100+ datasets found
  1. d

    Website Analytics

    • catalog.data.gov
    • data.brla.gov
    • +3more
    Updated Sep 20, 2025
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    data.brla.gov (2025). Website Analytics [Dataset]. https://catalog.data.gov/dataset/website-analytics-89ba5
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    Dataset updated
    Sep 20, 2025
    Dataset provided by
    data.brla.gov
    Description

    Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.

  2. Network Traffic Dataset

    • kaggle.com
    Updated Oct 31, 2023
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    Ravikumar Gattu (2023). Network Traffic Dataset [Dataset]. https://www.kaggle.com/datasets/ravikumargattu/network-traffic-dataset
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 31, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Ravikumar Gattu
    License

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

    Description

    Context

    The data presented here was obtained in a Kali Machine from University of Cincinnati,Cincinnati,OHIO by carrying out packet captures for 1 hour during the evening on Oct 9th,2023 using Wireshark.This dataset consists of 394137 instances were obtained and stored in a CSV (Comma Separated Values) file.This large dataset could be used utilised for different machine learning applications for instance classification of Network traffic,Network performance monitoring,Network Security Management , Network Traffic Management ,network intrusion detection and anomaly detection.

    The dataset can be used for a variety of machine learning tasks, such as network intrusion detection, traffic classification, and anomaly detection.

    Content :

    This network traffic dataset consists of 7 features.Each instance contains the information of source and destination IP addresses, The majority of the properties are numeric in nature, however there are also nominal and date kinds due to the Timestamp.

    The network traffic flow statistics (No. Time Source Destination Protocol Length Info) were obtained using Wireshark (https://www.wireshark.org/).

    Dataset Columns:

    No : Number of Instance. Timestamp : Timestamp of instance of network traffic Source IP: IP address of Source Destination IP: IP address of Destination Portocol: Protocol used by the instance Length: Length of Instance Info: Information of Traffic Instance

    Acknowledgements :

    I would like thank University of Cincinnati for giving the infrastructure for generation of network traffic data set.

    Ravikumar Gattu , Susmitha Choppadandi

    Inspiration : This dataset goes beyond the majority of network traffic classification datasets, which only identify the type of application (WWW, DNS, ICMP,ARP,RARP) that an IP flow contains. Instead, it generates machine learning models that can identify specific applications (like Tiktok,Wikipedia,Instagram,Youtube,Websites,Blogs etc.) from IP flow statistics (there are currently 25 applications in total).

    **Dataset License: ** CC0: Public Domain

    Dataset Usages : This dataset can be used for different machine learning applications in the field of cybersecurity such as classification of Network traffic,Network performance monitoring,Network Security Management , Network Traffic Management ,network intrusion detection and anomaly detection.

    ML techniques benefits from this Dataset :

    This dataset is highly useful because it consists of 394137 instances of network traffic data obtained by using the 25 applications on a public,private and Enterprise networks.Also,the dataset consists of very important features that can be used for most of the applications of Machine learning in cybersecurity.Here are few of the potential machine learning applications that could be benefited from this dataset are :

    1. Network Performance Monitoring : This large network traffic data set can be utilised for analysing the network traffic to identifying the network patterns in the network .This help in designing the network security algorithms for minimise the network probelms.

    2. Anamoly Detection : Large network traffic dataset can be utilised training the machine learning models for finding the irregularitues in the traffic which could help identify the cyber attacks.

    3.Network Intrusion Detection : This large dataset could be utilised for machine algorithms training and designing the models for detection of the traffic issues,Malicious traffic network attacks and DOS attacks as well.

  3. Share of U.S. mobile website traffic 2015-2025

    • statista.com
    Updated Sep 11, 2025
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    Statista (2025). Share of U.S. mobile website traffic 2015-2025 [Dataset]. https://www.statista.com/statistics/683082/share-of-website-traffic-coming-from-mobile-devices-usa/
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    Dataset updated
    Sep 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of the second quarter of 2025, ***** percent of web traffic in the United States originated from mobile devices, down from over ** percent in the last quarter of 2024. In comparison, over ********** of web traffic worldwide was generated via mobile in the last examined period.

  4. METR-LA

    • kaggle.com
    Updated Feb 24, 2024
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    HuuAnnnn (2024). METR-LA [Dataset]. https://www.kaggle.com/datasets/annnnguyen/metr-la-dataset
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 24, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    HuuAnnnn
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    A dataset containing the traffic network information in Los Angeles city from March to Jun 2012. It is used in the traffic forecasting task in Graph Neural Networks.

    The source from the paper: https://arxiv.org/abs/2206.09113

    The METR-LA dataset contains 02 information: - A adj_METR-LA.pkl: is the graph that contains the physical connection of 207 loop detectors in the traffic network. This dictionary contains 03 elements: the real sensor ID, the mapped sensor to node ID, and the adjacency matrix. - A METR-LA.h5: is the time series that is collected from each sensor in the traffic network over time.

  5. Total global visitor traffic to Google.com 2024

    • statista.com
    Updated Aug 20, 2025
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    Statista (2025). Total global visitor traffic to Google.com 2024 [Dataset]. https://www.statista.com/statistics/268252/web-visitor-traffic-to-googlecom/
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    Dataset updated
    Aug 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2023 - Mar 2024
    Area covered
    Worldwide
    Description

    In March 2024, search platform Google.com generated approximately 85.5 billion visits, down from 87 billion platform visits in October 2023. Google is a global search platform and one of the biggest online companies worldwide.

  6. Website traffic strategies by industry and size of enterprise

    • datasets.ai
    • www150.statcan.gc.ca
    • +3more
    21, 55, 8
    Updated Aug 8, 2024
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    Statistics Canada | Statistique Canada (2024). Website traffic strategies by industry and size of enterprise [Dataset]. https://datasets.ai/datasets/a7882acc-a647-4fa6-a58b-6dae889de472
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    8, 55, 21Available download formats
    Dataset updated
    Aug 8, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Authors
    Statistics Canada | Statistique Canada
    Description

    Digital technology and Internet use, website traffic strategies, by North American Industry Classification System (NAICS) and size of enterprise for Canada from 2012 to 2013.

  7. d

    NYC.gov Web Analytics

    • catalog.data.gov
    • data.cityofnewyork.us
    • +3more
    Updated Sep 30, 2022
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    data.cityofnewyork.us (2022). NYC.gov Web Analytics [Dataset]. https://catalog.data.gov/dataset/nyc-gov-web-analytics
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    Dataset updated
    Sep 30, 2022
    Dataset provided by
    data.cityofnewyork.us
    Area covered
    New York
    Description

    Web traffic statistics for the top 2000 most visited pages on nyc.gov by month.

  8. i

    Data from: MGraph: Adaptive Multi-Graph Neural Network for Dynamic...

    • ieee-dataport.org
    Updated Jul 29, 2025
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    Jabulani Mpofu (2025). MGraph: Adaptive Multi-Graph Neural Network for Dynamic Spatial-Temporal Traffic Flow Forecasting [Dataset]. https://ieee-dataport.org/documents/mgraph-adaptive-multi-graph-neural-network-dynamic-spatial-temporal-traffic-flow
    Explore at:
    Dataset updated
    Jul 29, 2025
    Authors
    Jabulani Mpofu
    Description

    30

  9. T

    Internet Traffic from Mobile Devices Statistics 2025

    • techkv.com
    Updated Jul 31, 2025
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    TechKV (2025). Internet Traffic from Mobile Devices Statistics 2025 [Dataset]. https://techkv.com/mobile-internet-traffic-statistics/
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    Dataset updated
    Jul 31, 2025
    Dataset authored and provided by
    TechKV
    License

    https://techkv.com/privacy-policy/https://techkv.com/privacy-policy/

    Time period covered
    Jan 1, 2024 - Dec 31, 2025
    Area covered
    Global
    Description

    It’s not really surprising to know that most of the internet traffic comes from mobile devices. Yet, I wouldn’t have believed this 10 or 15 years back. Sure, mobile devices were becoming popular, but the adoption rates had a sudden jump in the past decade. A quick analysis of statistics...

  10. Global monthly traffic volume for leading online education platforms...

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Global monthly traffic volume for leading online education platforms 2022-2024 [Dataset]. https://www.statista.com/statistics/1462755/web-traffic-online-learning-platforms/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 2022 - Jan 2024
    Area covered
    Worldwide
    Description

    Between December 2022 and January 2024, ******** was the online learning platform reporting the highest traffic, with a peak of *** million visits to its websites in December 2023. ******** ranked second, with the platform reaching a peak of ** million visits in the examined period. The website ******* (which stands for technology, entertainment, design) saw a peak of over ** million visits in March 2023.

  11. DoorDash.com: web traffic worldwide 2025

    • statista.com
    Updated Jul 15, 2025
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    Statista (2025). DoorDash.com: web traffic worldwide 2025 [Dataset]. https://www.statista.com/statistics/1452396/doordash-web-traffic-worldwide/
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    Dataset updated
    Jul 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 2025
    Area covered
    United States, Worldwide
    Description

    In June 2025, DoorDash's website, doordash.com, had just under 72 million visitors globally, recording a bounce rate of approximately 34.2 percent. For comparison, web traffic figures of UberEats show lower monthly visits.

  12. Total global visitor traffic to Facebook.com 2024

    • statista.com
    Updated Aug 20, 2025
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    Statista (2025). Total global visitor traffic to Facebook.com 2024 [Dataset]. https://www.statista.com/statistics/1259926/web-visitor-traffic-to-facebookcom/
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    Dataset updated
    Aug 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2023 - Mar 2024
    Area covered
    Worldwide
    Description

    Facebook is a web traffic powerhouse: in March 2024 approximately 16.6 billion visits were measured to the Facebook.com, making it one of the most-visited websites online. In the third quarter of 2023, Facebook had nearly three billion monthly active users.

  13. f

    Data sources used to develop brand metrics.

    • plos.figshare.com
    xls
    Updated Dec 20, 2024
    + more versions
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    Stephanie R. Pitts; Sarah Trigger; Dannielle E. Kelley (2024). Data sources used to develop brand metrics. [Dataset]. http://doi.org/10.1371/journal.pone.0311723.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Dec 20, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Stephanie R. Pitts; Sarah Trigger; Dannielle E. Kelley
    License

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

    Description

    Puff Bar, a disposable electronic nicotine delivery system (ENDS), was the ENDS brand most commonly used by U.S. youth in 2021. We explored whether Puff Bar’s rise in marketplace prominence was detectable through advertising, retail sales, social media, and web traffic data sources. We retrospectively documented potential signals of interest in and uptake of Puff Bar in the United States using metrics based on advertising (Numerator and Comperemedia), retail sales (NielsenIQ), social media (Twitter, via Sprinklr), and web traffic (Similarweb) data from January 2019 to June 2022. We selected metrics based on (1) data availability, (2) potential to graph metric longitudinally, and (3) variability in metric. We graphed metrics and assessed data patterns compared to data for Vuse, a comparator product, and in the context of regulatory events significant to Puff Bar. The number of Twitter posts that contained a Puff Bar term (social media), Puff Bar product sales measured in dollars (sales), and the number of visits to the Puff Bar website (web traffic) exhibited potential for surveilling Puff Bar due to ease of calculation, comprehensibility, and responsiveness to events. Advertising tracked through Numerator and Comperemedia did not appear to capture marketing from Puff Bar’s manufacturer or drive change in marketplace prominence. This study demonstrates how quantitative changes in metrics developed using advertising, retail sales, social media, and web traffic data sources detected changes in Puff Bar’s marketplace prominence. We conclude that low-effort, scalable, rapid signal detection capabilities can be an important part of a multi-component tobacco surveillance program.

  14. u

    alis.alberta.ca - Web Traffic Statistics - Catalogue - Canadian Urban Data...

    • data.urbandatacentre.ca
    Updated Jun 24, 2025
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    (2025). alis.alberta.ca - Web Traffic Statistics - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/ab-alis-alberta-ca-web-traffic
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    Dataset updated
    Jun 24, 2025
    Description

    Through its Employment and Financial Services (EFS) division, Seniors, Community and Social Services’ (SCSS) programs form a strong foundation of support to help many Albertans find and keep jobs. The ministry provides financial support, employment services, career resources, referrals, information on job fairs and workshops, and local labor market information. The goal is to help individuals and families gain independence by providing opportunities to enhance their skills to get jobs. The alis.alberta.ca website provides employment resources to help Albertans enhance their employability, plan for education and training, make informed career choices, and connect to and be successful in the labour market. This dataset provides information on web traffic statistics for the alis website, including information on pageviews and web sessions, demographic information for web sessions, and traffic information for the alis YouTube channel (https://www.youtube.com/user/ALISwebsite).

  15. Y

    Citation Network Graph

    • shibatadb.com
    Updated Oct 29, 2007
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    Yubetsu (2007). Citation Network Graph [Dataset]. https://www.shibatadb.com/article/nHwe8Hfg
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    Dataset updated
    Oct 29, 2007
    Dataset authored and provided by
    Yubetsu
    License

    https://www.shibatadb.com/license/data/proprietary/v1.0/license.txthttps://www.shibatadb.com/license/data/proprietary/v1.0/license.txt

    Description

    Network of 42 papers and 94 citation links related to "Large-Scale Freeway Network Traffic Monitoring: A Map-Matching Algorithm Based on Low-Logging Frequency GPS Probe Data".

  16. Global share of human and bot web traffic 2013-2024

    • statista.com
    Updated Jul 21, 2025
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    Statista (2025). Global share of human and bot web traffic 2013-2024 [Dataset]. https://www.statista.com/statistics/1264226/human-and-bot-web-traffic-share/
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    Dataset updated
    Jul 21, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    In 2024, most of the global website traffic was still generated by humans, but bot traffic is constantly growing. Fraudulent traffic through bad bot actors accounted for 37 percent of global web traffic in the most recently measured period, representing an increase of 12 percent from the previous year. Sophistication of Bad Bots on the rise The complexity of malicious bot activity has dramatically increased in recent years. Advanced bad bots have doubled in prevalence over the past 2 years, indicating a surge in the sophistication of cyber threats. Simultaneously, the share of simple bad bots drastically increased over the last years, suggesting a shift in the landscape of automated threats. Meanwhile, areas like food and groceries, sports, gambling, and entertainment faced the highest amount of advanced bad bots, with more than 70 percent of their bot traffic affected by evasive applications. Good and bad bots across industries The impact of bot traffic varies across different sectors. Bad bots accounted for over 50 percent of the telecom and ISPs, community and society, and computing and IT segments web traffic. However, not all bot traffic is considered bad. Some of these applications help index websites for search engines or monitor website performance, assisting users throughout their online search. Therefore, areas like entertainment, food and groceries, and even areas targeted by bad bots themselves experienced notable levels of good bot traffic, demonstrating the diverse applications of benign automated systems across different sectors.

  17. a

    TrafficReportingLayers

    • azgeo-open-data-agic.hub.arcgis.com
    Updated Nov 1, 2024
    + more versions
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    AZGeo ArcGIS Online (AGO) (2024). TrafficReportingLayers [Dataset]. https://azgeo-open-data-agic.hub.arcgis.com/maps/b55316b859494e148f23f4574575157c
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    Dataset updated
    Nov 1, 2024
    Dataset authored and provided by
    AZGeo ArcGIS Online (AGO)
    Area covered
    Description

    Traffic sections define segments of roadway where traffic volume is homogeneous along each segment length, and the specific breakpoints where traffic volumes change. This segmentation of the roadway network is necessary for the assignment of point level traffic count information to GIS roadway segments and serve to support HPMS annual reporting and other planning purposes. The relationship between traffic count stations and traffic sections is defined in the traffic sections, and this link is critical in the creation, management, and use of all network traffic statistics and information. The spatial location of each traffic section and station is defined in ADOT’s GIS linear reference system.Traffic counts are generally collected at a single point along a section of roadway, and are commonly referred to as Count Locations, Sites, or Stations.Ideally, counts are taken at the same location (or nearby) periodically. The MS2 Traffic Count Database System (TCDS) allows traffic collection agencies to create or contribute to a database of traffic data, including count locations. ADOT also maintains a database of traffic count stations, which is reconciled with the TCDS. Traffic Count Stations are assigned to a Traffic Section through the Traffic Section ID. The Station"s ID can also be used in the calculation of traffic statistics for that Traffic Section, which is how it is utilized in analysis and reporting (such as HPMS).

  18. Share of mobile internet traffic in global regions 2025

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Share of mobile internet traffic in global regions 2025 [Dataset]. https://www.statista.com/statistics/306528/share-of-mobile-internet-traffic-in-global-regions/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2025
    Area covered
    Worldwide
    Description

    In January 2025 mobile devices excluding tablets accounted for over ** percent of web page views worldwide. Meanwhile, over ** percent of webpage views in Africa were generated via mobile. In contrast, just over half of web traffic in North America still took place via desktop connections with mobile only accounting for **** percent of total web traffic. While regional infrastructure remains an important factor in broadband vs. mobile coverage, most of the world has had their eyes on the recent 5G rollout across the globe, spearheaded by tech-leaders China and the United States. The number of mobile 5G subscriptions worldwide is forecast to reach more than ***** billion by 2028. Social media: room for growth in Africa and southern Asia Overall, more than ** percent of the world’s mobile internet subscribers are also active on social media. A fast-growing market, with newcomers such as TikTok taking the world by storm, marketers have been cashing in on social media’s reach. Overall, social media penetration is highest in Europe and America while in Africa and southern Asia, there is still room for growth. As of 2021, Facebook and Google-owned YouTube are the most popular social media platforms worldwide. Facebook and Instagram are most effective With nearly ***** billion users, it is no wonder that Facebook remains the social media avenue of choice for the majority of marketers across the world. Instagram, meanwhile, was the second most popular outlet. Both platforms are low-cost and support short-form content, known for its universal consumer appeal and answering to the most important benefits of using these kind of platforms for business and advertising purposes.

  19. Global data traffic 1H 2021, by category

    • statista.com
    Updated Jul 1, 2025
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    Statista (2025). Global data traffic 1H 2021, by category [Dataset]. https://www.statista.com/statistics/1312357/global-data-traffic-by-content-type/
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    Dataset updated
    Jul 1, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    In the first half of 2021, video accounted for over **** of global traffic. Social occupied the next largest share at **** percent, while web browsing accounted for around a *****. Audio accounted for only **** percent of traffic worldwide.

  20. Netherlands: share of web traffic 2025, by device

    • statista.com
    Updated Mar 21, 2025
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    Statista (2025). Netherlands: share of web traffic 2025, by device [Dataset]. https://www.statista.com/statistics/1382691/distribution-of-websites-traffic-in-netherlands-by-device/
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    Dataset updated
    Mar 21, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2025
    Area covered
    Netherlands
    Description

    In February 2025, laptop and desktop devices generated around 54 percent of the web traffic from web browsers in the Netherlands. Traffic generated by mobile phones accounted for almost 44 percent of the total, while tablets only made up 1.99 percent.

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data.brla.gov (2025). Website Analytics [Dataset]. https://catalog.data.gov/dataset/website-analytics-89ba5

Website Analytics

Explore at:
Dataset updated
Sep 20, 2025
Dataset provided by
data.brla.gov
Description

Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.

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