31 datasets found
  1. 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.

  2. Recipe Site Traffic: Analysis & Prediction

    • kaggle.com
    Updated Sep 21, 2025
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    Michael Matta (2025). Recipe Site Traffic: Analysis & Prediction [Dataset]. https://www.kaggle.com/datasets/michaelmatta0/recipe-site-traffic-analysis-and-prediction
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 21, 2025
    Dataset provided by
    Kaggle
    Authors
    Michael Matta
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    This dataset originates from DataCamp. Many users have reposted copies of the CSV on Kaggle, but most of those uploads omit the original instructions, business context, and problem framing. In this upload, I’ve included that missing context in the About Dataset so the reader of my notebook or any other notebook can fully understand how the data was intended to be used and the intended problem framing.

    Note: I have also uploaded a visualization of the workflow I personally took to tackle this problem, but it is not part of the dataset itself. Additionally, I created a PowerPoint presentation based on my work in the notebook, which you can download from here:
    PPTX Presentation

    Recipe Site Traffic

    From: Head of Data Science
    Received: Today
    Subject: New project from the product team

    Hey!

    I have a new project for you from the product team. Should be an interesting challenge. You can see the background and request in the email below.

    I would like you to perform the analysis and write a short report for me. I want to be able to review your code as well as read your thought process for each step. I also want you to prepare and deliver the presentation for the product team - you are ready for the challenge!

    They want us to predict which recipes will be popular 80% of the time and minimize the chance of showing unpopular recipes. I don't think that is realistic in the time we have, but do your best and present whatever you find.

    You can find more details about what I expect you to do here. And information on the data here.

    I will be on vacation for the next couple of weeks, but I know you can do this without my support. If you need to make any decisions, include them in your work and I will review them when I am back.

    Good Luck!

    From: Product Manager - Recipe Discovery
    To: Head of Data Science
    Received: Yesterday
    Subject: Can you help us predict popular recipes?

    Hi,

    We haven't met before but I am responsible for choosing which recipes to display on the homepage each day. I have heard about what the data science team is capable of and I was wondering if you can help me choose which recipes we should display on the home page?

    At the moment, I choose my favorite recipe from a selection and display that on the home page. We have noticed that traffic to the rest of the website goes up by as much as 40% if I pick a popular recipe. But I don't know how to decide if a recipe will be popular. More traffic means more subscriptions so this is really important to the company.

    Can your team: - Predict which recipes will lead to high traffic? - Correctly predict high traffic recipes 80% of the time?

    We need to make a decision on this soon, so I need you to present your results to me by the end of the month. Whatever your results, what do you recommend we do next?

    Look forward to seeing your presentation.

    About Tasty Bytes

    Tasty Bytes was founded in 2020 in the midst of the Covid Pandemic. The world wanted inspiration so we decided to provide it. We started life as a search engine for recipes, helping people to find ways to use up the limited supplies they had at home.

    Now, over two years on, we are a fully fledged business. For a monthly subscription we will put together a full meal plan to ensure you and your family are getting a healthy, balanced diet whatever your budget. Subscribe to our premium plan and we will also deliver the ingredients to your door.

    Example Recipe

    This is an example of how a recipe may appear on the website, we haven't included all of the steps but you should get an idea of what visitors to the site see.

    Tomato Soup

    Servings: 4
    Time to make: 2 hours
    Category: Lunch/Snack
    Cost per serving: $

    Nutritional Information (per serving) - Calories 123 - Carbohydrate 13g - Sugar 1g - Protein 4g

    Ingredients: - Tomatoes - Onion - Carrot - Vegetable Stock

    Method: 1. Cut the tomatoes into quarters….

    Data Information

    The product manager has tried to make this easier for us and provided data for each recipe, as well as whether there was high traffic when the recipe was featured on the home page.

    As you will see, they haven't given us all of the information they have about each recipe.

    You can find the data here.

    I will let you decide how to process it, just make sure you include all your decisions in your report.

    Don't forget to double check the data really does match what they say - it might not.

    Column NameDetails
    recipeNumeric, unique identifier of recipe
    caloriesNumeric, number of calories
    carbohydrateNumeric, amount of carbohydrates in grams
    sugarNumeric, amount of sugar in grams
    proteinNumeric, amount of prote...
  3. Total global visitor traffic to amazon.com 2024

    • statista.com
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    Statista, Total global visitor traffic to amazon.com 2024 [Dataset]. https://www.statista.com/statistics/623566/web-visits-to-amazoncom/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2023 - Mar 2024
    Area covered
    Worldwide
    Description

    In March 2024, Amazon.com had approximately 2.2 billion combined web visits, up from 2.1 billion visits in February. In the fourth quarter of 2024, Amazon’s net income amounted to approximately 20 billion U.S. dollars. Online retail in the United States Online retail in the United States is constantly growing. In the third quarter of 2023, e-commerce sales accounted for 15.6 percent of retail sales in the United States. During that quarter, U.S. retail e-commerce sales amounted to over 284 billion U.S. dollars. Amazon is the leading online store in the country, in terms of e-commerce net sales. Amazon.com generated around 130 billion U.S. dollars in online sales in 2022. Walmart ranked as the second-biggest online store, with revenues of 52 billion U.S. dollars. The king of Black Friday In 2023, Amazon ranked as U.S. shoppers' favorite place to go shopping during Black Friday, even surpassing in-store purchasing. Nearly six out of ten consumers chose Amazon as the number one place to go find the best Black Friday deals. Similar findings can be observed in the United Kingdom (UK), where Amazon is also ranked as the preferred Black Friday destination.

  4. d

    Traffic counter – daily history

    • datasets.ai
    23, 57, 8
    Updated Mar 26, 2025
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    Plateforme ouverte des données publiques françaises (2025). Traffic counter – daily history [Dataset]. https://datasets.ai/datasets/https-opendata-bordeaux-metropole-fr-explore-dataset-pc_capte_p_histo_jour-
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    23, 8, 57Available download formats
    Dataset updated
    Mar 26, 2025
    Dataset authored and provided by
    Plateforme ouverte des données publiques françaises
    Description

    The dataset presents the counting history (per day) of the different counting sites (loop-type traffic counter). It is built from the webservice of aggregation proposed by Bordeaux Métropole.

    A join was made with the dataset Traffic Counter in order to retrieve all descriptive information from the counting site including location and date of installation (cdate).

  5. s

    Data from: Traffic Volumes

    • data.sandiego.gov
    Updated Jul 29, 2016
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    (2016). Traffic Volumes [Dataset]. https://data.sandiego.gov/datasets/traffic-volumes/
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    csv csv is tabular data. excel, google docs, libreoffice calc or any plain text editor will open files with this format. learn moreAvailable download formats
    Dataset updated
    Jul 29, 2016
    Description

    The census count of vehicles on city streets is normally reported in the form of Average Daily Traffic (ADT) counts. These counts provide a good estimate for the actual number of vehicles on an average weekday at select street segments. Specific block segments are selected for a count because they are deemed as representative of a larger segment on the same roadway. ADT counts are used by transportation engineers, economists, real estate agents, planners, and others professionals for planning and operational analysis. The frequency for each count varies depending on City staff’s needs for analysis in any given area. This report covers the counts taken in our City during the past 12 years approximately.

  6. Share of global mobile website traffic 2015-2025

    • statista.com
    Updated Nov 19, 2025
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    Statista (2025). Share of global mobile website traffic 2015-2025 [Dataset]. https://www.statista.com/statistics/277125/share-of-website-traffic-coming-from-mobile-devices/
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    Dataset updated
    Nov 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    In the second quarter of 2025, mobile devices (excluding tablets) accounted for 62.54 percent of global website traffic. Since consistently maintaining a share of around 50 percent beginning in 2017, mobile usage surpassed this threshold in 2020 and has demonstrated steady growth in its dominance of global web access. Mobile traffic Due to low infrastructure and financial restraints, many emerging digital markets skipped the desktop internet phase entirely and moved straight onto mobile internet via smartphone and tablet devices. India is a prime example of a market with a significant mobile-first online population. Other countries with a significant share of mobile internet traffic include Nigeria, Ghana and Kenya. In most African markets, mobile accounts for more than half of the web traffic. By contrast, mobile only makes up around 45.49 percent of online traffic in the United States. Mobile usage The most popular mobile internet activities worldwide include watching movies or videos online, e-mail usage and accessing social media. Apps are a very popular way to watch video on the go and the most-downloaded entertainment apps in the Apple App Store are Netflix, Tencent Video and Amazon Prime Video.

  7. Traffic Counter Data

    • datasets.ai
    • cloud.csiss.gmu.edu
    • +1more
    0, 53, 54
    Updated Oct 12, 2015
    + more versions
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    Data.gov.ie (2015). Traffic Counter Data [Dataset]. https://datasets.ai/datasets/325e4b9e-067f-4b43-b514-18fcbe988061
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    53, 54, 0Available download formats
    Dataset updated
    Oct 12, 2015
    Dataset provided by
    data.gov.ie
    Description

    The NRA Traffic Data website presents data collected from the NRA traffic counters located on the National Road Network. The Website uses a dynamic mapping interface to allow the User to access data in a variety of report formats. Counter data includes multi-day volume, daily volume, weekly volume, average week, monthly volume, monthly summary, and hourly direction

  8. Data from: Annual Average Daily Traffic

    • gisdata-caltrans.opendata.arcgis.com
    • data.ca.gov
    • +2more
    Updated Sep 30, 2024
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    California_Department_of_Transportation (2024). Annual Average Daily Traffic [Dataset]. https://gisdata-caltrans.opendata.arcgis.com/datasets/d8833219913c44358f2a9a71bda57f76
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    Dataset updated
    Sep 30, 2024
    Dataset provided by
    Caltranshttp://dot.ca.gov/
    Authors
    California_Department_of_Transportation
    Area covered
    Description

    Annual average daily traffic is the total volume for the year divided by 365 days. The traffic count year is from October 1st through September 30th. Very few locations in California are actually counted continuously. Traffic Counting is generally performed by electronic counting instruments moved from location throughout the State in a program of continuous traffic count sampling. The resulting counts are adjusted to an estimate of annual average daily traffic by compensating for seasonal influence, weekly variation and other variables which may be present. Annual ADT is necessary for presenting a statewide picture of traffic flow, evaluating traffic trends, computing accident rates. planning and designing highways and other purposes.Traffic Census Program Page

  9. M

    Annual Average Daily Traffic Locations in Minnesota

    • gisdata.mn.gov
    fgdb, gpkg, html +3
    Updated Nov 27, 2025
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    Transportation Department (2025). Annual Average Daily Traffic Locations in Minnesota [Dataset]. https://gisdata.mn.gov/dataset/trans-aadt-traffic-count-locs
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    shp, html, webapp, gpkg, jpeg, fgdbAvailable download formats
    Dataset updated
    Nov 27, 2025
    Dataset provided by
    Transportation Department
    Area covered
    Minnesota
    Description

    AADT represents current (most recent) Annual Average Daily Traffic on sampled road systems. This information is displayed using the Traffic Count Locations Active feature class as of the annual HPMS freeze in January. Historical AADT is found in another table. Please note that updates to this dataset are on an annual basis, therefore the data may not match ground conditions or may not be available for new roadways. Resource Contact: Christy Prentice, Traffic Forecasting & Analysis (TFA), http://www.dot.state.mn.us/tda/contacts.html#TFA

    Check other metadata records in this package for more information on Annual Average Daily Traffic Locations Information.


    Link to ESRI Feature Service:

    Annual Average Daily Traffic Locations in Minnesota: Annual Average Daily Traffic Locations


  10. Leading websites worldwide 2025, by monthly visits

    • statista.com
    • boostndoto.org
    Updated Oct 29, 2025
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    Statista (2025). Leading websites worldwide 2025, by monthly visits [Dataset]. https://www.statista.com/statistics/1201880/most-visited-websites-worldwide/
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    Dataset updated
    Oct 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 2025
    Area covered
    Worldwide
    Description

    In August 2025, Google.com was the most visited website worldwide, with an average of 98.2 billion monthly visits. The platform has maintained its leading position since June 2010, when it surpassed Yahoo to take first place. YouTube ranked second during the same period, recording over 48 billion monthly visits. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.

  11. Traffic Volume Archive 2006 to 2021

    • gis-michigan.opendata.arcgis.com
    • hub.arcgis.com
    Updated Oct 15, 2015
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    Michigan Department of Transportation (2015). Traffic Volume Archive 2006 to 2021 [Dataset]. https://gis-michigan.opendata.arcgis.com/maps/2bcfd62c243e462ea4ff040f8581fe5f
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    Dataset updated
    Oct 15, 2015
    Dataset authored and provided by
    Michigan Department of Transportationhttp://www.michigan.gov/mdot
    Area covered
    Description

    The Annual Average Daily Traffic (AADT) is the estimated mean daily traffic volume and the Commercial Annual Average Daily Traffic (CAADT) is the estimated mean daily traffic volume for commercial vehicles. For continuous sites, estimates are calculated by summing the Annual Average Days of the Week and dividing by seven. For short-count sites, estimates are made by factoring a short count using seasonal and day-of-week adjustment factors.Data Coverage: The dataset covers the entire Federal Aid System in the State of Michigan.Update Cycle: AADT & CAADT volumes are created and released every year.Transportation Data Management System (TDMS) AADT Calculation HelpTraffic Monitoring Program

  12. G

    Traffic flow

    • open.canada.ca
    • catalogue.arctic-sdi.org
    csv, geojson, gpkg +5
    Updated Nov 26, 2025
    + more versions
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    Government and Municipalities of Québec (2025). Traffic flow [Dataset]. https://open.canada.ca/data/en/dataset/c77c495a-2a4c-447e-9184-25722289007f
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    geojson, gpkg, shp, wfs, html, pdf, csv, wmsAvailable download formats
    Dataset updated
    Nov 26, 2025
    Dataset provided by
    Government and Municipalities of Québec
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Linear network representing the estimated traffic flows for roads and highways managed by the Ministry of Transport and Sustainable Mobility (MTMD). These flows are obtained using a statistical estimation method applied to data from more than 4,500 collection sites spread over the main roads of Quebec. It includes DJMA (annual average daily flow), DJME (summer average daily flow), DJME (summer average daily flow (June, July, August, September) and DJMH (average daily winter flow (December, January, February, March) as well as other traffic data. It is important to note that these values are calculated for total traffic directions. Interactive map: Some files are accessible by querying an à la carte traffic section with a click (the file links are displayed in the descriptive table that is displayed upon click): • Historical aggregate data (PDF) • Annual reports for permanent sites (PDF and Excel) • Hourly data (hourly average per weekday per month) (Excel) This third party metadata element was translated using an automated translation tool (Amazon Translate).

  13. Leading websites worldwide 2025, by unique visitors

    • statista.com
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    Statista, Leading websites worldwide 2025, by unique visitors [Dataset]. https://www.statista.com/statistics/1201889/most-visited-websites-worldwide-unique-visits/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 2025
    Area covered
    Worldwide
    Description

    In August 2025, Google.com was the most visited website worldwide, attracting approximately 5.66 billion unique monthly visitors. YouTube.com ranked second, with an estimated 2.98 billion unique visitors. Both platforms also held the top positions globally in terms of total website visits.

  14. a

    ADOT 2024 Average Annual Daily Traffic (AADT)

    • azgeo-open-data-agic.hub.arcgis.com
    Updated Sep 23, 2025
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    AZGeo ArcGIS Online (AGO) (2025). ADOT 2024 Average Annual Daily Traffic (AADT) [Dataset]. https://azgeo-open-data-agic.hub.arcgis.com/maps/269b42334ec94589a1c1835ba4d15a3e
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    Dataset updated
    Sep 23, 2025
    Dataset authored and provided by
    AZGeo ArcGIS Online (AGO)
    Area covered
    Description

    The Annual Average Daily Traffic (AADT) for sections of roads for all vehicle types, including single and combination trucks, reported in the 2024 Highway Performance Monitoring System (HPMS) federal report. Annual Average Daily Traffic (AADT) is used to represent vehicle traffic on a typical day of the year and is important for planning purposes, such as defining the federal functional classification of a roadway. The values are calculated using data collected from traffic counter devices, such as Automatic Traffic Recorders (ATR), Weigh In Motion (WIM) devices, and short term counters using tubes. All available traffic data collected throughout the year are then summed and divided by 365 to calculate the annual average daily traffic. Single unit trucks are any trucks that meets the requirements established for the FHWA Truck Classification Method for Categories 4 through 7. Combination unit trucks are any trucks that meets the requirements established for the FHWA Truck Classification Method for Categories 8 through 13. Refer to the Federal Highway Administration website for more information about truck classifications. Reported Extent: State Highway System (i.e. all ADOT-owned roads), National Highway System (NHS), and all federal aid-eligible roads. Federal aid-eligible roads include urban roads classified as minor collectors or above (functional system 1-6) and rural roads classified as major collectors or above (function system 1-5). Roads where ATRs are available, counts are updated annually. For roads where short term counters must be used, traffic counts are collected every three years for all National Highway System (NHS) roads as well as interstates (functional system 1), principal arterials (functional systems 2-3), and sample panel sections. All other federal aid-eligible roads, including minor arterials and collectors, are collected every six years. On one-way roadways and ramps, the AADT represents the single-direction of traffic. For two-way roadways, AADT is reported only on the cardinal direction of the roadway and represents the total traffic for both the cardinal and non-cardinal directions of travel. Note, the cardinal direction refers to the direction of increasing mileposts.

  15. Traffic Volume and Classification in Massachusetts

    • mass.gov
    Updated Sep 18, 2017
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    Massachusetts Department of Transportation (2017). Traffic Volume and Classification in Massachusetts [Dataset]. https://www.mass.gov/traffic-volume-and-classification-in-massachusetts
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    Dataset updated
    Sep 18, 2017
    Dataset authored and provided by
    Massachusetts Department of Transportationhttp://www.massdot.state.ma.us/
    Area covered
    Massachusetts
    Description

    A collection of historic traffic count data and guidelines for how to collect new data for Massachusetts Department of Transportation (MassDOT) projects.

  16. Passant Frequencies Retail Sites Daily Updated

    • hub.tumidata.org
    url
    Updated Jun 4, 2024
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    TUMI (2024). Passant Frequencies Retail Sites Daily Updated [Dataset]. https://hub.tumidata.org/dataset/passant_frequencies_retail_sites_daily_updated_bonn
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    urlAvailable download formats
    Dataset updated
    Jun 4, 2024
    Dataset provided by
    Tumi Inc.http://www.tumi.com/
    Description

    Passant Frequencies Retail Sites Daily Updated
    This dataset falls under the category Individual Transport Traffic Volume.
    It contains the following data: hystreet.com provides daily updated pedestrian frequencies at three inner-city retail locations in Bonn as an OpenService. The data is collected anonymously by laser scanner and measured 24 hours a day, 7 days a week. Pedestrian frequency is an important indicator of the attractiveness of a city centre. Whether retailers, investors, city planners, traffic planners, trade researchers or city centre visitors, a wide range of stakeholders benefit from pedestrian frequency data. The data is also available at https://hystreet.com/.
    This dataset was scouted on 2022-02-17 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: hystreet.com aktuelle Daten von Passantenfrequenzen in Innenstadten - hystreet.com

  17. E-News Express

    • kaggle.com
    zip
    Updated Sep 28, 2023
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    Mariyam Al Shatta (2023). E-News Express [Dataset]. https://www.kaggle.com/datasets/mariyamalshatta/e-news-express
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    zip(925 bytes)Available download formats
    Dataset updated
    Sep 28, 2023
    Authors
    Mariyam Al Shatta
    License

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

    Description

    Business Context

    The advent of e-news, or electronic news, portals has offered us a great opportunity to quickly get updates on the day-to-day events occurring globally. The information on these portals is retrieved electronically from online databases, processed using a variety of software, and then transmitted to the users. There are multiple advantages of transmitting new electronically, like faster access to the content and the ability to utilize different technologies such as audio, graphics, video, and other interactive elements that are either not being used or aren’t common yet in traditional newspapers.

    E-news Express, an online news portal, aims to expand its business by acquiring new subscribers. With every visitor to the website taking certain actions based on their interest, the company plans to analyze these actions to understand user interests and determine how to drive better engagement. The executives at E-news Express are of the opinion that there has been a decline in new monthly subscribers compared to the past year because the current webpage is not designed well enough in terms of the outline & recommended content to keep customers engaged long enough to make a decision to subscribe.

    [Companies often analyze user responses to two variants of a product to decide which of the two variants is more effective. This experimental technique, known as A/B testing, is used to determine whether a new feature attracts users based on a chosen metric.]

    Objective

    The design team of the company has researched and created a new landing page that has a new outline & more relevant content shown compared to the old page. In order to test the effectiveness of the new landing page in gathering new subscribers, the Data Science team conducted an experiment by randomly selecting 100 users and dividing them equally into two groups. The existing landing page was served to the first group (control group) and the new landing page to the second group (treatment group). Data regarding the interaction of users in both groups with the two versions of the landing page was collected. Being a data scientist in E-news Express, you have been asked to explore the data and perform a statistical analysis (at a significance level of 5%) to determine the effectiveness of the new landing page in gathering new subscribers for the news portal by answering the following questions:

    Do the users spend more time on the new landing page than on the existing landing page? Is the conversion rate (the proportion of users who visit the landing page and get converted) for the new page greater than the conversion rate for the old page? Does the converted status depend on the preferred language? Is the time spent on the new page the same for the different language users?

    Data Dictionary

    The data contains information regarding the interaction of users in both groups with the two versions of the landing page.

    user_id - Unique user ID of the person visiting the website group - Whether the user belongs to the first group (control) or the second group (treatment) landing_page - Whether the landing page is new or old time_spent_on_the_page - Time (in minutes) spent by the user on the landing page converted - Whether the user gets converted to a subscriber of the news portal or not language_preferred - Language chosen by the user to view the landing page

  18. Total global visitor traffic to Wikipedia.org 2024

    • statista.com
    Updated Aug 20, 2025
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    Statista (2025). Total global visitor traffic to Wikipedia.org 2024 [Dataset]. https://www.statista.com/statistics/1259907/wikipedia-website-traffic/
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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, close to 4.4 billion unique global visitors had visited Wikipedia.org, slightly down from 4.4 billion visitors since August of the same year. Wikipedia is a free online encyclopedia with articles generated by volunteers worldwide. The platform is hosted by the Wikimedia Foundation.

  19. Monthly website traffic on nykaa.com 2024

    • statista.com
    Updated Feb 15, 2024
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    Statista (2024). Monthly website traffic on nykaa.com 2024 [Dataset]. https://www.statista.com/statistics/1242055/nykaa-website-traffic/
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    Dataset updated
    Feb 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 2023 - Jan 2024
    Area covered
    India
    Description

    In the month of January 2024, the beauty and personal care retailer Nykaa had about **** million website visits. In comparison, the month of December in 2023 clocked over ten million monthly website visits.

  20. ESRI Traffic Service

    • hub-gema-soc.opendata.arcgis.com
    • hub.arcgis.com
    Updated Jan 26, 2018
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    Georgia Emergency Management & Homeland Security Agency (2018). ESRI Traffic Service [Dataset]. https://hub-gema-soc.opendata.arcgis.com/maps/28d6cf5e19084fc3b58db8646968ec2b
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    Dataset updated
    Jan 26, 2018
    Dataset provided by
    Georgia Emergency Management and Homeland Security Agency
    U.S. Department of Homeland Securityhttp://www.dhs.gov/
    Authors
    Georgia Emergency Management & Homeland Security Agency
    Area covered
    Description

    The map layers in this service provide color-coded maps of the traffic conditions you can expect for the present time (the default). The map shows present traffic as a blend of live and typical information. Live speeds are used wherever available and are established from real-time sensor readings. Typical speeds come from a record of average speeds, which are collected over several weeks within the last year or so. Layers also show current incident locations where available. By changing the map time, the service can also provide past and future conditions. Live readings from sensors are saved for 12 hours, so setting the map time back within 12 hours allows you to see a actual recorded traffic speeds, supplemented with typical averages by default. You can choose to turn off the average speeds and see only the recorded live traffic speeds for any time within the 12-hour window. Predictive traffic conditions are shown for any time in the future.The color-coded traffic map layer can be used to represent relative traffic speeds; this is a common type of a map for online services and is used to provide context for routing, navigation, and field operations. A color-coded traffic map can be requested for the current time and any time in the future. A map for a future request might be used for planning purposes.The map also includes dynamic traffic incidents showing the location of accidents, construction, closures, and other issues that could potentially impact the flow of traffic. Traffic incidents are commonly used to provide context for routing, navigation and field operations. Incidents are not features; they cannot be exported and stored for later use or additional analysis.Data sourceEsri’s typical speed records and live and predictive traffic feeds come directly from HERE (www.HERE.com). HERE collects billions of GPS and cell phone probe records per month and, where available, uses sensor and toll-tag data to augment the probe data collected. An advanced algorithm compiles the data and computes accurate speeds. The real-time and predictive traffic data is updated every five minutes through traffic feeds.Data coverageThe service works globally and can be used to visualize traffic speeds and incidents in many countries. Check the service coverage web map to determine availability in your area of interest. Look at the coverage map to learn whether a country currently supports traffic. The support for traffic incidents can be determined by identifying a country. For detailed information on this service, visit the directions and routing documentation and the ArcGIS Help.SymbologyTraffic speeds are displayed as a percentage of free-flow speeds, which is frequently the speed limit or how fast cars tend to travel when unencumbered by other vehicles. The streets are color coded as follows:Green (fast): 85 - 100% of free flow speedsYellow (moderate): 65 - 85%Orange (slow); 45 - 65%Red (stop and go): 0 - 45%To view live traffic only—that is, excluding typical traffic conditions—enable the Live Traffic layer and disable the Traffic layer. (You can find these layers under World/Traffic > [region] > [region] Traffic). To view more comprehensive traffic information that includes live and typical conditions, disable the Live Traffic layer and enable the Traffic layer.ArcGIS Online organization subscriptionImportant Note:The World Traffic map service is available for users with an ArcGIS Online organizational subscription. To access this map service, you'll need to sign in with an account that is a member of an organizational subscription. If you don't have an organizational subscription, you can create a new account and then sign up for a 30-day trial of ArcGIS Online.

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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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Total global visitor traffic to Google.com 2024

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8 scholarly articles cite this dataset (View in Google Scholar)
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.

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