This data is comprised of U.S. Census tracts for the year 2019 with data from the American Community Survey, CDC social vulnerability index, CDC Places EPA toxic release inventory sites, PM2.5 annual average from the Atmospheric Composition Analysis Group (https://sites.wustl.edu/acag/). This dataset was created as part of the CAFE Introduction to QGIS 101!!! Session on 6/27/2024 and is for training purposes only.

The US Census Bureau provides a large collection of data files, some of which are encoded separately or do not have an obvious means to integrate. Suppose that the files are located and need to be integrated to make some data-driven decisions using Census population estimates. The resultant files may be very useful to explore, but the user wants to get into visual representation and start considering things spatially and temporally. In this resource, the Jupyter notebook walks through a set of operations created to integrate Census population estimates with the known ESRI shapefile for the equivalent county-scales.

This dataset contains measures of the number and per capita density of education and training services per United States census tract from 2003 through 2017. This includes traditional education establishments such as elementary schools, secondary schools, and colleges, as well as businesses offering specialized training such as art classes, driving instruction, computer training, and standardized test preparation.

The 2002 Census of Law Enforcement Training Academies (CLETA02) was the first effort by the Bureau of Justice Statistics (BJS) to collect information from law enforcement training academies across the United States. The CLETA02 included all currently operating academies that provided basic law enforcement training. Academies that provided only in-service training, corrections/detention training, or other special types of training were excluded. Data were collected on personnel, expenditures, facilities, equipment, trainees, training curricula, and a variety of special topic areas. As of year-end 2002, a total of 626 law enforcement academies operating in the United States offered basic law enforcement training to individuals recruited or seeking to become law enforcement officers.

Note: For information on data collection, confidentiality protection, nonsampling error, and definitions, see the 2020 Island Areas Censuses Technical Documentation..Due to COVID-19 restrictions impacting data collection for the 2020 Census of American Samoa, data tables reporting social and economic characteristics do not include the group quarters population in the table universe. As a result, impacted 2020 data tables should not be compared to 2010 and other past census data tables reporting the same characteristics. The Census Bureau advises data users to verify table universes are the same before comparing data across census years. For more information about data collection limitations and the impacts on American Samoa's data products, see the 2020 Island Areas Censuses Technical Documentation..Explanation of Symbols: 1.An "-" means the statistic could not be computed because there were an insufficient number of observations. 2. An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.3. An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.4. An "N" means data are not displayed for the selected geographic area due to concerns with statistical reliability or an insufficient number of cases.5. An "(X)" means not applicable..Source: U.S. Census Bureau, 2020 Census, American Samoa.

In 2018, there were 681 state and local law enforcement training academies that provided basic training instruction to 59,511 recruits. As part of the 2018 Census of Law Enforcement Training Academies (CLETA), respondents provided general information about the academies' facilities, resources, programs, and staff. The core curricula subject areas and hours dedicated to each topic, as well as training offered in some special topics, were also included. The collection included information about recruit demographics, completion, and reasons for non-completion of basic training. BJS administered previous versions of the CLETA in 2002, 2006, and 2013.

ASS: Exp: Educational: Buss Schools & Computer & Management Training data was reported at 9.494 USD bn in 2016. This records an increase from the previous number of 9.216 USD bn for 2015. ASS: Exp: Educational: Buss Schools & Computer & Management Training data is updated yearly, averaging 8.281 USD bn from Dec 2009 (Median) to 2016, with 8 observations. The data reached an all-time high of 9.494 USD bn in 2016 and a record low of 7.593 USD bn in 2009. ASS: Exp: Educational: Buss Schools & Computer & Management Training data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H021: Annual Services Survey: Employer Firms Expense.

Note: For information on data collection, confidentiality protection, nonsampling error, and definitions, see the 2020 Island Areas Censuses Technical Documentation..Due to COVID-19 restrictions impacting data collection for the 2020 Census of the U.S. Virgin Islands, data tables reporting social and economic characteristics do not include the group quarters population in the table universe. As a result, impacted 2020 data tables should not be compared to 2010 and other past census data tables reporting the same characteristics. The Census Bureau advises data users to verify table universes are the same before comparing data across census years. For more information about data collection limitations and the impacts on the U.S. Virgin Island's data products, see the 2020 Island Areas Censuses Technical Documentation..Explanation of Symbols: 1.An "-" means the statistic could not be computed because there were an insufficient number of observations. 2. An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.3. An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.4. An "N" means data are not displayed for the selected geographic area due to concerns with statistical reliability or an insufficient number of cases.5. An "(X)" means not applicable..Source: U.S. Census Bureau, 2020 Census, U.S. Virgin Islands.

Note: For information on data collection, confidentiality protection, nonsampling error, and definitions, see the 2020 Island Areas Censuses Technical Documentation..Due to operational changes for military installation enumeration, the 2020 Census of Guam data tables reporting housing, social, and economic characteristics do not include housing units or populations living on Guam's U.S. military installations in the table universe. As a result, impacted 2020 data tables should not be compared to 2010 and other past census data tables reporting the same characteristics. The Census Bureau advises data users to verify table universes are the same before comparing data across census years. For more information about operational changes and the impacts on Guam's data products, see the 2020 Island Areas Censuses Technical Documentation..Due to COVID-19 restrictions impacting data collection for the 2020 Census of Guam, data tables reporting social and economic characteristics do not include the group quarters population in the table universe. As a result, impacted 2020 data tables should not be compared to 2010 and other past census data tables reporting the same characteristics. The Census Bureau advises data users to verify table universes are the same before comparing data across census years. For more information about data collection limitations and the impacts on Guam's data products, see the 2020 Island Areas Censuses Technical Documentation..Explanation of Symbols: 1.An "-" means the statistic could not be computed because there were an insufficient number of observations. 2. An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.3. An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.4. An "N" means data are not displayed for the selected geographic area due to concerns with statistical reliability or an insufficient number of cases.5. An "(X)" means not applicable..Source: U.S. Census Bureau, 2020 Census, Guam.

United States QSS: Revenue: Educational: Business, Computer & Management Training data was reported at 3.133 USD bn in Mar 2018. This records a decrease from the previous number of 3.243 USD bn for Dec 2017. United States QSS: Revenue: Educational: Business, Computer & Management Training data is updated quarterly, averaging 2.667 USD bn from Mar 2010 (Median) to Mar 2018, with 33 observations. The data reached an all-time high of 3.377 USD bn in Sep 2017 and a record low of 2.228 USD bn in Mar 2010. United States QSS: Revenue: Educational: Business, Computer & Management Training data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H019: Quarterly Services Survey.

As of year-end 2006 a total of 648 state and local law enforcement academies were providing basic training to entry-level recruits in the United States. State agencies approved 98 percent of these academies. This data collection describes the academies in terms of their personnel, expenditures, facilities, curricula, and trainees using data from the 2006 Census of State and Local Law Enforcement Training Academies (CLETA) sponsored by the Bureau of Justice Statistics (BJS). The 2006 CLETA, like the initial 2002 study, collected data from all state and local academies that provided basic law enforcement training. Academies that provided only in-service training, corrections and detention training, or other special types of training were excluded. Federal training academies were also excluded.

Analysis of ‘US Adult Income’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/johnolafenwa/us-census-data on 28 January 2022.

--- Dataset description provided by original source is as follows ---

US Adult Census data relating income to social factors such as Age, Education, race etc.

The Us Adult income dataset was extracted by Barry Becker from the 1994 US Census Database. The data set consists of anonymous information such as occupation, age, native country, race, capital gain, capital loss, education, work class and more. Each row is labelled as either having a salary greater than ">50K" or "<=50K".

This Data set is split into two CSV files, named adult-training.txt and adult-test.txt.

The goal here is to train a binary classifier on the training dataset to predict the column income_bracket which has two possible values ">50K" and "<=50K" and evaluate the accuracy of the classifier with the test dataset.

Note that the dataset is made up of categorical and continuous features. It also contains missing values The categorical columns are: workclass, education, marital_status, occupation, relationship, race, gender, native_country

The continuous columns are: age, education_num, capital_gain, capital_loss, hours_per_week

This Dataset was obtained from the UCI repository, it can be found on

https://archive.ics.uci.edu/ml/datasets/census+income, http://mlr.cs.umass.edu/ml/machine-learning-databases/adult/

USAGE This dataset is well suited to developing and testing wide linear classifiers, deep neutral network classifiers and a combination of both. For more info on Combined Deep and Wide Model classifiers, refer to the Research Paper by Google https://arxiv.org/abs/1606.07792

Refer to this kernel for sample usage : https://www.kaggle.com/johnolafenwa/wage-prediction

Complete Tutorial is available from http://johnolafenwa.blogspot.com.ng/2017/07/machine-learning-tutorial-1-wage.html?m=1

--- Original source retains full ownership of the source dataset ---

The United States Virgin Islands Summary File contains data on population and housing subjects compiled from questions on the 2010 United States Virgin Islands Census questionnaire. Population subjects include age, sex, children ever born, citizenship status, foreign-born status, disability status, educational attainment, race, Hispanic or Latino origin, family type, grandparents as caregivers, group quarters population, health insurance coverage status, household type and relationship, employment status, work experience, class of worker, industry, occupation, place of work, journey to work, travel time to work, language spoken at home and ability to speak English, marital status, nativity, year of entry, place of birth, parents' place of birth, earnings, income, poverty status, residence in 2009, school enrollment, vocational training and veteran status. Housing subjects include acreage, agricultural sales, business on property, computer ownership, internet service, kitchen facilities, cooking fuel, mortgage status, number of rooms, number of bedrooms, occupancy status, occupants per room, plumbing facilities, purchase of water from water vendor, gross rent, condominium status and fee, mobile home costs, selected monthly owner costs, sewage disposal, source of water, telephone service available, tenure, units in structure, vacancy status, value of home, vehicles available, year householder moved into unit and year structure built. The data are organized in 548 tables, one variable per table cell, which are presented at up to 21 levels of observation, including the United States Virgin Islands as a whole, islands, census subdistricts, places (census designated places and towns), estates, census tracts, block groups, blocks and 5-digit ZIP Code Tabulation Areas. Altogether, 110 tables are presented at the block level and higher, 288 at the block group level and higher and 150 at the census tract level and higher. Additionally, the tables are iterated for the urban and rural geographic components of islands and 21 geographic components of the United States Virgin Islands as a whole: 15 urban components (total urban, urbanized areas, urban clusters, and urbanized areas and urban clusters of various population sizes) and 6 rural components (total rural, rural areas outside places, rural areas inside places and inside places of various population sizes). Due to problems in the initial version, the Census Bureau ultimately issued the Summary File as two data products. The first or main release comprises 50 data files with all the tables except 11 tables on selected monthly owner costs, the tables HBG66, HBG67, HBG68, HBG69, HBG70, HBG71, HBG72, HBG73, HCT19, HCT20 and HCT21. The second, supplemental release consists of a document file with the 11 tables on selected monthly owner costs. ICPSR provides each product as a separate ZIP archive. The archive with the supplemental release also includes additional technical documentation prepared by the Bureau.

The 2002 Census of Law Enforcement Training Academies (CLETA02) was the first effort by the Bureau of Justice Statistics (BJS) to collect information from law enforcement training academies across the United States. The CLETA02 included all currently oper

From 2011 to 2013, a total of 664 state and local law enforcement academies provided basic training to entry-level officer recruits in the United States. During this period, more than 135,000 recruits (45,000 per year) entered a basic training program, and 86 percent completed the program successfully. This completion rate was the same as was observed for the 57,000 recruits who entered training programs in 2005. This data collection describes basic training programs for new recruits based on their content, instructors, and teaching methods. It also describes the recruits' demographics, completion rates, and reasons for failure. The data describing recruits cover those entering basic training programs from 2011 to 2013. The data describing academies are based on 2013, the latest year referenced in the survey. Like prior BJS studies conducted in 2002 and 2006, the 2013 CLETA collected data from all state and local academies that provided basic law enforcement training. Academies that provided only in-service, corrections and detention, or other specialized training were excluded. Federal training academies were also excluded. Any on-the-job training received by recruits subsequent to their academy training is not covered.

This dataset is used in the demo video of the course Publish Census data onODS Academy, Opendatasoft's training platform.

Graph and download economic data for Total Revenue for Business Schools and Computer and Management Training, All Establishments (REV6114ALLEST144QNSA) from Q1 2010 to Q1 2025 about trains, schools, management, computers, revenue, establishments, business, and USA.

These data are from the 20-, 15-, and 5-percent samples of the 1970 United States Census of Population and Housing, and contain tabulations of population characteristics such as education, occupation, income, citizenship, and vocational training. Twenty selected geographic summary areas -- including states, counties, standard metropolitan statistical areas, urbanized areas, and places -- constitute the units of observation. Separate tallies are shown for whites, Blacks, Hispanic American (referred to as Spanish Americans in the 1970 Census), and the total population.

Occupation describes the kind of work a person does on the job. Occupation data were derived from answers to questions 45 and 46 in the 2015 American Community Survey (ACS). Question 45 asks: “What kind of work was this person doing?” Question 46 asks: “What were this person’s most important activities or duties?”

These questions were asked of all people 15 years old and over who had worked in the past 5 years. For employed people, the data refer to the person’s job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people and people who are not currently employed but report having a job within the last five years, the data refer to their last job.

These questions describe the work activity and occupational experience of the American labor force. Data are used to formulate policy and programs for employment, career development, and training; to provide information on the occupational skills of the labor force in a given area to analyze career trends; and to measure compliance with antidiscrimination policies. Companies use these data to decide where to locate new plants, stores, or offices.

Graph and download economic data for Expenses for Business Schools and Computer and Management Training, All Establishments, Employer Firms (BSACAMTEAEE36114) from 2009 to 2022 about trains, schools, management, computers, employer firms, establishments, expenditures, business, and USA.