5 datasets found
  1. China Populated Places (OpenStreetMap Export)

    • data.humdata.org
    geojson, geopackage +2
    Updated Apr 15, 2025
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    Humanitarian OpenStreetMap Team (HOT) (2025). China Populated Places (OpenStreetMap Export) [Dataset]. https://data.humdata.org/dataset/hotosm_chn_populated_places
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    shp(19375476), geopackage(16452069), kml(13660947), geojson(13392890)Available download formats
    Dataset updated
    Apr 15, 2025
    Dataset provided by
    OpenStreetMap//www.openstreetmap.org/
    Humanitarian OpenStreetMap Team
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Description

    This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :

    tags['place'] IN ('isolated_dwelling', 'town', 'village', 'hamlet', 'city')

    Features may have these attributes:

    This dataset is one of many "https://data.humdata.org/organization/hot">OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

  2. China, Hong Kong Special Administrative Region Populated Places...

    • data.humdata.org
    garmin img, geojson +3
    Updated Jul 8, 2025
    + more versions
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    Humanitarian OpenStreetMap Team (HOT) (2025). China, Hong Kong Special Administrative Region Populated Places (OpenStreetMap Export) [Dataset]. https://data.humdata.org/dataset/b102ee53-8536-4871-b4d5-96e381b31353?force_layout=desktop
    Explore at:
    geopackage, garmin img, geopackage(59504), geojson(49368), shp(1895044), geopackage(1883104), geojson(1218455), shp(63856), kml(51081), kml(1228549)Available download formats
    Dataset updated
    Jul 8, 2025
    Dataset provided by
    OpenStreetMap//www.openstreetmap.org/
    Humanitarian OpenStreetMap Team
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    China, Hong Kong
    Description

    This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :

    tags['place'] IN ('isolated_dwelling', 'town', 'village', 'hamlet', 'city') OR tags['landuse'] IN ('residential')

    Features may have these attributes:

    This dataset is one of many "https://data.humdata.org/organization/hot">OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

  3. China, Macao Special Administrative Region Populated Places (OpenStreetMap...

    • data.humdata.org
    garmin img, geojson +3
    Updated Jun 1, 2025
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    Humanitarian OpenStreetMap Team (HOT) (2025). China, Macao Special Administrative Region Populated Places (OpenStreetMap Export) [Dataset]. https://data.humdata.org/dataset/c9a8a6f6-9584-439e-bfe3-7cbec642fb80?force_layout=desktop
    Explore at:
    geojson(26035), geopackage(4794), geopackage(42489), geojson(1429), shp(2344), shp(39695), garmin img, geopackage, kml(1629), kml(26509)Available download formats
    Dataset updated
    Jun 1, 2025
    Dataset provided by
    OpenStreetMap//www.openstreetmap.org/
    Humanitarian OpenStreetMap Team
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Macao, China
    Description

    This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :

    tags['place'] IN ('isolated_dwelling', 'town', 'village', 'hamlet', 'city') OR tags['landuse'] IN ('residential')

    Features may have these attributes:

    This dataset is one of many "https://data.humdata.org/organization/hot">OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

  4. C

    WeChat Statistics By Revenue, Users Demographics and Facts

    • coolest-gadgets.com
    Updated Feb 17, 2025
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    Coolest Gadgets (2025). WeChat Statistics By Revenue, Users Demographics and Facts [Dataset]. https://coolest-gadgets.com/wechat-statistics/
    Explore at:
    Dataset updated
    Feb 17, 2025
    Dataset authored and provided by
    Coolest Gadgets
    License

    https://coolest-gadgets.com/privacy-policyhttps://coolest-gadgets.com/privacy-policy

    Time period covered
    2022 - 2032
    Area covered
    Global
    Description

    Introduction

    WeChat Statistics: WeChat, developed by Tencent in China and launched in 2011, is a multi-functional app that seamlessly combines messaging, social media, and mobile payment services. Originally designed as a messaging platform similar to WhatsApp, WeChat quickly evolved into a comprehensive “super app†that enables users to communicate, make payments, and access a wide array of services, such as shopping, ride-hailing, and booking appointments. With over 1.37 billion monthly active users as of June 2024, WeChat has achieved remarkable penetration in China, capturing about 80% of the population and integrating into daily life as an essential tool.

    A key feature that sets WeChat apart is its Mini Programs, which allow third-party developers to create applications within WeChat’s ecosystem, enabling users to perform various tasks without leaving the app. This functionality has transformed mobile usage in China, making WeChat a central hub for commerce, social interactions, and more, with an 88% daily usage rate recorded in 2020 and an 89% penetration rate for Mini Programs by 2022.

    Its features, such as WeChat Pay, QR codes, and in-app marketing tools, have become essential for businesses, driving customer engagement and sales. However, as WeChat faces regulatory challenges and growing competition from other apps like Douyin, Tencent continues to innovate with new features to retain its super app status. WeChat’s development into a multi-dimensional platform underscores its role as a key player in China's digital economy and its potential to influence global app ecosystems.

  5. COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

    • statista.com
    • ai-chatbox.pro
    Updated Nov 25, 2024
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    Statista (2024). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
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    Dataset updated
    Nov 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

    The difficulties of death figures

    This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

    Where are these numbers coming from?

    The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

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    Learn how you can add new datasets to our index.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Humanitarian OpenStreetMap Team (HOT) (2025). China Populated Places (OpenStreetMap Export) [Dataset]. https://data.humdata.org/dataset/hotosm_chn_populated_places
Organization logoOrganization logo

China Populated Places (OpenStreetMap Export)

Explore at:
shp(19375476), geopackage(16452069), kml(13660947), geojson(13392890)Available download formats
Dataset updated
Apr 15, 2025
Dataset provided by
OpenStreetMap//www.openstreetmap.org/
Humanitarian OpenStreetMap Team
License

Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically

Description

This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :

tags['place'] IN ('isolated_dwelling', 'town', 'village', 'hamlet', 'city')

Features may have these attributes:

This dataset is one of many "https://data.humdata.org/organization/hot">OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

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