Provides transit agency-wide totals for service data for applicable agencies reporting to the National Transit Database in the 2022 and 2023 report years. This view is based off of the "2022 - 2023 NTD Annual Data - Service (by Mode and Time Period)" dataset, which displays the same data at a lower level of aggregation. This view displays the data at a higher level (by agency).

NTD Data Tables organize and summarize data from the 2022 and 2023 National Transit Database in a manner that is more useful for quick reference and summary analysis. The parent dataset is based on the 2022 and 2023 Service database files.

In years 2015-2021, you can find this data in the "Service" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data.

In versions of the data tables from before 2014, you can find data on service in the file called "Transit Operating Statistics: Service Supplied and Consumed."

If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.

This database was designed in response to the Director Memorandum - "Effective January 1, 2019 all structure greater than 120 square feet in the State Responsibility Area (SRA) damaged by wildfire will be inspected and documented in the DINS Collector App."

About this dataset

Context

The dataset tabulates the Ocean View population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Ocean View. The dataset can be utilized to understand the population distribution of Ocean View by age. For example, using this dataset, we can identify the largest age group in Ocean View.

Key observations

The largest age group in Ocean View, DE was for the group of age 75 to 79 years years with a population of 521 (18.88%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Ocean View, DE was the Under 5 years years with a population of 29 (1.05%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Ocean View is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Ocean View total 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 Ocean View Population by Age. You can refer the same here

This dataset details operating expenses for each applicable agency reporting to the National Transit Database in the 2022 and 2023 report years. Expense types include Vehicle Operations, General Administration, and more. This view is based off of the "2022 - 2023 NTD Annual Data - Operating Expenses (by Function)" dataset, which displays the same data at a lower level of aggregation (by mode). This view displays the data at a higher level (by agency).

Only Full Reporters report expenses by function and type. Expenses from other reporter types are included under Reduced Reporter Expenses.

NTD Data Tables organize and summarize data from the 2022 and 2023 National Transit Database in a manner that is more useful for quick reference and summary analysis. The parent dataset is based on the 2022 and 2023 Operating Expenses database files.

In years 2015-2021, you can find this data in the "Operating Expenses" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data.

If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.

3<p_{\text{T}}^{(t)}<4 GeV/c, 45^{o}<phi_{s}<90^{o}, pi region ridge

This dataset provides information about the number of properties, residents, and average property values for Lake View Road cross streets in Bethany, MO.

These data sets were originally created for the following publications:

M. E. Houle, H.-P. Kriegel, P. Kröger, E. Schubert, A. Zimek Can Shared-Neighbor Distances Defeat the Curse of Dimensionality? In Proceedings of the 22nd International Conference on Scientific and Statistical Database Management (SSDBM), Heidelberg, Germany, 2010.

H.-P. Kriegel, E. Schubert, A. Zimek Evaluation of Multiple Clustering Solutions In 2nd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings Held in Conjunction with ECML PKDD 2011, Athens, Greece, 2011.

The outlier data set versions were introduced in:

E. Schubert, R. Wojdanowski, A. Zimek, H.-P. Kriegel On Evaluation of Outlier Rankings and Outlier Scores In Proceedings of the 12th SIAM International Conference on Data Mining (SDM), Anaheim, CA, 2012.

They are derived from the original image data available at https://aloi.science.uva.nl/

The image acquisition process is documented in the original ALOI work: J. M. Geusebroek, G. J. Burghouts, and A. W. M. Smeulders, The Amsterdam library of object images, Int. J. Comput. Vision, 61(1), 103-112, January, 2005

Additional information is available at: https://elki-project.github.io/datasets/multi_view

The following views are currently available:

    Feature type
    Description
    Files


    Object number
    Sparse 1000 dimensional vectors that give the true object assignment
    objs.arff.gz


    RGB color histograms
    Standard RGB color histograms (uniform binning)
    aloi-8d.csv.gz aloi-27d.csv.gz aloi-64d.csv.gz aloi-125d.csv.gz aloi-216d.csv.gz aloi-343d.csv.gz aloi-512d.csv.gz aloi-729d.csv.gz aloi-1000d.csv.gz


    HSV color histograms
    Standard HSV/HSB color histograms in various binnings
    aloi-hsb-2x2x2.csv.gz aloi-hsb-3x3x3.csv.gz aloi-hsb-4x4x4.csv.gz aloi-hsb-5x5x5.csv.gz aloi-hsb-6x6x6.csv.gz aloi-hsb-7x7x7.csv.gz aloi-hsb-7x2x2.csv.gz aloi-hsb-7x3x3.csv.gz aloi-hsb-14x3x3.csv.gz aloi-hsb-8x4x4.csv.gz aloi-hsb-9x5x5.csv.gz aloi-hsb-13x4x4.csv.gz aloi-hsb-14x5x5.csv.gz aloi-hsb-10x6x6.csv.gz aloi-hsb-14x6x6.csv.gz


    Color similiarity
    Average similarity to 77 reference colors (not histograms) 18 colors x 2 sat x 2 bri + 5 grey values (incl. white, black)
    aloi-colorsim77.arff.gz (feature subsets are meaningful here, as these features are computed independently of each other)


    Haralick features
    First 13 Haralick features (radius 1 pixel)
    aloi-haralick-1.csv.gz


    Front to back
    Vectors representing front face vs. back faces of individual objects
    front.arff.gz


    Basic light
    Vectors indicating basic light situations
    light.arff.gz


    Manual annotations
    Manually annotated object groups of semantically related objects such as cups
    manual1.arff.gz

Outlier Detection Versions

Additionally, we generated a number of subsets for outlier detection:

    Feature type
    Description
    Files


    RGB Histograms
    Downsampled to 100000 objects (553 outliers)
    aloi-27d-100000-max10-tot553.csv.gz aloi-64d-100000-max10-tot553.csv.gz



    Downsampled to 75000 objects (717 outliers)
    aloi-27d-75000-max4-tot717.csv.gz aloi-64d-75000-max4-tot717.csv.gz



    Downsampled to 50000 objects (1508 outliers)
    aloi-27d-50000-max5-tot1508.csv.gz aloi-64d-50000-max5-tot1508.csv.gz

20-60% Au+Au, 3<p_{T}^{(t)}<4 GeV/c, 1<p_{T}^{(a)}<2 GeV/c, slice 5, ridge

background subtracted correlation with upper flow systematic uncertainty Au+Au 20-60%, 4<p_{\text{T}}^{(t)}<6 GeV/c, slice 0

sigma vs phis pt=0.51 GeV/c

About this dataset

Context

The dataset tabulates the Lake View population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Lake View. The dataset can be utilized to understand the population distribution of Lake View by age. For example, using this dataset, we can identify the largest age group in Lake View.

Key observations

The largest age group in Lake View, IA was for the group of age 65-69 years with a population of 108 (11.45%), according to the 2021 American Community Survey. At the same time, the smallest age group in Lake View, IA was the 0-4 years with a population of 12 (1.27%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Lake View is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Lake View total 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 Lake View Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Southern View population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Southern View. The dataset can be utilized to understand the population distribution of Southern View by age. For example, using this dataset, we can identify the largest age group in Southern View.

Key observations

The largest age group in Southern View, IL was for the group of age 55 to 59 years years with a population of 187 (10.17%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Southern View, IL was the Under 5 years years with a population of 26 (1.41%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Southern View is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Southern View total 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 Southern View Population by Age. You can refer the same here

OC Waze Partner Hub GeoRSS Cumulative Alert Data from Velocity feed analytics. The data are updated in regular (5-minute) intervals. OC Waze Partner Hub data provide information about traffic jams and events that affect road conditions, either from drivers using Waze, a.k.a. Wazers, or from external sources. Wazers may issue reports from the location at which they are currently located or, if no longer at the location, within 30 minutes after the event occurred. We are also able to provide automatic alerts for what we call Unusual Traffic (or Irregularities) - incidents that affect a large number of users and fall outside the normal traffic patterns for a given day and time.Waze generates traffic jam information by processing the following data sources:Data: includes all traffic data reported by Waze users through the Waze mobile application. Reliability: Each alert gets a reliability score based on other user reactions (‘Thumbs up’, ‘Not there’ etc.) and the level of the reporter (Wazers gain levels by contributing to the map, starting at level 1 and reaching up to level 6. The higher the level, the more experienced and trustworthy the Wazer.) The score (0-10) indicates how reliable the report is. Confidence: Each alert gets a confidence score based on other user reactions (‘Thumbs up’, ‘Not there’). The score ranges between 0 and 10. A higher score indicates more positive feedback from Waze users.Original data provided by Waze App. Learn more at Waze.com.

About this dataset

Context

The dataset tabulates the data for the Bay View, OH population pyramid, which represents the Bay View 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

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Bay View, OH, is 11.8.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Bay View, OH, is 38.5.
• Total dependency ratio for Bay View, OH is 50.2.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Bay View, OH is 2.6.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Bay View population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Bay View for the selected age group is shown in the following column.
• Population (Female): The female population in the Bay View for the selected age group is shown in the following column.
• Total Population: The total population of the Bay View for the selected age group is shown in the following column.

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 Bay View Population by Age. You can refer the same here

flow background with lower flow systematic uncertainty Au+Au 20-60%, 4

This dataset provides information about the number of properties, residents, and average property values for Arbor View Drive cross streets in Athens, GA.

U.S. Chronic Disease Indicators (CDI) CDC's Division of Population Health provides cross-cutting set of 124 indicators that were developed by consensus and that allows states and territories and large metropolitan areas to uniformly define, collect, and report chronic disease data that are important to public health practice and available for states, territories and large metropolitan areas. In addition to providing access to state-specific indicator data, the CDI web site serves as a gateway to additional information and data resources.

Data View Service provided by Ipswich Borough Council to publish data sets under the EU INSPIRE Initiative

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

The California Water Quality Status Report is an annual data-driven snapshot of the Water Board’s water quality and ecosystem data. This third edition of the report is organized around the watershed from land to sea. Each theme-specific story includes a brief background, a data analysis summary, an overview of management actions, and access to the raw data. View the 2019 California Water Quality Status Report. Data for Fig. 2 1,2,3,-Trichloropropane is provided as a download below. The data can also be downloaded from the State Water Resources Control Board (SWRCB) website. Data for Fig. 6 Statewide Water Bodies Toxicity can be downloaded from the California Open Data Portal.