4 datasets found
  1. Caribbean Netherlands, Bonaire; Cruise passengers

    • data.overheid.nl
    • cbs.nl
    • +1more
    atom, json
    Updated May 16, 2025
    + more versions
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    Centraal Bureau voor de Statistiek (Rijk) (2025). Caribbean Netherlands, Bonaire; Cruise passengers [Dataset]. https://data.overheid.nl/dataset/18127-caribbean-netherlands--bonaire--cruise-ship-passengers
    Explore at:
    json(KB), atom(KB)Available download formats
    Dataset updated
    May 16, 2025
    Dataset provided by
    Centraal Bureau voor de Statistiek
    License

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

    Area covered
    Caribisch Nederland, Bonaire
    Description

    This table contains the numbers of passengers (excluding crew members) arriving by cruise ship on Bonaire. The figures published here are entirely based on available registers, i.e. the accuracy of these figures depends on the quality of the registers and Statistics Netherlands has conducted numerous plausibility checks on these registers, for example by establishing mutual links among these registers.

    Data available from: January 2012

    Status of the figures: The figures for 2014 to 2021 are final. The figures for 2022 to 2025 are provisional.

    Changes as of May 16, 2025: - The previously published figures for 2021 have been made final. - From 2014 to 2021, the final quarterly figures have been added. - From 2022 to 2025, the provisional figures for the months, quarters and years have been added.

    When will new figures be published? The new figures will be published within three months after expiration of the period available.

  2. g

    Pedestrian evacuation time maps, population estimates, and cruise ship...

    • gimi9.com
    • data.usgs.gov
    • +2more
    Updated Feb 21, 2025
    + more versions
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    (2025). Pedestrian evacuation time maps, population estimates, and cruise ship passenger estimates for USVI tsunami-hazard zones [Dataset]. https://gimi9.com/dataset/data-gov_pedestrian-evacuation-time-maps-population-estimates-and-cruise-ship-passenger-estimates-f
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    Dataset updated
    Feb 21, 2025
    Area covered
    U.S. Virgin Islands
    Description

    These datasets support the conclusions in the journal article entitled " Population vulnerability of residents, employees, and cruise-ship passengers to tsunami hazards in complex seismic regions: a case study of the U.S. Virgin Islands" as described in the abstract below: Reducing the potential for loss of life from tsunamis is challenging on islands located in complex seismic regions given the multiple sources that surround islands, differences among islands in the amount of time to evacuate before wave arrival, and the high number of residents, employees, and tourists in tsunami-hazard zones. We examine variations in population vulnerability in island communities to multiple tsunami threats and use the United States territory of the U.S. Virgin Islands (USVI), including St. Thomas, St. John, and St. Croix islands, as our case study. We estimate the tsunami-hazard exposure of residents, employees, and cruise-ship passengers on vessels docking at USVI marine facilities, as well as model pedestrian travel times out of inundation zones for 13 credible tsunami scenarios. Results indicate that the threat to life safety in USVI posed by tsunamis is not equal among the three islands, both in terms of the magnitude of people in hazard zones and the amount of time available to evacuate for the various scenarios. The number of employees and cruise-ship passengers in tsunami-hazard zones is orders of magnitude higher than the number of residents, suggesting that risk assessments that only account for residents are under-estimating threats to life safety from tsunamis. Finally, reducing departure delays has a greater impact than increasing pedestrian travel speeds on reducing the number of people that may have insufficient time to evacuate hazard zones before wave arrival.

  3. A

    ‘COVID-19 dataset in Japan’ 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). ‘COVID-19 dataset in Japan’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-covid-19-dataset-in-japan-2665/latest
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    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
    Japan
    Description

    Analysis of ‘COVID-19 dataset in Japan’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/lisphilar/covid19-dataset-in-japan on 28 January 2022.

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

    1. Context

    This is a COVID-19 dataset in Japan. This does not include the cases in Diamond Princess cruise ship (Yokohama city, Kanagawa prefecture) and Costa Atlantica cruise ship (Nagasaki city, Nagasaki prefecture). - Total number of cases in Japan - The number of vaccinated people (New/experimental) - The number of cases at prefecture level - Metadata of each prefecture

    Note: Lisphilar (author) uploads the same files to https://github.com/lisphilar/covid19-sir/tree/master/data

    This dataset can be retrieved with CovsirPhy (Python library).

    pip install covsirphy --upgrade
    
    import covsirphy as cs
    data_loader = cs.DataLoader()
    japan_data = data_loader.japan()
    # The number of cases (Total/each province)
    clean_df = japan_data.cleaned()
    # Metadata
    meta_df = japan_data.meta()
    

    Please refer to CovsirPhy Documentation: Japan-specific dataset.

    Note: Before analysing the data, please refer to Kaggle notebook: EDA of Japan dataset and COVID-19: Government/JHU data in Japan. The detailed explanation of the build process is discussed in Steps to build the dataset in Japan. If you find errors or have any questions, feel free to create a discussion topic.

    1.1 Total number of cases in Japan

    covid_jpn_total.csv Cumulative number of cases: - PCR-tested / PCR-tested and positive - with symptoms (to 08May2020) / without symptoms (to 08May2020) / unknown (to 08May2020) - discharged - fatal

    The number of cases: - requiring hospitalization (from 09May2020) - hospitalized with mild symptoms (to 08May2020) / severe symptoms / unknown (to 08May2020) - requiring hospitalization, but waiting in hotels or at home (to 08May2020)

    In primary source, some variables were removed on 09May2020. Values are NA in this dataset from 09May2020.

    Manually collected the data from Ministry of Health, Labour and Welfare HP:
    厚生労働省 HP (in Japanese)
    Ministry of Health, Labour and Welfare HP (in English)

    The number of vaccinated people: - Vaccinated_1st: the number of vaccinated persons for the first time on the date - Vaccinated_2nd: the number of vaccinated persons with the second dose on the date - Vaccinated_3rd: the number of vaccinated persons with the third dose on the date

    Data sources for vaccination: - To 09Apr2021: 厚生労働省 HP 新型コロナワクチンの接種実績(in Japanese) - 首相官邸 新型コロナワクチンについて - From 10APr2021: Twitter: 首相官邸(新型コロナワクチン情報)

    1.2 The number of cases at prefecture level

    covid_jpn_prefecture.csv Cumulative number of cases: - PCR-tested / PCR-tested and positive - discharged - fatal

    The number of cases: - requiring hospitalization (from 09May2020) - hospitalized with severe symptoms (from 09May2020)

    Using pdf-excel converter, manually collected the data from Ministry of Health, Labour and Welfare HP:
    厚生労働省 HP (in Japanese)
    Ministry of Health, Labour and Welfare HP (in English)

    Note: covid_jpn_prefecture.groupby("Date").sum() does not match covid_jpn_total. When you analyse total data in Japan, please use covid_jpn_total data.

    1.3 Metadata of each prefecture

    covid_jpn_metadata.csv - Population (Total, Male, Female): 厚生労働省 厚生統計要覧(2017年度)第1-5表 - Area (Total, Habitable): Wikipedia 都道府県の面積一覧 (2015)

    2. Acknowledgements

    To create this dataset, edited and transformed data of the following sites was used.

    厚生労働省 Ministry of Health, Labour and Welfare, Japan:
    厚生労働省 HP (in Japanese)
    Ministry of Health, Labour and Welfare HP (in English) 厚生労働省 HP 利用規約・リンク・著作権等 CC BY 4.0 (in Japanese)

    国土交通省 Ministry of Land, Infrastructure, Transport and Tourism, Japan: 国土交通省 HP (in Japanese) 国土交通省 HP (in English) 国土交通省 HP 利用規約・リンク・著作権等 CC BY 4.0 (in Japanese)

    Code for Japan / COVID-19 Japan: Code for Japan COVID-19 Japan Dashboard (CC BY 4.0) COVID-19 Japan 都道府県別 感染症病床数 (CC BY)

    Wikipedia: Wikipedia

    LinkData: LinkData (Public Domain)

    Inspiration

    1. Changes in number of cases over time
    2. Percentage of patients without symptoms / mild or severe symptoms
    3. What to do next to prevent outbreak

    License and how to cite

    Kindly cite this dataset under CC BY-4.0 license as follows. - Hirokazu Takaya (2020-2022), COVID-19 dataset in Japan, GitHub repository, https://github.com/lisphilar/covid19-sir/data/japan, or - Hirokazu Takaya (2020-2022), COVID-19 dataset in Japan, Kaggle Dataset, https://www.kaggle.com/lisphilar/covid19-dataset-in-japan

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

  4. d

    Melbourne Visitor Contact Stats

    • data.gov.au
    unknown format
    Updated Apr 8, 2020
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    data.melbourne.vic.gov.au (2020). Melbourne Visitor Contact Stats [Dataset]. https://data.gov.au/dataset/ds-melbourne-https%3A%2F%2Fdata.melbourne.vic.gov.au%2Fapi%2Fviews%2Fe63d-rbu7
    Explore at:
    unknown formatAvailable download formats
    Dataset updated
    Apr 8, 2020
    Dataset provided by
    data.melbourne.vic.gov.au
    License

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

    Area covered
    Melbourne
    Description

    The City of Melbourne provides visitor programs such as city tours, town hall tours, cruise ship and visitor shuttle trips and face to face visitor contact points including the visitor centre, …Show full descriptionThe City of Melbourne provides visitor programs such as city tours, town hall tours, cruise ship and visitor shuttle trips and face to face visitor contact points including the visitor centre, visitor booth and the city ambassador program. This dataset tracks the number of people who participate in visitor programs and the number of visitors our customer relations officers assist every month. Melbourne Visitor Shuttle ceased as of September 2017 The Melbourne Visitor Centre closed on Sunday 19th of August 2018 The Melbourne Visitor Hub at Town Hall opened on Monday 20th of August 2018 The Visitor Hub at Queen Victoria Market opened in late November

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Centraal Bureau voor de Statistiek (Rijk) (2025). Caribbean Netherlands, Bonaire; Cruise passengers [Dataset]. https://data.overheid.nl/dataset/18127-caribbean-netherlands--bonaire--cruise-ship-passengers
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Caribbean Netherlands, Bonaire; Cruise passengers

Explore at:
json(KB), atom(KB)Available download formats
Dataset updated
May 16, 2025
Dataset provided by
Centraal Bureau voor de Statistiek
License

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

Area covered
Caribisch Nederland, Bonaire
Description

This table contains the numbers of passengers (excluding crew members) arriving by cruise ship on Bonaire. The figures published here are entirely based on available registers, i.e. the accuracy of these figures depends on the quality of the registers and Statistics Netherlands has conducted numerous plausibility checks on these registers, for example by establishing mutual links among these registers.

Data available from: January 2012

Status of the figures: The figures for 2014 to 2021 are final. The figures for 2022 to 2025 are provisional.

Changes as of May 16, 2025: - The previously published figures for 2021 have been made final. - From 2014 to 2021, the final quarterly figures have been added. - From 2022 to 2025, the provisional figures for the months, quarters and years have been added.

When will new figures be published? The new figures will be published within three months after expiration of the period available.

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