philadelphia. 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 2013 and 2023, 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 New Philadelphia, the median household income for the households where the householder is White decreased by $6,439(12.25%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $52,550 in 2013 and $46,111 in 2023.
• Black or African American: As per the U.S. Census Bureau population data, in New Philadelphia, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• 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

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 New Philadelphia.
• 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
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are 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 New Philadelphia median household income by race. You can refer the same here

About this dataset

Context

This list ranks the 1 cities in the Philadelphia County, PA by Non-Hispanic White population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Non-Hispanic White Population: This column displays the rank of cities in the Philadelphia County, PA by their Non-Hispanic White population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Non-Hispanic White Population: The Non-Hispanic White population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Non-Hispanic White. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Philadelphia County Non-Hispanic White Population: This tells us how much of the entire Philadelphia County, PA Non-Hispanic White population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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/.

This dataset tracks annual reduced-price lunch eligibility from 2001 to 2015 for Girls High School vs. Pennsylvania and Philadelphia City School District

About this dataset

Context

This list ranks the 1 cities in the Philadelphia County, PA by Non-Hispanic Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Non-Hispanic Other Race Population: This column displays the rank of cities in the Philadelphia County, PA by their Non-Hispanic Some Other Race (SOR) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Non-Hispanic Other Race Population: The Non-Hispanic Other Race population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Non-Hispanic Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Philadelphia County Non-Hispanic Other Race Population: This tells us how much of the entire Philadelphia County, PA Non-Hispanic Other Race population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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/.

Municipal Population and Employment Forecasts for the DVRPC region, 2015 - 2050. To be used for planning purposes.

As a part of DVRPC’s long-range planning activities, the Commission is required to maintain forecasts with at least a 20-year horizon, or to the horizon year of the long-range plan. Allocation of growth is forecasted using a land use model, UrbanSim, and working closely with member county planning staffs. DVRPC has prepared regional, county, and municipal-level population and employment forecasts in five-year increments through 2050, using 2015 Census population estimates and 2015 National Establishments Time Series (NETS) employment data as the base. A forthcoming Analytical Data Report will document the forecasting process and methodologies.

This data provides the municipal level forecast for our 8 counties outside of Philadelphia, and Planning District-level forecast within Philadelphia. Note: while 2019 land use model results are provided, the forecast was only adopted for 2015, 2020, 2025, 2030, 2035, 2040, 2045, and 2050.

Philadelphia Council District Health Dashboard - Dataset and Codebook

Description

This dataset supports the Philadelphia Council District Health Dashboard, an interactive web application that visualizes health disparities and social determinants of health across Philadelphia's 10 City Council Districts. The dashboard provides district-level insights to guide equitable policy and investment decisions by City Council members and the public.

Background

Philadelphia residents experience drastically different health outcomes across the city – differences shaped by federal, state, and local policies rather than individual choices alone. This project maps key health indicators across all 10 Philadelphia City Council Districts to show how politics and geography intersect to shape Philadelphian health.

Data Sources

• US Census Bureau American Community Survey (ACS) 5-year estimates (2018-2022)
• Open Data Philly (2015-2024)

Data aggregated from original geographic units to City Council District boundaries using population-weighted methods.

Dataset Contents

Files:

• data_v1_1.csv - Main dataset containing health indicators by Philadelphia City Council District
• codebook_v1_1.csv - Complete metadata and variable documentation

Methodology

• Population-weighted aggregation for demographic/socioeconomic variables
• Area-weighted aggregation for environmental variables
• Count aggregation for incident data
• City averages calculated as population-weighted across districts

Geographic Coverage

• Unit: Philadelphia City Council Districts (n=10)
• Period: 2018-2022 (ACS), 2015-2024 (Open Data Philly)

Applications

Supports policy analysis, community advocacy, academic research, and public health planning at the district level.

Contact

Authors

Amber Bolli, Tamara Rushovich, Ran Li, Stephanie Hernandez, Alina Schnake-Mahl

Funding

Transform Academia for Equity grant from Robert Wood Johnson Foundation

Keywords

Philadelphia, City Council, Health Disparities, Social Determinants, Urban Health, Public Policy, Geospatial Analysis

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. The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

This dataset tracks annual reduced-price lunch eligibility from 2000 to 2015 for Central High School vs. Pennsylvania and Philadelphia City School District

This dataset tracks annual reduced-price lunch eligibility from 2010 to 2015 for Academy At Palumbo vs. Pennsylvania and Philadelphia City School District

This dataset tracks annual reduced-price lunch eligibility from 2000 to 2015 for Franklin S Edmonds School vs. Pennsylvania and Philadelphia City School District

This dataset includes the number of newly identified (incident) children with blood lead levels (BLL) ≥5 µg/dL, the number of children screened, and the percent of children screened with BLLs ≥5 µg/dL. The ZIP code data is for 2015 and the census tract data is for 2013-2015.

Cell counts with missing values are those with less than six observations, which was truncated to ensure confidentiality. Cells with values of zero were included.

Trouble downloading or have questions about this City dataset? Visit the OpenDataPhilly Discussion Group

This EnviroAtlas dataset describes the block group population and the percentage of the block group population that has potential views of water bodies. A potential view of water is defined as having a body of water that is greater than 300m2 within 50m of a residential location. The window views are considered "potential" because the procedure does not account for presence or directionality of windows in one's home. The residential locations are defined using the EnviroAtlas Dasymetric (2011/October 2015) map. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Historical Dataset of Philadelphia Elementary School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2023),Total Classroom Teachers Trends Over Years (1988-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1988-2023),Asian Student Percentage Comparison Over Years (2012-2021),Hispanic Student Percentage Comparison Over Years (2007-2023),Black Student Percentage Comparison Over Years (1989-2022),White Student Percentage Comparison Over Years (1990-2023),Two or More Races Student Percentage Comparison Over Years (2015-2023),Diversity Score Comparison Over Years (1990-2023),Free Lunch Eligibility Comparison Over Years (2009-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2009-2023),Reading and Language Arts Proficiency Comparison Over Years (2010-2022),Math Proficiency Comparison Over Years (2010-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2010-2022)

Graph and download economic data for Civilian Labor Force in FRB-Philadelphia District (DISCONTINUED) (D3LFN) from Jan 1990 to Nov 2015 about FRB PHI District, civilian, labor force, labor, and USA.

Energy Use and Greenhouse Gas Emissions Inventory for Greater Philadelphia https://www.dvrpc.org/Products/18018 Energy Use is defined as the BBTU (Billion British Thermal Units) equivalent of energy consumed by end point users. For electricity this is the BBTU equivalent of the electricity at point of consumption, not the heat content of the fuels used for electricity generation. Emissions (MTCO2E - Metric tons of carbon dioxide equivalent) from the following sectors and fuel sources are not included in this allocation: enteric fermentation and manure management; commerical and general aviation; marine and port-related activity; off-road vehicles and equipment; freight and intercity passenger rail; coal; fuels used predominently in the industrial sector (e.g., petroleum coke); and land use, land use change, and forestry.

Population and Employment data used in this analysis came from DVRPC's Municipal-level Poulation and Employment Forecasts.

GEOID_10 - Unique GIS ID for Municipality.

ACRES - Total Municipal Acres.

USEACRES - Energy Use per Acres (BBTUs).

EUPOPEM - Energy Use per Person/Job (BBTUs).

EMIACRE - GHG Emissions per Acre (MTCO2E).

EMPOPE - GHG Emissions per Person/Job (MTCO2E).

EMSQACRE - GHG Emissions/Sequestration including Land Use, Land Use Change, and Foresty per Acres (MTCO2E).

EMSQPOPE - GHG Emissions/Sequestration including Land Use, Land Use Change, and Foresty per Person/Job (MTCO2E). DVRPC estimates that net GHG emissions decreased 10 percent from 2010 to 2015, from emissions equivalent to the release of 82 million metric tons of carbon dioxide (MMTCO2e) to about 74 MMTCO2e. GHG emissions were 21 percent lower in 2015 than in 2005. The top three drivers of reductions between 2010 and 2015 were, in decreasing levels of significance, change in electricity generation mix (a cleaner electricity grid due to the continued switch from coal to natural gas), decreased on-road emissions per mile traveled, and decreased electricity consumption per household. Continued reductions will require sustained, concerted and aggressive action at the household, firm, community, regional, state, national, and global level, as well as continued technical advancement. More information can be found at www.dvrpc.org/EnergyClimate/Inventory.htm. Please refer to DVRPC's Energy Use and Greenhouse Gas Emissions Inventory for Greater Philadelphia: Methods and Sources for further details on analysis methods and data sources. https://www.dvrpc.org/Products/TM18023

This dataset tracks annual reduced-price lunch eligibility from 2002 to 2015 for Bridesburg School vs. Pennsylvania and Philadelphia City School District

This dataset tracks annual reduced-price lunch eligibility from 2014 to 2015 for Parkway West vs. Pennsylvania and Philadelphia City School District

This dataset tracks annual reduced-price lunch eligibility from 2003 to 2015 for Penn Alexander School vs. Pennsylvania and Philadelphia City School District

The revenue of the Philadelphia 76ers franchise reached 396 million U.S. dollars in the 2023/24 season. This denoted an increase of around seven percent from the previous season, when the estimated revenue of the National Basketball Association franchise amounted to 371 million U.S. dollars.