About this dataset

Context

The dataset tabulates the population of Java by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Java across both sexes and to determine which sex constitutes the majority.

Key observations

There is a considerable majority of female population, with 65.66% of total population being female. 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.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Java is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Java 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 Java Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Java town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Java town. The dataset can be utilized to understand the population distribution of Java town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Java town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Java town.

Key observations

Largest age group (population): Male # 40-44 years (139) | Female # 65-69 years (126). 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Java town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Java town is shown in the following column.
• Population (Female): The female population in the Java town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Java town for each age group.

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 Java town Population by Gender. You can refer the same here

Data for Effects of Spatial Density of Public Places to the Intensity of COVID-19 Positive Cases

About this dataset

Context

The dataset tabulates the population of Java by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Java across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of female population, with 60.54% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Java is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Java 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 Java Population by Race & Ethnicity. You can refer the same here

Statistics of the ORBDA source database content at the dataset and patient levels.

Comprehensive demographic dataset for Java, VA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Comprehensive YouTube channel statistics for Java Brains, featuring 698,000 subscribers and 138,055,007 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Technology category and is based in US. Track 1,866 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Comprehensive YouTube channel statistics for Kim Java, featuring 289,000 subscribers and 75,959,025 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category and is based in US. Track 914 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Comprehensive demographic dataset for North Java, NY, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Dataset and code used to reproduce figures and tables presented in a paper.

This is a dataset about the usage of properties and datatypes in the Web Data Commons RDFa, Microdata, Embedded JSON-LD, and Microformats Data Sets (November 2018) based on the Common Crawl November 2018 archive. The dataset has been produced using the RDF Property and Datatype Usage Scanner v2.1.1, which is based on the Apache Jena framework. Only RDFa and embedded JSON-LD data were considered, as Microdata and Microformats do not incorporate explicit datatypes.

Dataset Properties

• Size: 22.2 MiB compressed, 569.6 MiB uncompressed, 2 608 325 rows plus 1 head line determined using gunzip -c measurements.csv.gz | wc -l
• Parsing Failures: The scanner failed to parse 4 135 842 triples (~0.077 %) of the source dataset (containing 5 367 569 192 triples).
• Content:
  • CATEGORY: The category (html-embedded-jsonld or html-rdfa) of the Web Data Commons file that has been measured.
  • FILE_URL: The URL of the Web Data Commons file that has been measured.
  • MEASUREMENT: The applied measurement with specific conditions, one of:
    • UnpreciseRepresentableInDouble: The number of lexicals that are in the lexical space but not in the value space of xsd:double.
    • UnpreciseRepresentableInFloat: The number of lexicals that are in the lexical space but not in the value space of xsd:float.
    • UsedAsDatatype: The total number of literals with the datatype.
    • UsedAsPropertyRange: The number of statements that specify the datatype as range of the property.
    • ValidDateNotation: The number of lexicals that are in the lexical space of xsd:date.
    • ValidDateTimeNotation: The number of lexicals that are in the lexical space of xsd:dateTime.
    • ValidDecimalNotation: The number of lexicals that represent a number with decimal notation and whose lexical representation is thereby in the lexical space of xsd:decimal, xsd:float, and xsd:double.
    • ValidExponentialNotation: The number of lexicals that represent a number with exponential notation and whose lexical representation is thereby in the lexical space of xsd:float, and xsd:double.
    • ValidInfOrNaNNotation: The number of lexicals that equals either INF, +INF, -INF or NaN and whose lexical representation is thereby in the lexical space of xsd:float, and xsd:double.
    • ValidIntegerNotation: The number of lexicals that represent an integer number and whose lexical representation is thereby in the lexical space of xsd:integer, xsd:decimal, xsd:float, and xsd:double.
    • ValidTimeNotation: The number of lexicals that are in the lexical space of xsd:time.
    • ValidTrueOrFalseNotation: The number of lexicals that equal either true or false and whose lexical representation is thereby in the lexical space of xsd:boolean.
    • ValidZeroOrOneNotation: The number of lexicals that equal either 0 or 1 and whose lexical representation is thereby in the lexical space of xsd:boolean, and xsd:integer, xsd:decimal, xsd:float, and xsd:double.
    Note: Lexical representation of xsd:double values in embedded JSON-LD got normalized to always use exponential notation with up to 16 fractional digits (see related code). Be careful by drawing conclusions from according Valid… and Unprecise… measures.
  • PROPERTY: The property that has been measured.
  • DATATYPE: The datatype that has been measured.
  • QUANTITY: The count of statements that fulfill the condition specified by the measurement per file, property and datatype.

Preview

"CATEGORY","FILE_URL","MEASUREMENT","PROPERTY","DATATYPE","QUANTITY"
"html-rdfa","http://data.dws.informatik.uni-mannheim.de/structureddata/2018-12/quads/dpef.html-rdfa.nq-00000.gz","UnpreciseRepresentableInDouble","https://www.w3.org/2006/vcard/ns#longitude","https://www.w3.org/2001/XMLSchema#float","4"
"html-rdfa","http://data.dws.informatik.uni-mannheim.de/structureddata/2018-12/quads/dpef.html-rdfa.nq-00000.gz","UnpreciseRepresentableInDouble","https://www.w3.org/2006/vcard/ns#latitude","https://www.w3.org/2001/XMLSchema#float","4"
"html-rdfa","http://data.dws.informatik.uni-mannheim.de/structureddata/2018-12/quads/dpef.html-rdfa.nq-00000.gz","UnpreciseRepresentableInDouble","https://purl.org/goodrelations/v1#hasCurrencyValue","https://www.w3.org/2001/XMLSchema#float","6"
"html-rdfa","http://data.dws.informatik.uni-mannheim.de/structureddata/2018-12/quads/dpef.html-rdfa.nq-00000.gz","UnpreciseRepresentableInDouble","http://purl.org/goodrelations/v1#hasCurrencyValue","http://www.w3.org/2001/XMLSchema#floatfloat","8"
"html-rdfa","http://data.dws.informatik.uni-mannheim.de/structureddata/2018-12/quads/dpef.html-rdfa.nq-00000.gz","UnpreciseRepresentableInDouble","https://opengraphprotocol.org/schema/latitude","http://www.w3.org/2001/XMLSchema#string","30"
…
"html-embedded-jsonld","http://data.dws.informatik.uni-mannheim.de/structureddata/2018-12/quads/dpef.html-embedded-jsonld.nq-00734.gz","ValidZeroOrOneNotation","http://schema.org/numberOfItems","http://www.w3.org/2001/XMLSchema#integer","40"
"html-embedded-jsonld","http://data.dws.informatik.uni-mannheim.de/structureddata/2018-12/quads/dpef.html-embedded-jsonld.nq-00734.gz","ValidZeroOrOneNotation","http://schema.org/ratingValue","http://www.w3.org/2001/XMLSchema#integer","431"
"html-embedded-jsonld","http://data.dws.informatik.uni-mannheim.de/structureddata/2018-12/quads/dpef.html-embedded-jsonld.nq-00734.gz","ValidZeroOrOneNotation","http://schema.org/width","http://www.w3.org/2001/XMLSchema#integer","122"
"html-embedded-jsonld","http://data.dws.informatik.uni-mannheim.de/structureddata/2018-12/quads/dpef.html-embedded-jsonld.nq-00734.gz","ValidZeroOrOneNotation","http://schema.org/minValue","http://www.w3.org/2001/XMLSchema#integer","63"
"html-embedded-jsonld","http://data.dws.informatik.uni-mannheim.de/structureddata/2018-12/quads/dpef.html-embedded-jsonld.nq-00734.gz","ValidZeroOrOneNotation","http://schema.org/pageEnd","http://www.w3.org/2001/XMLSchema#integer","139"

Note: The data contain malformed IRIs, like "xsd:dateTime" (instead of probably "http://www.w3.org/2001/XMLSchema#dateTime"), which are caused by missing namespace definitions in the original source website.

Reproduce

To reproduce this dataset checkout the RDF Property and Datatype Usage Scanner v2.1.1 and execute:

mvn clean package
java -jar target/Scanner.jar --category html-rdfa --list http://webdatacommons.org/structureddata/2018-12/files/html-rdfa.list November2018
java -jar target/Scanner.jar --category html-embedded-jsonld --list http://webdatacommons.org/structureddata/2018-12/files/html-embedded-jsonld.list November2018
./measure.sh November2018
# Wait until the scan has completed. This will take a few days
java -jar target/Scanner.jar --results ./November2018/measurements.csv.gz November2018

Comprehensive YouTube channel statistics for Joshua Java, featuring 2,970,000 subscribers and 1,370,123,440 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category. Track 171 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

About this dataset

Context

The dataset tabulates the population of Java by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Java. The dataset can be utilized to understand the population distribution of Java by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Java. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Java.

Key observations

Largest age group (population): Male # 35-39 years (7) | Female # 20-24 years (28). 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Java population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Java is shown in the following column.
• Population (Female): The female population in the Java is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Java for each age group.

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 Java Population by Gender. You can refer the same here

Context

Dataset is based on box score and standing statistics from the NBA.

Calculations such as number of possessions, floor impact counter, strength of schedule, and simple rating system are performed.

Finally, extracts are created based on a perspective:

• teamBoxScore.csv communicates game data from each teams perspective

• officialBoxScore.csv communicates game data from each officials perspective

• playerBoxScore.csv communicates game data from each players perspective

• standing.csv communicates standings data for each team every day during the season

Content

Data Sources

Box score and standing statistics were obtained by a Java application using RESTful APIs provided by xmlstats.

Calculation Sources

Another Java application performs advanced calculations on the box score and standing data.
Formulas for these calculations were primarily obtained from these sources:

• https://basketball.realgm.com/info/glossary
• https://www.nbastuffer.com/team-evaluation-metrics/
• https://www.basketball-reference.com/about/glossary.html

Inspiration

Favoritism

Does a referee impact the number of fouls made against a player or the pace of a game?

Forcasting

Can the aggregated points scored by and against a team along with their strength of schedule be used to determine their projected winning percentage for the season?

Predicting the Past

For a given game, can games played earlier in the season help determine how a team will perform?

Lots of data elements and possibilities. Let your imagination roam!

Method-level statistics of the preprocessed ELFF datasets.

This dataset contains data on shipping and trade in the Java Sea in the period from 1870 until 1940. The dataset forms the basis of a source publication. The collection of statistics is published as part of the project "The Java Sea Region in an Age of Transition, ca. 1870-1970". In this co-operative project, which started in 1997, researchers from Diponegoro University in Semerang, the Free University of Amsterdam and Leiden University particpate. It attempts to analyse the infrastructural, technological and economic development of the Java Sea Region, the central maritime zone of Indonesia, during the period 1870-1970. The tables present statistics on the twelve major ports around the Java Sea, six located on the Northern Coast of Java, six located in the Outer Islands. Within the network of domestic and international trade they display a wide range of characteristics, typical of the diversity of the Indonesian Archipelago.

East Java Descriptive Statistics.

Indonesia Employment: Java: DKI Jakarta data was reported at 4,726.779 Person th in 2018. This records an increase from the previous number of 4,509.171 Person th for 2017. Indonesia Employment: Java: DKI Jakarta data is updated yearly, averaging 3,497.359 Person th from Aug 1984 (Median) to 2018, with 33 observations. The data reached an all-time high of 4,861.832 Person th in 2016 and a record low of 2,024.243 Person th in 1984. Indonesia Employment: Java: DKI Jakarta data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.GBA019: Employment: by Province.

Statistics for the all and 10k datasets created using the SUS-openEHR-Builder.

About this dataset

Context

The dataset tabulates the Java town household income by age. The dataset can be utilized to understand the age-based income distribution of Java town income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Java, New York annual median income by age groups dataset (in 2022 inflation-adjusted dollars)
• Age-wise distribution of Java, New York household incomes: Comparative analysis across 16 income brackets

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Java town income distribution by age. You can refer the same here