Context

While working on the gun violence data set, i wanted to normalize the number of incidents because some states are more populous than others so normalizing the gun incidents per million people gave me a different outlook towards the data. The source of this data is unofficial as the last numbers from US census bureau were available only from 2010. I just wanted to get a quick unofficial source of this data and stumbled upon this site

http://worldpopulationreview.com/states/

Content

Simple two columns - state and population as of 2018

Acknowledgements

http://worldpopulationreview.com/states/

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

Context

This file contains an estimate of the world's population and consumer price index by country.

Content

It only has four columns with the country column representing the name of a specific country, country code identifing a particular country, the population representing the estimated population size of a country as of 2018 September, and the Consumer_price_index representing the estimated consumer price index for every country. Some countries may be missing or may be under a different name.

Acknowledgements

Credit to http://worldpopulationreview.com/countries

https://tradingeconomics.com/country-list/consumer-price-index-cpi

Analysis of ‘COVID-19 State Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/nightranger77/covid19-state-data on 28 January 2022.

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

This dataset is a per-state amalgamation of demographic, public health and other relevant predictors for COVID-19.

Deaths, Infections and Tests by State

The COVID Tracking Project: https://covidtracking.com/data/api

Used positive, death and totalTestResults from the API for, respectively, Infected, Deaths and Tested in this dataset. Please read the documentation of the API for more context on those columns

Predictor Data and Sources

Population (2020)

Density is people per meter squared https://worldpopulationreview.com/states/

ICU Beds and Age 60+

https://khn.org/news/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds/

GDP

https://worldpopulationreview.com/states/gdp-by-state/

Income per capita (2018)

https://worldpopulationreview.com/states/per-capita-income-by-state/

Gini

https://en.wikipedia.org/wiki/List_of_U.S._states_by_Gini_coefficient

Unemployment (2020)

Rates from Feb 2020 and are percentage of labor force
https://www.bls.gov/web/laus/laumstrk.htm

Sex (2017)

Ratio is Male / Female
https://www.kff.org/other/state-indicator/distribution-by-gender/

Smoking Percentage (2020)

https://worldpopulationreview.com/states/smoking-rates-by-state/

Influenza and Pneumonia Death Rate (2018)

Death rate per 100,000 people
https://www.cdc.gov/nchs/pressroom/sosmap/flu_pneumonia_mortality/flu_pneumonia.htm

Chronic Lower Respiratory Disease Death Rate (2018)

Death rate per 100,000 people
https://www.cdc.gov/nchs/pressroom/sosmap/lung_disease_mortality/lung_disease.htm

Active Physicians (2019)

https://www.kff.org/other/state-indicator/total-active-physicians/

Hospitals (2018)

https://www.kff.org/other/state-indicator/total-hospitals

Health spending per capita

Includes spending for all health care services and products by state of residence. Hospital spending is included and reflects the total net revenue. Costs such as insurance, administration, research, and construction expenses are not included.
https://www.kff.org/other/state-indicator/avg-annual-growth-per-capita/

Pollution (2019)

Pollution: Average exposure of the general public to particulate matter of 2.5 microns or less (PM2.5) measured in micrograms per cubic meter (3-year estimate)
https://www.americashealthrankings.org/explore/annual/measure/air/state/ALL

Medium and Large Airports

For each state, number of medium and large airports https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_the_United_States

Temperature (2019)

Note that FL was incorrect in the table, but is corrected in the Hottest States paragraph
https://worldpopulationreview.com/states/average-temperatures-by-state/
District of Columbia temperature computed as the average of Maryland and Virginia

Urbanization (2010)

Urbanization as a percentage of the population https://www.icip.iastate.edu/tables/population/urban-pct-states

Age Groups (2018)

https://www.kff.org/other/state-indicator/distribution-by-age/

School Closure Dates

Schools that haven't closed are marked NaN https://www.edweek.org/ew/section/multimedia/map-coronavirus-and-school-closures.html

Note that some datasets above did not contain data for District of Columbia, this missing data was found via Google searches manually entered.

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

Associated with manuscript titled: Fifty Muslim-majority countries have fewer COVID-19 cases and deaths than the 50 richest non-Muslim countriesThe objective of this research was to determine the difference in the total number of COVID-19 cases and deaths between Muslim-majority and non-Muslim countries, and investigate reasons for the disparities. Methods: The 50 Muslim-majority countries had more than 50.0% Muslims with an average of 87.5%. The non-Muslim country sample consisted of 50 countries with the highest GDP while omitting any Muslim-majority countries listed. The non-Muslim countries’ average percentage of Muslims was 4.7%. Data pulled on September 18, 2020 included the percentage of Muslim population per country by World Population Review15 and GDP per country, population count, and total number of COVID-19 cases and deaths by Worldometers.16 The data set was transferred via an Excel spreadsheet on September 23, 2020 and analyzed. To measure COVID-19’s incidence in the countries, three different Average Treatment Methods (ATE) were used to validate the results. Results published as a preprint at https://doi.org/10.31235/osf.io/84zq5(15) Muslim Majority Countries 2020 [Internet]. Walnut (CA): World Population Review. 2020- [Cited 2020 Sept 28]. Available from: http://worldpopulationreview.com/country-rankings/muslim-majority-countries (16) Worldometers.info. Worldometer. Dover (DE): Worldometer; 2020 [cited 2020 Sept 28]. Available from: http://worldometers.info

List of Army personnel in the world, and the population of the respective country. The data is extracted and scrapped from 1. https://worldpopulationreview.com/country-rankings/military-size-by-country 2. https://en.wikipedia.org/wiki/List_of_countries_by_number_of_military_and_paramilitary_personnel

This dataset is a per-state amalgamation of demographic, public health and other relevant predictors for COVID-19.

Deaths, Infections and Tests by State

The COVID Tracking Project: https://covidtracking.com/data/api

Used positive, death and totalTestResults from the API for, respectively, Infected, Deaths and Tested in this dataset. Please read the documentation of the API for more context on those columns

Predictor Data and Sources

Population (2020)

Density is people per meter squared https://worldpopulationreview.com/states/

ICU Beds and Age 60+

https://khn.org/news/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds/

GDP

https://worldpopulationreview.com/states/gdp-by-state/

Income per capita (2018)

https://worldpopulationreview.com/states/per-capita-income-by-state/

Gini

https://en.wikipedia.org/wiki/List_of_U.S._states_by_Gini_coefficient

Unemployment (2020)

Rates from Feb 2020 and are percentage of labor force
https://www.bls.gov/web/laus/laumstrk.htm

Sex (2017)

Ratio is Male / Female
https://www.kff.org/other/state-indicator/distribution-by-gender/

Smoking Percentage (2020)

https://worldpopulationreview.com/states/smoking-rates-by-state/

Influenza and Pneumonia Death Rate (2018)

Death rate per 100,000 people
https://www.cdc.gov/nchs/pressroom/sosmap/flu_pneumonia_mortality/flu_pneumonia.htm

Chronic Lower Respiratory Disease Death Rate (2018)

Death rate per 100,000 people
https://www.cdc.gov/nchs/pressroom/sosmap/lung_disease_mortality/lung_disease.htm

Active Physicians (2019)

https://www.kff.org/other/state-indicator/total-active-physicians/

Hospitals (2018)

https://www.kff.org/other/state-indicator/total-hospitals

Health spending per capita

Includes spending for all health care services and products by state of residence. Hospital spending is included and reflects the total net revenue. Costs such as insurance, administration, research, and construction expenses are not included.
https://www.kff.org/other/state-indicator/avg-annual-growth-per-capita/

Pollution (2019)

Pollution: Average exposure of the general public to particulate matter of 2.5 microns or less (PM2.5) measured in micrograms per cubic meter (3-year estimate)
https://www.americashealthrankings.org/explore/annual/measure/air/state/ALL

Medium and Large Airports

For each state, number of medium and large airports https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_the_United_States

Temperature (2019)

Note that FL was incorrect in the table, but is corrected in the Hottest States paragraph
https://worldpopulationreview.com/states/average-temperatures-by-state/
District of Columbia temperature computed as the average of Maryland and Virginia

Urbanization (2010)

Urbanization as a percentage of the population https://www.icip.iastate.edu/tables/population/urban-pct-states

Age Groups (2018)

https://www.kff.org/other/state-indicator/distribution-by-age/

School Closure Dates

Schools that haven't closed are marked NaN https://www.edweek.org/ew/section/multimedia/map-coronavirus-and-school-closures.html

Note that some datasets above did not contain data for District of Columbia, this missing data was found via Google searches manually entered.

This dataset provides a comprehensive overview of global population trends, historical data, and future projections. It includes detailed information for various countries and regions, encompassing key demographic indicators such as population size, growth rates, and density.

The dataset covers a broad time span, from 1980 to 2050, allowing for analysis of long-term population dynamics. It incorporates data from reputable sources like the United Nations Population Division and World Population Review, ensuring data accuracy and reliability.

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

This map was designed as an overview map of the Lake Tanganika Basin. Many of the data are of coarse resolution and should be verified before used in an research or planning efforts.Sources by Layer GroupsAdmin: Populations retrieved from worldpopulationreview.com.Town and village names and locations retrieved the NGA GEOnet Names Server (GNS) http://geonames.nga.mil/gns/html/. These data may be incomplete or show incorrect spellings. Refugee camp names and locations provided by Frankfurt Zoological Society. TNC Tuungane Project Villages GPS point locations collected by TNC staff. For more information about the Tuungane Project please visit: https://www.nature.org/ourinitiatives/regions/africa/wherewework/tuungane-project.xml.Interntaional Boundaries retrieved from GADM database (www.gadm.org).Admin Level 1 & 2 subnational boundaries below the country level. This varies by country. Infrastructure:Liemba stops: Derived from https://en.wikivoyage.org/wiki/MV_Liemba\Airport names: Derived from NGA GEOnet Names Server (GNS) http://geonames.nga.mil/gns/html/Roads: The Global Roads Open Access Data Set, Version 1 (gROADSv1) was developed under the auspices of the CODATA Global Roads Data Development Task Group. The data set combines the best available roads data by country into a global roads coverage, using the UN Spatial Data Infrastructure Transport (UNSDI-T) version 2 as a common data model. All country road networks have been joined topologically at the borders, and many countries have been edited for internal topology. Source data for each country are provided in the documentation, and users are encouraged to refer to the readme file for use constraints that apply to a small number of countries. Because the data are compiled from multiple sources, the date range for road network representations ranges from the 1980s to 2010 depending on the country (most countries have no confirmed date), and spatial accuracy varies. The baseline global data set was compiled by the Information Technology Outreach Services (ITOS) of the University of Georgia. Updated data for 27 countries and 6 smaller geographic entities were assembled by Columbia University's Center for International Earth Science Information Network (CIESIN), with a focus largely on developing countries with the poorest data coverage.Credits: http://sedac.ciesin.columbia.edu/data/set/groads-global-roads-open-access-v1Dams: Lehner, B., C. Reidy Liermann, C. Revenga, C. Vorosmarty, B. Fekete, P. Crouzet, P. Doll, M. Endejan, K. Frenken, J. Magome, C. Nilsson, J.C. Robertson, R. Rodel, N. Sindorf, and D. Wisser. 2011. Global Reservoir and Dam Database, Version 1 (GRanDv1): Reservoirs, Revision 01. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC).http://dx.doi.org/10.7927/H4HH6H08. Accessed 28 August 2016.Credits: http://sedac.ciesin.columbia.edu/pfs/grand.htmlPower Plants: Data for power plants with total installed generating capacity > 10 mw from the Platts World Electric Power Plants Database (WEPP 2006). Plants were georeferenced using location information from the WEPP, auxiliary GIS datasets, World Bank project documents and the internet. Locations are approximate, precision varies greatly by point, based on the source of coordinate information.The following attributes are included:PLANT: power plant name,STATUS: status (OPR, CON, PLN, OTHER, UNK),SUM_MW: total installed generating capacity,LATITUDE: approximate location, latitude,LONGITUDE: approximate location, longitude,GEN_TYPE: type of electricity generation (HYDRO, THERMAL, OTHER)Credits: http://www.infrastructureafrica.org/Transmission Lines & Railroads: Africa Infrastructure Knowledge Program http://www.infrastructureafrica.org/.Socioeconomic: FEWS Livelihood Zones, Lean Times Livelihood Hazards: These were derived form country level livelihood zones information at the Famine Early Warning System Network. : Data for individual countries with detailed descriptions of livelihood zones, inclkuding crop calendars and hazards, can be found at http://www.fews.net/.Distance to Markets:HarvestChoice, 2015. "Travel time to nearest town over 20K (mean, hours, 2000)." International Food Policy Research Institute, Washington, DC., and University of Minnesota, St. Paul, MN. Available online at http://harvestchoice.org/data/tt_20k.Lean Times: Lean Times refer to times of the year when food shortages may occur. These were derived form country level livelihood zones information at the Famine Early Warning System Network. NOTE: None of the regions within Lake Tanganyika indicated July as a time of food shortages; therefore, July is excluded as a seperate layer.http://www.fews.net/Population Density: Center for International Earth Science Information Network - CIESIN - Columbia University. 2016. Gridded Population of the World, Version 4 (GPWv4): Population Density. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/10.7927/H4NP22DQ.http://sedac.ciesin.columbia.edu/data/set/gpw-v4-population-density2011 Fishiereis Frame Survey sites: Indicates at the regional or district level, the percentage of fish landing sites with described properties. Citation: LTA Secretariat, 2012.Lake Tanganyika Regional Fisheries Frame Survey 2011, Bujumbura, Burundi, 30 pFamily Planning, HIV Statistics, Women Issues, Childrens Health, Water and Sanitation,Houshold Fuel Source: Socioeconomic data from USAID-funded The Demographic and Health Surveys (DHS) Program: Produced by ICF International. Spatial Data Repository, The Demographic and Health Surveys Program. ICF International. Available from spatialdata.dhsprogram.com [Accessed 18 August 2016]. Fishiereis Frame Survey :All Datasets Indicates at the regional or district level, the percentage of fish landing sites with described properties. Citation: LTA Secretariat, 2012.Lake Tanganyika Regional Fisheries Frame Survey 2011, Bujumbura, Burundi, 30 pFishieries Frame SurveyConservation:Human Disturbance Index:Simple Human Disturbance Index to assess the relative levels of human disturbance along the lakeshore of Lake Tanganyika. Evidence from Britton et al.(2017) indicates that human activity in the nearshore environment will significantly influence fish populations along the lakeshore. For detailed methods see https://tnc.box.com/s/k65bdhh72gjjv7f3v0gwvn2856onh9h9.Credits: Dr. Tracy Baker, The Nature Conservancy Africa Program: tracy.baker@tnc.orgHydroBASINS Level 08 Average HDI:Average level of human disturbance at the HydroBASINS Level 8. This level correxpond to the unit of analysis for IUCN Red List data. Credits: Dr. Tracy Baker, The Nature Conservancy Africa Program: tracy.baker@tnc.orgProtected Areas:IUCN and UNEP-WCMC (year), The World Database on Protected Areas (WDPA) [On-line], [January, 2017], Cambridge, UK: UNEP-WCMC. Available at: www.protectedplanet.net.Priority Aquatic Sites: Aquaruim trade watch fish: Estimated ranges of cichlids considered to be endangered or critically endagered, Credit Ad KoningsProposed Lake Key Biodiversity Area & Key Biodiversity Area Trigger Species Ranges: The Nature Conservancy staff worked with IUCN and other experts to compile and analyze available spatial data for Lake Tanganyika, to identify candidate areas within the lake that have exceptional potential to meet the revised KBAcriteria and thresholds based on the new standard, as well as having practical potential for application of local and regional management and conservation strategies. This layer represents a draft version of this work. The work still must undergo a national level stakeholder consultation. Credits: Dr. Kristen Blann, The Nature Conservancy - Freshwater Ecologist, Minnesota Priority Fisheries Conservation Sites - TAFIRI: TAFIRI Conservation Priorities derived from 2013 presentation by Dr. Ismael Kimirei, TAFIRI Director, Kigoma. Priorities were ranked by a quatitative assessment at each site. Priority Fisheries Conservation Sites - Zambia Fisheries: Zambia Fisheries priority sites acquired via personal communication with Mr. Taylor Banda, Senior Fisheries Officer at Mpulungu. The sites represent the current planning scenario alon the Zambia side of the lake. Lake & Freshwater Species & Basin Freshwater Species: Known and accessible information on freshwater species within Lake Tanganyika. Data may not include all known species for a taxon. Spatial unit used to calcuate total freshwater species richness is the HydroBASINS Level 11 dataset boundaries.Species level data were derived from the IUCN Red List of Threatened Species (http://www.iucnredlist.org), the Lake Tanganyika Biodiversity Program (http://www.ltbp.org/), and Ad Konings. Zambia Terrestrial Species Distributions: Mean probability of species presence, conditioned on environmental variables.See: https://tnc.box.com/s/hvqdyawz26i75lm5lnlj7dh0uut65rk7Credits: Dr. Anne Trainor, The Nature Conservancy Africa Program - Smart Growth Director anne.trainor@tnc.orgMammals & Amphibians : Modeled number of mammal species across the Lake Tangnayika Basin. This is a surface layer with no individual species level information given. International Union for Conservation of Nature - IUCN, and Center for International Earth Science Information Network - CIESIN - Columbia University. 2015. Gridded Species Distribution: Global Mammal Richness Grids, 2015 Release. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/10.7927/H4N014G5.Credits: http://sedac.ciesin.columbia.edu/data/set/species-global-mammal-richness-2015Terrestrial Ecoregions & Greater Mahale Ecosystem: Olson, D. M. and E. Dinerstein. 2002. The Global 200: Priority ecoregions for global conservation. (PDF file) Annals of the Missouri Botanical Garden 89:125-126. -The Nature Conservancy, USDA Forest Service and U.S. Geological Survey, based on Bailey, Robert G. 1995. Description of the ecoregions of the United States (2nd ed.). Misc. Pub. No. 1391, Map scale

Tajikistan is a landlocked country located in Central Asia bordered by Kyrgyzstan, China, Afghanistan, and Uzbekistan.It has a significantly young population with the median age being 25.3 years (World Population Review, n.d.). A majority of the population is under 40 and of the 10.1 million population, only 5.7 million are over the age of 18 (World Population Review, n.d.). That means almost half of the population are children and teenagers.Most of the population belongs to an ethnic group called the Tajik group but there are also ethnic Russians and Uzbeks who live there (World Population Review, n.d.). The country has health care system issues and life expectancy is only 66 years while infant mortality rates are at 3.7% (World Population Review, n.d.)

Introduction

Gmail Statistics: Gmail, the popular email service by Google, has become an essential tool for communication in today's digital age. But how much do you know about how Gmail works and how people use it globally? This article includes a range of effective analyses on current trends of Gmail, such as market share, users, country-wise usage, etc. All the statistics described below will be valuable.

So, let’s get ready to explore some fascinating statistics about this email giant.