Summary Test

Abstract

Census Data for Demo This dataset was created on 2021-06-15.

Additional Information

Extraction was done by Barry Becker from the 1994 Census database. A set of reasonably clean records was extracted using the following conditions: ((AAGE>16) && (AGI>100) && (AFNLWGT>1)&& (HRSWK>0))

This data was extracted from the census bureau database found at http://www.census.gov/ftp/pub/DES/www/welcome.html Donor: Ronny Kohavi and Barry Becker, Data Mining and Visualization Silicon Graphics. e-mail: ronnyk@sgi.com for questions. Split into train-test using MLC++ GenCVFiles (2/3, 1/3 random). 48842 instances, mix of continuous and discrete (train=32561, test=16281) 45222 if instances with unknown values are removed (train=30162, test=15060) Duplicate or conflicting instances : 6 Class probabilities for adult.all file Probability for the label '>50K' : 23.93% / 24.78% (without unknowns) Probability for the label '<=50K' : 76.07% / 75.22% (without unknowns)

Extraction was done by Barry Becker from the 1994 Census database. A set of reasonably clean records was extracted using the following conditions: ((AAGE>16) && (AGI>100) && (AFNLWGT>1)&& (HRSWK>0))

Dataset

This dataset was created by Mohammad Sadat Hossain

Released under CC0: Public Domain

Contents

In March 2001, the New Jersey Private Well Testing Act (PWTA) was signed into law, and its regulations became effective in September 2002. The PWTA is a consumer information law that requires sellers or buyers of property with wells in NJ to test the untreated ground water for a variety of water quality parameters. The test data is submitted electronically by the test laboratories to the NJ Department of Environmental Protection for statewide analysis of ground water quality. These data presented here provide a summary of the percentage of wells that exceeded a maximum contaminant level (MCL) by census block group for the period September 2002 to December 2024.

Imports - Laboratory, Testing & Control Instrument (Census) in the United States increased to 728.97 USD Million in February from 667.43 USD Million in January of 2024. This dataset includes a chart with historical data for the United States Imports of Laboratory, Testing & Control Instrume.

Assumptions: Costs were obtained in US Dollars (USD), British Pounds (GBP), and Gambian Dalasi (GMD). GMD and GBP costs were converted to USD using a historic currency conversion of an average of 366 days from the 01st January 2009 to the 1st of January 2010 (http://www.oanda.com/currency/historical-rates/). For this time period, 1GMD = 0.0377 USD, and 1GBP = 1.5665 USD.For training, the following assumptions were made: Two days’ training.Training was done at the Regional Eye Care Centre, so there are no facility costs.Training was done by the manager of the NECP, who has no per diem.For census taking, the following assumptions were made: One NECP census takers on a motorcycle per EAOne census taker can census 1 EA/day (based on PRET)The census taker would not do a first separate trip to make a household head listCosts were obtained in US Dollars (USD), British Pounds (GBP), and Gambian Dalasi (GMD). GMD and GBP costs were converted to USD using a historic currency conversion of an average of 366 days from the 01st January 2009 to the 1st of January 2010 (http://www.oanda.com/currency/historical-rates/). For this time period, 1GMD = 0.0377 USD, and 1GBP = 1.5665 USD.For training, the following assumptions were made: Two days’ training.Training was done at the Regional Eye Care Centre, so there are no facility costs.Training was done by the manager of the NECP, who has no per diem.Two days’ training.Training was done at the Regional Eye Care Centre, so there are no facility costs.Training was done by the manager of the NECP, who has no per diem.For census taking, the following assumptions were made: One NECP census takers on a motorcycle per EAOne census taker can census 1 EA/day (based on PRET)The census taker would not do a first separate trip to make a household head listOne NECP census takers on a motorcycle per EAOne census taker can census 1 EA/day (based on PRET)The census taker would not do a first separate trip to make a household head listCensus costs by item.

Images of completed 2007 questionnaires

Images of completed 2007 questionnaires

Analysis and Extracts

Key Table Information.Table Title.Age and Sex.Table ID.ACSST1Y2024.S0101.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Subject Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and t...

Exports - Measuring, Testing & Control Instruments (Census) in the United States increased to 2533.97 USD Million in February from 2456.93 USD Million in January of 2024. This dataset includes a chart with historical data for the United States Exports of Measuring, Testing & Control Instrumen.

This is a MD iMAP hosted service layer. Find more information at http://imap.maryland.gov. This layer contains the average upload speed (mbps) per census block. Last Updated: Feature Service Layer Link: https://mdgeodata.md.gov/imap/rest/services/UtilityTelecom/MD_BroadbandSpeedTest/MapServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

The table Test is part of the dataset Census Test, available at https://columbia.redivis.com/datasets/me29-2g7vagrw4. It contains 3125 rows across 90 variables.

AZ 2020 Census Tracts, RUCA codes and categories, and selected ACS 2020 5 yr estimate data used with DES Services map. US Census data fields include population and households, race/ethnicity, FPL, Medicaid means tested under 65, Spanish speaking households, no vehicle, 1 vehicle, no Internet, no computer

*** The County of Santa Clara Public Health Department discontinued updates to the COVID-19 data tables effective June 30, 2025. The COVID-19 data tables will be removed from the Open Data Portal on December 30, 2025. For current information on COVID-19 in Santa Clara County, please visit the Respiratory Virus Dashboard [sccphd.org/respiratoryvirusdata]. For any questions, please contact phinternet@phd.sccgov.org ***

Cumulative COVID-19 tests performed among county residents per 100,000 people residing in the census tract. Source: California Department of Public Health, California Reportable Disease Information Exchange (CalREDIE). Note: Data are not presented if the test count is between 1 to 10 and/or population size is less than 1000 in a census tract.

COVID-19 cumulative test rate by census tract is updated the first Tuesday of each month. This table was updated for the last time on January 24, 2023.

This intermediate level data set was extracted from the census bureau database. There are 48842 instances of data set, mix of continuous and discrete (train=32561, test=16281).

The data set has 15 attribute which include age, sex, education level and other relevant details of a person. The data set will help to improve your skills in Exploratory Data Analysis, Data Wrangling, Data Visualization and Classification Models.

Feel free to explore the data set with multiple supervised and unsupervised learning techniques. The Following description gives more details on this data set:

• age: the age of an individual.
• workclass: The type of work or employment of an individual. It can have the following categories:
  • Private: Working in the private sector.
  • Self-emp-not-inc: Self-employed individuals who are not incorporated.
  • Self-emp-inc: Self-employed individuals who are incorporated.
  • Federal-gov: Working for the federal government.
  • Local-gov: Working for the local government.
  • State-gov: Working for the state government.
  • Without-pay: Not working and without pay.
  • Never-worked: Never worked before.
• Final Weight: The weights on the CPS files are controlled to independent estimates of the civilian noninstitutional population of the US. These are prepared monthly for us by Population Division here at the Census Bureau. We use 3 sets of controls.

These are: 1. A single cell estimate of the population 16+ for each state. 2. Controls for Hispanic Origin by age and sex. 3. Controls by Race, age and sex.

We use all three sets of controls in our weighting program and "rake" through them 6 times so that by the end we come back to all the controls we used.

People with similar demographic characteristics should have similar weights. There is one important caveat to remember about this statement. That is that since the CPS sample is actually a collection of 51 state samples, each with its own probability of selection, the statement only applies within state.

• education: The highest level of education completed.
• education-num: The number of years of education completed.
• marital-status: The marital status.
• occupation: Type of work performed by an individual.
• relationship: The relationship status.
• race: The race of an individual.
• sex: The gender of an individual.
• capital-gain: The amount of capital gain (financial profit).
• capital-loss: The amount of capital loss an individual has incurred.
• hours-per-week: The number of hours works per week.
• native-country: The country of origin or the native country.
• income: The income level of an individual and serves as the target variable. It indicates whether the income is greater than $50,000 or less than or equal to $50,000, denoted as (>50K, <=50K).

2010 Census data on poverty and recipients of Supplemental Nutrition Assistance Program benefits based on 2010 Census tract centroids

AZ 2020 Census Tracts and selected ACS 2020 5 yr estimate data used with DES Services map. Fields include population and households, race/ethnicity, FPL, Medicaid means tested under 65, Spanish speaking households, no vehicle, 1 vehicle, no Internet, no computer

For use in social analysis