100+ datasets found
  1. Website Traffic Data

    • kaggle.com
    zip
    Updated Nov 8, 2022
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    Sandeep Kumar (2022). Website Traffic Data [Dataset]. https://www.kaggle.com/datasets/sandeepkumar69/website-traffic-data
    Explore at:
    zip(1375 bytes)Available download formats
    Dataset updated
    Nov 8, 2022
    Authors
    Sandeep Kumar
    Description

    DISCLAIMER- I DO NOT OWN THIS DATASET. THIS IS BEING USED ONLY FOR THE SAKE OF THE NOTEBOOK. This dataset contains data about the daily traffic on a website, in a given time period. It has only 2 columns, the first being the 'date' column and the second being the 'number of visits' column. It is a pretty simple dataset, so it wouldn't require much cleaning and preprocessing. There might be few 'nan' values, so you ought to fill/drop them at your convenience. If you like the data, please do upvote as it helps me out. Thank you, and have a great time.

  2. d

    Open Data Website Traffic

    • catalog.data.gov
    • data.lacity.org
    Updated Jun 21, 2025
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    data.lacity.org (2025). Open Data Website Traffic [Dataset]. https://catalog.data.gov/dataset/open-data-website-traffic
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    Dataset updated
    Jun 21, 2025
    Dataset provided by
    data.lacity.org
    Description

    Daily utilization metrics for data.lacity.org and geohub.lacity.org. Updated monthly

  3. Website Traffic

    • kaggle.com
    zip
    Updated Aug 5, 2024
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    AnthonyTherrien (2024). Website Traffic [Dataset]. https://www.kaggle.com/datasets/anthonytherrien/website-traffic
    Explore at:
    zip(65228 bytes)Available download formats
    Dataset updated
    Aug 5, 2024
    Authors
    AnthonyTherrien
    License

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

    Description

    Dataset Overview

    This dataset provides detailed information on website traffic, including page views, session duration, bounce rate, traffic source, time spent on page, previous visits, and conversion rate.

    Dataset Description

    • Page Views: The number of pages viewed during a session.
    • Session Duration: The total duration of the session in minutes.
    • Bounce Rate: The percentage of visitors who navigate away from the site after viewing only one page.
    • Traffic Source: The origin of the traffic (e.g., Organic, Social, Paid).
    • Time on Page: The amount of time spent on the specific page.
    • Previous Visits: The number of previous visits by the same visitor.
    • Conversion Rate: The percentage of visitors who completed a desired action (e.g., making a purchase).

    Data Summary

    • Total Records: 2000
    • Total Features: 7

    Key Features

    1. Page Views: This feature indicates the engagement level of the visitors by showing how many pages they visit during their session.
    2. Session Duration: This feature measures the length of time a visitor stays on the website, which can indicate the quality of the content.
    3. Bounce Rate: A critical metric for understanding user behavior. A high bounce rate may indicate that visitors are not finding what they are looking for.
    4. Traffic Source: Understanding where your traffic comes from can help in optimizing marketing strategies.
    5. Time on Page: This helps in analyzing which pages are retaining visitors' attention the most.
    6. Previous Visits: This can be used to analyze the loyalty of visitors and the effectiveness of retention strategies.
    7. Conversion Rate: The ultimate metric for measuring the effectiveness of the website in achieving its goals.

    Usage

    This dataset can be used for various analyses such as:

    • Identifying key drivers of engagement and conversion.
    • Analyzing the effectiveness of different traffic sources.
    • Understanding user behavior patterns and optimizing the website accordingly.
    • Improving marketing strategies based on traffic source performance.
    • Enhancing user experience by analyzing time spent on different pages.

    Acknowledgments

    This dataset was generated for educational purposes and is not from a real website. It serves as a tool for learning data analysis and machine learning techniques.

  4. a

    TMS daily traffic counts CSV

    • hub.arcgis.com
    • catalogue.data.govt.nz
    • +1more
    Updated Aug 30, 2020
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    Waka Kotahi (2020). TMS daily traffic counts CSV [Dataset]. https://hub.arcgis.com/datasets/9cb86b342f2d4f228067a7437a7f7313
    Explore at:
    Dataset updated
    Aug 30, 2020
    Dataset authored and provided by
    Waka Kotahi
    License

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

    Description

    You can also access an API version of this dataset.

    TMS

    (traffic monitoring system) daily-updated traffic counts API

    Important note: due to the size of this dataset, you won't be able to open it fully in Excel. Use notepad / R / any software package which can open more than a million rows.

    Data reuse caveats: as per license.

    Data quality

    statement: please read the accompanying user manual, explaining:

    how

     this data is collected identification 
    
     of count stations traffic 
    
     monitoring technology monitoring 
    
     hierarchy and conventions typical 
    
     survey specification data 
    
     calculation TMS 
    
     operation. 
    

    Traffic

    monitoring for state highways: user manual

    [PDF 465 KB]

    The data is at daily granularity. However, the actual update

    frequency of the data depends on the contract the site falls within. For telemetry

    sites it's once a week on a Wednesday. Some regional sites are fortnightly, and

    some monthly or quarterly. Some are only 4 weeks a year, with timing depending

    on contractors’ programme of work.

    Data quality caveats: you must use this data in

    conjunction with the user manual and the following caveats.

    The

     road sensors used in data collection are subject to both technical errors and 
    
     environmental interference.Data 
    
     is compiled from a variety of sources. Accuracy may vary and the data 
    
     should only be used as a guide.As 
    
     not all road sections are monitored, a direct calculation of Vehicle 
    
     Kilometres Travelled (VKT) for a region is not possible.Data 
    
     is sourced from Waka Kotahi New Zealand Transport Agency TMS data.For 
    
     sites that use dual loops classification is by length. Vehicles with a length of less than 5.5m are 
    
     classed as light vehicles. Vehicles over 11m long are classed as heavy 
    
     vehicles. Vehicles between 5.5 and 11m are split 50:50 into light and 
    
     heavy.In September 2022, the National Telemetry contract was handed to a new contractor. During the handover process, due to some missing documents and aged technology, 40 of the 96 national telemetry traffic count sites went offline. Current contractor has continued to upload data from all active sites and have gradually worked to bring most offline sites back online. Please note and account for possible gaps in data from National Telemetry Sites. 
    

    The NZTA Vehicle

    Classification Relationships diagram below shows the length classification (typically dual loops) and axle classification (typically pneumatic tube counts),

    and how these map to the Monetised benefits and costs manual, table A37,

    page 254.

    Monetised benefits and costs manual [PDF 9 MB]

    For the full TMS

    classification schema see Appendix A of the traffic counting manual vehicle

    classification scheme (NZTA 2011), below.

    Traffic monitoring for state highways: user manual [PDF 465 KB]

    State highway traffic monitoring (map)

    State highway traffic monitoring sites

  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/
    Explore at:
    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. Data from: Annual Average Daily Traffic

    • gisdata-caltrans.opendata.arcgis.com
    • data.ca.gov
    • +3more
    Updated Feb 27, 2026
    + more versions
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    California_Department_of_Transportation (2026). Annual Average Daily Traffic [Dataset]. https://gisdata-caltrans.opendata.arcgis.com/datasets/d8833219913c44358f2a9a71bda57f76
    Explore at:
    Dataset updated
    Feb 27, 2026
    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

  7. Average Annual Daily Traffic (AADT)

    • caliper.com
    cdf, dwg, dxf, gdb +9
    Updated Sep 23, 2025
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    Caliper Corporation (2025). Average Annual Daily Traffic (AADT) [Dataset]. https://www.caliper.com/mapping-software-data/aadt-traffic-count-data.htm
    Explore at:
    postgresql, postgis, sdo, geojson, shp, cdf, kml, kmz, dxf, dwg, ntf, sql server mssql, gdbAvailable download formats
    Dataset updated
    Sep 23, 2025
    Dataset authored and provided by
    Caliper Corporationhttp://www.caliper.com/
    License

    https://www.caliper.com/license/maptitude-license-agreement.htmhttps://www.caliper.com/license/maptitude-license-agreement.htm

    Time period covered
    2025
    Area covered
    United States
    Description

    Average Annual Daily Traffic data for use with GIS mapping software, databases, and web applications are from Caliper Corporation and contain data on the total volume of vehicle traffic on a highway or road for a year divided by 365 days.

  8. Annual Average Daily Traffic TDA

    • gis-fdot.opendata.arcgis.com
    • mapdirect-fdep.opendata.arcgis.com
    • +1more
    Updated Jul 21, 2017
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    Florida Department of Transportation (2017). Annual Average Daily Traffic TDA [Dataset]. https://gis-fdot.opendata.arcgis.com/datasets/fdot::annual-average-daily-traffic-tda/about
    Explore at:
    Dataset updated
    Jul 21, 2017
    Dataset authored and provided by
    Florida Department of Transportationhttps://www.fdot.gov/
    Area covered
    Description

    The FDOT Annual Average Daily Traffic feature class provides spatial information on Annual Average Daily Traffic section breaks for the state of Florida. In addition, it provides affiliated traffic information like KFCTR, DFCTR and TFCTR among others. This dataset is maintained by the Transportation Data & Analytics office (TDA). The source spatial data for this hosted feature layer was created on: 02/28/2026.Download Data: Enter Guest as Username to download the source shapefile from here: https://ftp.fdot.gov/file/d/FTP/FDOT/co/planning/transtat/gis/shapefiles/aadt.zip

  9. Traffic Volume and Classification in Massachusetts

    • mass.gov
    Updated Dec 17, 2021
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    Massachusetts Department of Transportation (2021). Traffic Volume and Classification in Massachusetts [Dataset]. https://www.mass.gov/traffic-volume-and-classification-in-massachusetts
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    Dataset updated
    Dec 17, 2021
    Dataset authored and provided by
    Massachusetts Department of Transportationhttp://mass.gov/orgs/massachusetts-department-of-transportation
    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.

  10. s

    Traffic Volumes from SCATS Traffic Management System Jan-Jun 2024 DCC

    • data.smartdublin.ie
    Updated Jun 30, 2024
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    (2024). Traffic Volumes from SCATS Traffic Management System Jan-Jun 2024 DCC [Dataset]. https://data.smartdublin.ie/dataset/dcc-scats-detector-volume-jan-jun-2024
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    Dataset updated
    Jun 30, 2024
    License

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

    Description

    Traffic volumes data across Dublin City from the SCATS traffic management system. The Sydney Coordinated Adaptive Traffic System (SCATS) is an intelligent transportation system used to manage timing of signal phases at traffic signals. SCATS uses sensors at each traffic signal to detect vehicle presence in each lane and pedestrians waiting to cross at the local site. The vehicle sensors are generally inductive loops installed within the road. 3 resources are provided: SCATS Traffic Volumes Data (Monthly) Contained in this report are traffic counts taken from the SCATS traffic detectors located at junctions. The primary function for these traffic detectors is for traffic signal control. Such devices can also count general traffic volumes at defined locations on approach to a junction. These devices are set at specific locations on approaches to the junction but may not be on all approaches to a junction. As there are multiple junctions on any one route, it could be expected that a vehicle would be counted multiple times as it progress along the route. Thus the traffic volume counts here are best used to represent trends in vehicle movement by selecting a specific junction on the route which best represents the overall traffic flows. Information provided: End Time: time that one hour count period finishes. Region: location of the detector site (e.g. North City, West City, etc). Site: this can be matched with the SCATS Sites file to show location Detector: the detectors/ sensors at each site are numbered Sum volume: total traffic volumes in preceding hour Avg volume: average traffic volumes per 5 minute interval in preceding hour All Dates Traffic Volumes Data This file contains daily totals of traffic flow at each site location. SCATS Site Location Data Contained in this report, the location data for the SCATS sites is provided. The meta data provided includes the following; Site id – This is a unique identifier for each junction on SCATS Site description( CAP) – Descriptive location of the junction containing street name(s) intersecting streets Site description (lower) - – Descriptive location of the junction containing street name(s) intersecting streets Region – The area of the city, adjoining local authority, region that the site is located LAT/LONG – Coordinates Disclaimer: the location files are regularly updated to represent the locations of SCATS sites under the control of Dublin City Council. However site accuracy is not absolute. Information for LAT/LONG and region may not be available for all sites contained. It is at the discretion of the user to link the files for analysis and to create further data. Furthermore, detector communication issues or faulty detectors could also result in an inaccurate result for a given period, so values should not be taken as absolute but can be used to indicate trends.

  11. t

    Traffic Count Segments

    • data-academy.tempe.gov
    • open.tempe.gov
    • +8more
    Updated Jul 27, 2020
    + more versions
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    City of Tempe (2020). Traffic Count Segments [Dataset]. https://data-academy.tempe.gov/datasets/traffic-count-segments
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    Dataset updated
    Jul 27, 2020
    Dataset authored and provided by
    City of Tempe
    License

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

    Area covered
    Description

    This dataset consists of 24-hour traffic volumes which are collected by the City of Tempe high (arterial) and low (collector) volume streets. Data located in the tabular section shares with its users total volume of vehicles passing through the intersection selected along with the direction of flow.Historical data from this feature layer extends from 2016 to present day.Contact: Sue TaaffeContact E-Mail: sue_taaffe@tempe.govContact Phone: 480-350-8663Link to embedded web map:http://www.tempe.gov/city-hall/public-works/transportation/traffic-countsLink to site containing historical traffic counts by node: https://gis.tempe.gov/trafficcounts/Folders/Data Source: SQL Server/ArcGIS ServerData Source Type: GeospatialPreparation Method: N/APublish Frequency: As information changesPublish Method: AutomaticData Dictionary

  12. d

    Website Analytics

    • catalog.data.gov
    • data.brla.gov
    • +1more
    Updated Mar 22, 2026
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    data.brla.gov (2026). Website Analytics [Dataset]. https://catalog.data.gov/dataset/website-analytics-89ba5
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    Dataset updated
    Mar 22, 2026
    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.

  13. A

    Traffic-Related Data

    • data.boston.gov
    html, pdf
    Updated Feb 4, 2026
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    Boston Transportation Department (2026). Traffic-Related Data [Dataset]. https://data.boston.gov/dataset/traffic-related-data
    Explore at:
    html, pdfAvailable download formats
    Dataset updated
    Feb 4, 2026
    Dataset authored and provided by
    Boston Transportation Department
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    Traffic-related data collected by the Boston Transportation Department, as well as other City departments and State agencies. Various types of counts: Turning Movement Counts, Automated Traffic Recordings, Pedestrian Counts, Delay Studies, and Gap Studies.

    ~_Turning Movement Counts (TMC)_ present the number of motor vehicles, pedestrians, and cyclists passing through the particular intersection. Specific movements and crossings are recorded for all street approaches involved with the intersection. This data is used in traffic signal retiming programs and for signal requests. Counts are typically conducted for 2-, 4-, 11-, and 12-Hr periods.

    ~_Automated Traffic Recordings (ATR)_ record the volume of motor vehicles traveling along a particular road, measures of travel speeds, and approximations of the class of the vehicles (motorcycle, 2-axle, large box truck, bus, etc). This type of count is conducted only along a street link/corridor, to gather data between two intersections or points of interest. This data is used in travel studies, as well as to review concerns about street use, speeding, and capacity. Counts are typically conducted for 12- & 24-Hr periods.

    ~_Pedestrian Counts (PED)_ record the volume of individual persons crossing a given street, whether at an existing intersection or a mid-block crossing. This data is used to review concerns about crossing safety, as well as for access analysis for points of interest. Counts are typically conducted for 2-, 4-, 11-, and 12-Hr periods.

    ~_Delay Studies (DEL)_ measure the delay experienced by motor vehicles due to the effects of congestion. Counts are typically conducted for a 1-Hr period at a given intersection or point of intersecting vehicular traffic.

    ~_Gap Studies (GAP)_ record the number of gaps which are typically present between groups of vehicles traveling through an intersection or past a point on a street. This data is used to assess opportunities for pedestrians to cross the street and for analyses on vehicular “platooning”. Counts are typically conducted for a specific 1-Hr period at a single point of crossing.

  14. d

    Click Global Data | Web Traffic Data + Transaction Data | Consumer and B2B...

    • datarade.ai
    .csv
    Updated Mar 13, 2025
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    Consumer Edge (2025). Click Global Data | Web Traffic Data + Transaction Data | Consumer and B2B Shopper Insights | 59 Countries, 3-Day Lag, Daily Delivery [Dataset]. https://datarade.ai/data-products/click-global-data-web-traffic-data-transaction-data-con-consumer-edge
    Explore at:
    .csvAvailable download formats
    Dataset updated
    Mar 13, 2025
    Dataset authored and provided by
    Consumer Edge
    Area covered
    Bermuda, Montserrat, Bosnia and Herzegovina, Marshall Islands, Congo, El Salvador, South Africa, Sri Lanka, Finland, Nauru
    Description

    Click Web Traffic Combined with Transaction Data: A New Dimension of Shopper Insights

    Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. Click enhances the unparalleled accuracy of CE Transact by allowing investors to delve deeper and browse further into global online web traffic for CE Transact companies and more. Leverage the unique fusion of web traffic and transaction datasets to understand the addressable market and understand spending behavior on consumer and B2B websites. See the impact of changes in marketing spend, search engine algorithms, and social media awareness on visits to a merchant’s website, and discover the extent to which product mix and pricing drive or hinder visits and dwell time. Plus, Click uncovers a more global view of traffic trends in geographies not covered by Transact. Doubleclick into better forecasting, with Click.

    Consumer Edge’s Click is available in machine-readable file delivery and enables: • Comprehensive Global Coverage: Insights across 620+ brands and 59 countries, including key markets in the US, Europe, Asia, and Latin America. • Integrated Data Ecosystem: Click seamlessly maps web traffic data to CE entities and stock tickers, enabling a unified view across various business intelligence tools. • Near Real-Time Insights: Daily data delivery with a 5-day lag ensures timely, actionable insights for agile decision-making. • Enhanced Forecasting Capabilities: Combining web traffic indicators with transaction data helps identify patterns and predict revenue performance.

    Use Case: Analyze Year Over Year Growth Rate by Region

    Problem A public investor wants to understand how a company’s year-over-year growth differs by region.

    Solution The firm leveraged Consumer Edge Click data to: • Gain visibility into key metrics like views, bounce rate, visits, and addressable spend • Analyze year-over-year growth rates for a time period • Breakout data by geographic region to see growth trends

    Metrics Include: • Spend • Items • Volume • Transactions • Price Per Volume

    Inquire about a Click subscription to perform more complex, near real-time analyses on public tickers and private brands as well as for industries beyond CPG like: • Monitor web traffic as a leading indicator of stock performance and consumer demand • Analyze customer interest and sentiment at the brand and sub-brand levels

    Consumer Edge offers a variety of datasets covering the US, Europe (UK, Austria, France, Germany, Italy, Spain), and across the globe, with subscription options serving a wide range of business needs.

    Consumer Edge is the Leader in Data-Driven Insights Focused on the Global Consumer

  15. a

    Traffic Counts Sites and Volume Data

    • l-a-mapping-services-lennoxaddington.hub.arcgis.com
    Updated Apr 2, 2019
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    County of Lennox & Addington (2019). Traffic Counts Sites and Volume Data [Dataset]. https://l-a-mapping-services-lennoxaddington.hub.arcgis.com/datasets/traffic-counts-sites-and-volume-data
    Explore at:
    Dataset updated
    Apr 2, 2019
    Dataset authored and provided by
    County of Lennox & Addington
    Description

    TERMS OF USE 1. Restriction on the use of Material on this websiteUsage and/or downloading this data indicates Your acceptance of the terms and conditions below.The data here controlled and operated by the Corporation of the County of Lennox and Addington (referred to the “County” herein) and is protected by copyright. No part of the information herein may be sold, copied, distributed, or transmitted in any form without the prior written consent of the County. All rights reserved. Copyright 2018 by the Corporation of the County of Lennox and Addington.2. DisclaimerThe County makes no representation, warranty or guarantee as to the content, accuracy, currency or completeness of any of the information provided on this website. The County explicitly disclaims any representations, warranties and guarantees, including, without limitation, the implied warranties of merchantability and fitness for a particular purpose.3. Limitation of LiabilityThe County is not responsible for any special, indirect, incidental or consequential damages that may arise from the use of or the inability to use, any web pages and/or the materials contained on the web page whether the materials are provided by the County or by a third party. Without limiting the generality of the foregoing, the County assumes no responsibility whatsoever for: any errors omissions, or inaccuracies in the information provided, regardless of how caused; or any decision made or action taken or not taken by the reader or other third party in reliance upon any information or data furnished on any web page.The Data is provided "as is" without warranty or any representation of accuracy, timeliness or completeness. The burden for determining accuracy, completeness, timeliness, merchantability and fitness for or the appropriateness for use rests solely on the requester. Lennox and Addington County makes no warranties, express or implied, as to the use of the Data. There are no implied warranties of merchantability or fitness for a particular purpose. The requester acknowledges and accepts the limitations of the Data, including the fact that the Data is dynamic and is in a constant state of maintenance, corrections and update.

  16. s

    Data from: Traffic Counts

    • dataworks.siouxfalls.gov
    • catalog.data.gov
    Updated Feb 13, 2020
    + more versions
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    City of Sioux Falls GIS (2020). Traffic Counts [Dataset]. https://dataworks.siouxfalls.gov/datasets/traffic-counts/about
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    Dataset updated
    Feb 13, 2020
    Dataset authored and provided by
    City of Sioux Falls GIS
    License

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

    Area covered
    Description

    Feature layer containing authoritative traffic count points for Sioux Falls, South Dakota.The traffic counts listed are 24-hour, weekday, two-directional counts. Traffic counts are normally collected during the summer months, but may be taken any season, as weather permits. The traffic counts are factored by the day of the week as well as by the month of the year to become an Average Annual Daily Total (AADT). Traffic volumes (i.e. count data) can fluctuate depending on the month, week, day of collection; the weather, type of road surface, nearby construction, etc. All of the historical data should be averaged to reflect the "normal" traffic count. More specific count data (time, date, hourly volume) can be obtained from the Sioux Falls Engineering Division at 367-8601.

  17. a

    Pasadena Traffic Count Website

    • hub.arcgis.com
    • data.cityofpasadena.net
    Updated Jan 1, 2006
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    CityOfPasadenaCAGIS (2006). Pasadena Traffic Count Website [Dataset]. https://hub.arcgis.com/documents/eaaffc1269994f0e8966e2024647cc56
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    Dataset updated
    Jan 1, 2006
    Dataset authored and provided by
    CityOfPasadenaCAGIS
    Area covered
    Pasadena
    Description

    The City of Pasadena has a longstanding interest in protecting neighborhoods from cut-through traffic and speeding vehicles. As early as the 1980’s, the City authorized installation of speed humps to slow traffic in residential areas. Today, almost 400 of these traffic management devices have been installed along with many other traffic management measures.Traffic counts are conducted throughout the City of Pasadena either through resident requests, development projects, specific and general plans, or engineering studies. The Department of Transportation has collected these traffic counts and made them available to the public through the use of a Traffic Count Database.

  18. d

    Traffic Count Segments

    • catalog.data.gov
    • open.tempe.gov
    • +7more
    Updated May 17, 2024
    + more versions
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    City of Tempe (2024). Traffic Count Segments [Dataset]. https://catalog.data.gov/dataset/traffic-count-segments-7aff2
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    Dataset updated
    May 17, 2024
    Dataset provided by
    City of Tempe
    Description

    This web map displays traffic count data provided by the City of Tempe Transportation Department. Data are symbolized by line thickness per each street section. Each segment's popup contains a weblink to historical traffic count data that are provided by the City of Tempe for public use.

  19. Annual Average Daily Traffic - 2021

    • gis-idot.opendata.arcgis.com
    Updated Apr 13, 2022
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    Illinois Department of Transportation (2022). Annual Average Daily Traffic - 2021 [Dataset]. https://gis-idot.opendata.arcgis.com/maps/IDOT::annual-average-daily-traffic-2021/explore
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    Dataset updated
    Apr 13, 2022
    Dataset authored and provided by
    Illinois Department of Transportationhttp://www.dot.il.gov/
    License

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

    Area covered
    Description

    Annual Average Daily Traffic volumes (AADT) is a product of IDOT’s Traffic Count Program. Counts from this program range in duration from data continuously recorded at permanent count stations to thousands of coverage count locations that are counted for a 24-hour period throughout the year. More information about IDOT’s Traffic Count Program can be found at the Illinois Travel Statistics site.

  20. g

    Traffic Count Segments | gimi9.com

    • gimi9.com
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    Traffic Count Segments | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_traffic-count-segments-4a2ab/
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    License

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

    Description

    🇺🇸 미국 English This dataset consists of 24-hour traffic volumes which are collected by the City of Tempe high (arterial) and low (collector) volume streets. Data located in the tabular section shares with its users total volume of vehicles passing through the intersection selected along with the direction of flow.Historical data from this feature layer extends from 2016 to present day.Contact: Sue TaaffeContact E-Mail: sue_taaffe@tempe.govContact Phone: 480-350-8663Link to embedded web map:http://www.tempe.gov/city-hall/public-works/transportation/traffic-countsLink to site containing historical traffic counts by node: https://gis.tempe.gov/trafficcounts/Folders/Data Source: SQL Server/ArcGIS ServerData Source Type: GeospatialPreparation Method: N/APublish Frequency: As information changes

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Sandeep Kumar (2022). Website Traffic Data [Dataset]. https://www.kaggle.com/datasets/sandeepkumar69/website-traffic-data
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Website Traffic Data

The daily traffic on a website.

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zip(1375 bytes)Available download formats
Dataset updated
Nov 8, 2022
Authors
Sandeep Kumar
Description

DISCLAIMER- I DO NOT OWN THIS DATASET. THIS IS BEING USED ONLY FOR THE SAKE OF THE NOTEBOOK. This dataset contains data about the daily traffic on a website, in a given time period. It has only 2 columns, the first being the 'date' column and the second being the 'number of visits' column. It is a pretty simple dataset, so it wouldn't require much cleaning and preprocessing. There might be few 'nan' values, so you ought to fill/drop them at your convenience. If you like the data, please do upvote as it helps me out. Thank you, and have a great time.

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