13 datasets found
  1. A

    ‘Population by Country - 2020’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 13, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘Population by Country - 2020’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-population-by-country-2020-c8b7/latest
    Explore at:
    Dataset updated
    Feb 13, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Population by Country - 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/tanuprabhu/population-by-country-2020 on 28 January 2022.

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

    Context

    I always wanted to access a data set that was related to the world’s population (Country wise). But I could not find a properly documented data set. Rather, I just created one manually.

    Content

    Now I knew I wanted to create a dataset but I did not know how to do so. So, I started to search for the content (Population of countries) on the internet. Obviously, Wikipedia was my first search. But I don't know why the results were not acceptable. And also there were only I think 190 or more countries. So then I surfed the internet for quite some time until then I stumbled upon a great website. I think you probably have heard about this. The name of the website is Worldometer. This is exactly the website I was looking for. This website had more details than Wikipedia. Also, this website had more rows I mean more countries with their population.

    Once I got the data, now my next hard task was to download it. Of course, I could not get the raw form of data. I did not mail them regarding the data. Now I learned a new skill which is very important for a data scientist. I read somewhere that to obtain the data from websites you need to use this technique. Any guesses, keep reading you will come to know in the next paragraph.

    https://fiverr-res.cloudinary.com/images/t_main1,q_auto,f_auto/gigs/119580480/original/68088c5f588ec32a6b3a3a67ec0d1b5a8a70648d/do-web-scraping-and-data-mining-with-python.png" alt="alt text">

    You are right its, Web Scraping. Now I learned this so that I could convert the data into a CSV format. Now I will give you the scraper code that I wrote and also I somehow found a way to directly convert the pandas data frame to a CSV(Comma-separated fo format) and store it on my computer. Now just go through my code and you will know what I'm talking about.

    Below is the code that I used to scrape the code from the website

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F3200273%2Fe814c2739b99d221de328c72a0b2571e%2FCapture.PNG?generation=1581314967227445&alt=media" alt="">

    Acknowledgements

    Now I couldn't have got the data without Worldometer. So special thanks to the website. It is because of them I was able to get the data.

    Inspiration

    As far as I know, I don't have any questions to ask. You guys can let me know by finding your ways to use the data and let me know via kernel if you find something interesting

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

  2. Population Dataset Country-Wise

    • kaggle.com
    zip
    Updated Mar 9, 2020
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    Akshit Batra (2020). Population Dataset Country-Wise [Dataset]. https://www.kaggle.com/akshitbatra/population-dataset-countrywise
    Explore at:
    zip(67274 bytes)Available download formats
    Dataset updated
    Mar 9, 2020
    Authors
    Akshit Batra
    Description

    Context

    Learning Web Scraping in order to build my own datasets, and this is the first one in the learning process. Let's try and build great datasets in the future for better analysis and predictions.

    Content

    Scraped the data on March 10, 2020, from https://www.worldometers.info/world-population/population-by-country/ Dataset represents the population count country-wise for a specific time period.

    Acknowledgements

    Firstly, Thanks to the Content creator on the website https://www.worldometers.info, who provides reliable data on the internet. Secondly, To the Tutor who taught me how to scrape websites.

    Inspiration

    Is this dataset valuable? Where can we utilize this dataset in data science?

  3. A

    ‘World Population by Year’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jan 28, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘World Population by Year’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-world-population-by-year-3a4c/0a3c3ba0/?iid=001-049&v=presentation
    Explore at:
    Dataset updated
    Jan 28, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    Analysis of ‘World Population by Year’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/sansuthi/world-population-by-year on 28 January 2022.

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

    Variables:

    • Year: 1951 to 2020
    • Population: World Population
    • ChangePerc: Yearly Change in Percentage
    • NetChange: Total Yearly Change
    • Density: Density in P/Km²
    • Urban: Urban Population
    • UrbanPerc: Urban Population Percentage

    Source of content: www.worldometers.info

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

  4. World Population Dataset

    • kaggle.com
    Updated Jan 6, 2024
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    CHANDAN CHOUDHURY (2024). World Population Dataset [Dataset]. https://www.kaggle.com/datasets/chandanchoudhury/world-population-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 6, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    CHANDAN CHOUDHURY
    Area covered
    World
    Description

    World Population Datasets Overview:

    Explore a comprehensive collection of datasets offering profound insights into global demographics and country-specific characteristics. These datasets, sourced from reputable platforms including worldometers.info and Wikipedia, cover a wide array of key indicators, providing a rich resource for in-depth analysis and exploration.

    Dataset 1: World Country Stats:

    Delve into detailed statistics for countries worldwide, encompassing essential factors such as regions, land area, fertility rates, and median ages. This dataset, provides a holistic view of demographic and geographical attributes.

    Dataset 2: World Population Details (2023):

    Gain nuanced insights into the demographic landscape of countries for the year 2023. This dataset, covers a multitude of population-related details, including yearly changes, density, net migrants, urban populations, and more.

    Dataset 3: World Population by Year (1950-2023):

    Uncover the evolution of world populations from 1950 to 2023, with yearly granularity for each country. This dataset allows you to analyze and understand population trends over more than seven decades.

    These datasets collectively form a robust foundation for researchers, analysts, and enthusiasts seeking to explore and understand the intricate dynamics of global populations and country-specific characteristics. Whether studying historical trends or focusing on the latest demographic profiles, these datasets offer a wealth of information for diverse analytical perspectives.

    Note This Dataset is created from worldometers and wikipedia.org. If you want to learn more, you can visit the Websites.

    Upvote this dataset if found helpful. :blush:

  5. Africa - Population Estimate

    • data.humdata.org
    geopackage
    Updated Feb 24, 2025
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    3iSolution (2025). Africa - Population Estimate [Dataset]. https://data.humdata.org/dataset/population-of-africa-geopackage
    Explore at:
    geopackage(241664)Available download formats
    Dataset updated
    Feb 24, 2025
    Dataset provided by
    3iSolution
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Africa
    Description

    The Africa Population (Live) counter shows a continuously updated estimate of the current population of Africa delivered by Worldometer's RTS algorithm, which processes data collected from the United Nations Population Division. From https://www.worldometers.info/world-population/africa-population/

  6. Top 20 Countries' Population as Of 2020

    • kaggle.com
    Updated Feb 26, 2021
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    Baasim Ahmed (2021). Top 20 Countries' Population as Of 2020 [Dataset]. https://www.kaggle.com/baasimahmed/top-20-countries-population-as-of-2020/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 26, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Baasim Ahmed
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    There's a story behind every dataset and here's your opportunity to share yours.

    Content

    What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

    Acknowledgements

    We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research. Credits and Information Taken by https://www.worldometers.info/world-population/

    Inspiration

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

  7. A

    SADC RVAA estimated population

    • data.amerigeoss.org
    • cloud.csiss.gmu.edu
    • +1more
    xlsx
    Updated Oct 12, 2021
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    UN Humanitarian Data Exchange (2021). SADC RVAA estimated population [Dataset]. https://data.amerigeoss.org/uk/dataset/sadc-rvaa-estimated-population-2018
    Explore at:
    xlsx(10475)Available download formats
    Dataset updated
    Oct 12, 2021
    Dataset provided by
    UN Humanitarian Data Exchange
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Estimated population data based on the latest United Nations Population Division estimates and http://www.worldometers.info/world-population/population-by-country/

  8. SADC RVAA estimated population

    • cloud.csiss.gmu.edu
    xlsx
    Updated Jul 23, 2019
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    UN Humanitarian Data Exchange (2019). SADC RVAA estimated population [Dataset]. http://cloud.csiss.gmu.edu/uddi/bg/dataset/sadc-rvaa-estimated-population-2018
    Explore at:
    xlsx(10475)Available download formats
    Dataset updated
    Jul 23, 2019
    Dataset provided by
    United Nationshttp://un.org/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Estimated population data based on the latest United Nations Population Division estimates and http://www.worldometers.info/world-population/population-by-country/

  9. World Demographic Data by Country (1955-2020)

    • zenodo.org
    csv
    Updated Nov 9, 2020
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    Ruben Deulofeu Gomez; Ruben Deulofeu Gomez (2020). World Demographic Data by Country (1955-2020) [Dataset]. http://doi.org/10.5281/zenodo.4264387
    Explore at:
    csvAvailable download formats
    Dataset updated
    Nov 9, 2020
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Ruben Deulofeu Gomez; Ruben Deulofeu Gomez
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    Demographic data set of countries of the world (1955-2020). This dataset is created using Web Scraping technics on webpage: https://www.worldometers.info/population/.

  10. Data set: 50 Muslim-majority countries and 50 richest non-Muslim countries...

    • figshare.com
    txt
    Updated Jun 1, 2023
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    Ponn P Mahayosnand; Gloria Gheno (2023). Data set: 50 Muslim-majority countries and 50 richest non-Muslim countries based on GDP: Total number of COVID-19 cases and deaths on September 18, 2020 [Dataset]. http://doi.org/10.6084/m9.figshare.14034938.v2
    Explore at:
    txtAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Ponn P Mahayosnand; Gloria Gheno
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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

  11. COVID19 cases by Continent

    • kaggle.com
    zip
    Updated Jun 3, 2020
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    Juok (2020). COVID19 cases by Continent [Dataset]. https://www.kaggle.com/dsv/1211964
    Explore at:
    zip(1325064 bytes)Available download formats
    Dataset updated
    Jun 3, 2020
    Authors
    Juok
    Description

    Context

    Late in December 2019, the World Health Organisation (WHO) China Country Office obtained information about severe pneumonia of an unknown cause, detected in the city of Wuhan in Hubei province, China. This later turned out to be the novel coronavirus disease (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) of the coronavirus family. The disease causes respiratory illness characterized by primary symptoms like cough, fever, and in more acute cases, difficulty in breathing. WHO later declared COVID-19 as a Pandemic because of its fast rate of spread across the Globe.

    Content

    The COVID-19 datasets organized by continent contain daily level information about the COVID-19 cases in the different continents of the world. It is a time-series data and the number of cases on any given day is cumulative. The original datasets can be found on this John Hopkins University Github repository. I will be updating the COVID-19 datasets on a daily basis, with every update from John Hopkins University. I have also included the World COVID-19 tests data scraped from Worldometer and 2020 world population also from [worldometer]((https://www.worldometers.info/world-population/population-by-country/).

    The datasets

    COVID-19 cases covid19_world.csv. It contains the cumulative number of COVID-19 cases from around the world since January 22, 2020, as compiled by John Hopkins University. covid19_asia.csv, covid19_africa.csv, covid19_europe.csv, covid19_northamerica.csv, covid19.southamerica.csv, covid19_oceania.csv, and covid19_others.csv. These contain the cumulative number of COVID-19 cases organized by the continent.

    Field description - ObservationDate: Date of observation in YY/MM/DD - Country_Region: name of Country or Region - Province_State: name of Province or State - Confirmed: the number of COVID-19 confirmed cases - Deaths: the number of deaths from COVID-19 - Recovered: the number of recovered cases - Active: the number of people still infected with COVID-19 Note: Active = Confirmed - (Deaths + Recovered)

    COVID-19 tests `covid19_tests.csv. It contains the cumulative number of COVID tests data from worldometer conducted since the onset of the pandemic. Data available from June 01, 2020.

    Field description Date: date in YY/MM/DD Country, Other: Country, Region, or dependency TotalTests: cumulative number of tests up till that date Population: population of Country, Region, or dependency Tests/1M pop: tests per 1 million of the population 1 Testevery X ppl: 1 test for every X number of people

    2020 world population world_population(2020).csv. It contains the 2020 world population as reported by woldometer.

    Field description Country (or dependency): Country or dependency Population (2020): population in 2020 Yearly Change: yearly change in population as a percentage Net Change: the net change in population Density(P/km2): population density Land Area(km2): land area Migrants(net): net number of migrants Fert. Rate: Fertility Rate Med. Age: median age Urban pop: urban population World Share: share of the world population as a percentage

    Acknowledgements

    1. John Hopkins University for making COVID-19 datasets available to the public: https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_daily_reports
    2. John Hopkins University COVID-19 Dashboard: https://coronavirus.jhu.edu/map.html
    3. COVID-19 Africa dashboard: http://covid-19-africa.sen.ovh/
    4. Worldometer: https://www.worldometers.info/
    5. SRk for uploading a global COVID-19 dataset on Kaggle: https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset#covid_19_data.csv
    6. United Nations Department of General Assembly and Conference Management: https://www.un.org/depts/DGACM/RegionalGroups.shtml
    7. wallpapercave.com: https://wallpapercave.com/covid-19-wallpapers

    Inspiration

    Possible Insights 1. The current number of COVID-19 cases in Africa 2. The current number of COVID-19 cases by country 3. The number of COVID-19 cases in Africa / African country(s) by May 30, 2020 (Any future date)

  12. A

    ‘Covid19 in World Countries-Latest Data’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Nov 12, 2021
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ‘Covid19 in World Countries-Latest Data’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-covid19-in-world-countries-latest-data-e27d/ee48ef6e/?iid=001-583&v=presentation
    Explore at:
    Dataset updated
    Nov 12, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    Analysis of ‘Covid19 in World Countries-Latest Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/anandhuh/covid19-in-world-countrieslatest-data on 12 November 2021.

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

    Content

    This dataset contains Covid-19 data of world countries as on November 10, 2021

    Attribute Information

    • Country - Name of world countries
    • Total Cases - Total number of Covid-19 cases
    • Total Deaths - Total number of Deaths
    • Total Recovered - Total number of recovered cases
    • Active Cases - Total number of Active cases
    • Total Cases/1 mil population- Total Cases per 1 million of the population
    • Death/1 mil population - Total Deaths per 1 million of the population
    • Total Tests - Total number of Covid tests done
    • Tests/1 mil population - Covid tests done per 1 million of the population
    • Population - Population of the country

    Source

    Link : https://www.worldometers.info/coronavirus/#countries

    Other Updated Covid 19 Datasets

    Link : https://www.kaggle.com/anandhuh/datasets

    Upvote if you find it useful 🙏

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

  13. Coronavirus COVID-19 Global Cases

    • redivis.com
    application/jsonl +7
    Updated Jul 13, 2020
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    Stanford Center for Population Health Sciences (2020). Coronavirus COVID-19 Global Cases [Dataset]. http://doi.org/10.57761/pyf5-4e40
    Explore at:
    sas, csv, application/jsonl, spss, stata, parquet, arrow, avroAvailable download formats
    Dataset updated
    Jul 13, 2020
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 22, 2020 - Jul 12, 2020
    Description

    Abstract

    JHU Coronavirus COVID-19 Global Cases, by country

    Documentation

    PHS is updating the Coronavirus Global Cases dataset weekly, Monday, Wednesday and Friday from Cloud Marketplace.

    This data comes from the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). This database was created in response to the Coronavirus public health emergency to track reported cases in real-time. The data include the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries, aggregated at the appropriate province or state. It was developed to enable researchers, public health authorities and the general public to track the outbreak as it unfolds. Additional information is available in the blog post.

    Visual Dashboard (desktop): https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

    Section 2

    Included Data Sources are:

    %3C!-- --%3E

    Section 3

    **Terms of Use: **

    This GitHub repo and its contents herein, including all data, mapping, and analysis, copyright 2020 Johns Hopkins University, all rights reserved, is provided to the public strictly for educational and academic research purposes. The Website relies upon publicly available data from multiple sources, that do not always agree. The Johns Hopkins University hereby disclaims any and all representations and warranties with respect to the Website, including accuracy, fitness for use, and merchantability. Reliance on the Website for medical guidance or use of the Website in commerce is strictly prohibited.

    Section 4

    **U.S. county-level characteristics relevant to COVID-19 **

    Chin, Kahn, Krieger, Buckee, Balsari and Kiang (forthcoming) show that counties differ significantly in biological, demographic and socioeconomic factors that are associated with COVID-19 vulnerability. A range of publicly available county-specific data identifying these key factors, guided by international experiences and consideration of epidemiological parameters of importance, have been combined by the authors and are available for use:

    https://github.com/mkiang/county_preparedness/

  14. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘Population by Country - 2020’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-population-by-country-2020-c8b7/latest

‘Population by Country - 2020’ analyzed by Analyst-2

Explore at:
Dataset updated
Feb 13, 2020
Dataset authored and provided by
Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Analysis of ‘Population by Country - 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/tanuprabhu/population-by-country-2020 on 28 January 2022.

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

Context

I always wanted to access a data set that was related to the world’s population (Country wise). But I could not find a properly documented data set. Rather, I just created one manually.

Content

Now I knew I wanted to create a dataset but I did not know how to do so. So, I started to search for the content (Population of countries) on the internet. Obviously, Wikipedia was my first search. But I don't know why the results were not acceptable. And also there were only I think 190 or more countries. So then I surfed the internet for quite some time until then I stumbled upon a great website. I think you probably have heard about this. The name of the website is Worldometer. This is exactly the website I was looking for. This website had more details than Wikipedia. Also, this website had more rows I mean more countries with their population.

Once I got the data, now my next hard task was to download it. Of course, I could not get the raw form of data. I did not mail them regarding the data. Now I learned a new skill which is very important for a data scientist. I read somewhere that to obtain the data from websites you need to use this technique. Any guesses, keep reading you will come to know in the next paragraph.

https://fiverr-res.cloudinary.com/images/t_main1,q_auto,f_auto/gigs/119580480/original/68088c5f588ec32a6b3a3a67ec0d1b5a8a70648d/do-web-scraping-and-data-mining-with-python.png" alt="alt text">

You are right its, Web Scraping. Now I learned this so that I could convert the data into a CSV format. Now I will give you the scraper code that I wrote and also I somehow found a way to directly convert the pandas data frame to a CSV(Comma-separated fo format) and store it on my computer. Now just go through my code and you will know what I'm talking about.

Below is the code that I used to scrape the code from the website

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F3200273%2Fe814c2739b99d221de328c72a0b2571e%2FCapture.PNG?generation=1581314967227445&alt=media" alt="">

Acknowledgements

Now I couldn't have got the data without Worldometer. So special thanks to the website. It is because of them I was able to get the data.

Inspiration

As far as I know, I don't have any questions to ask. You guys can let me know by finding your ways to use the data and let me know via kernel if you find something interesting

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

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