Analysis of ‘London bike sharing dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/hmavrodiev/london-bike-sharing-dataset on 12 November 2021.

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

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Context

The purpose is to try predict the future bike shares.

Content

The data is acquired from 3 sources:
- Https://cycling.data.tfl.gov.uk/ 'Contains OS data © Crown copyright and database rights 2016' and Geomni UK Map data © and database rights [2019] 'Powered by TfL Open Data'
- freemeteo.com - weather data
- https://www.gov.uk/bank-holidays
From 1/1/2015 to 31/12/2016

The data from cycling dataset is grouped by "Start time", this represent the count of new bike shares grouped by hour. The long duration shares are not taken in the count.

Metadata:

"timestamp" - timestamp field for grouping the data
"cnt" - the count of a new bike shares
"t1" - real temperature in C
"t2" - temperature in C "feels like"
"hum" - humidity in percentage
"wind_speed" - wind speed in km/h
"weather_code" - category of the weather
"is_holiday" - boolean field - 1 holiday / 0 non holiday
"is_weekend" - boolean field - 1 if the day is weekend
"season" - category field meteorological seasons: 0-spring ; 1-summer; 2-fall; 3-winter.

"weathe_code" category description:
1 = Clear ; mostly clear but have some values with haze/fog/patches of fog/ fog in vicinity
2 = scattered clouds / few clouds
3 = Broken clouds
4 = Cloudy
7 = Rain/ light Rain shower/ Light rain
10 = rain with thunderstorm
26 = snowfall
94 = Freezing Fog

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

This data contains the number of hires of London's Santander Cycle Hire Scheme from 2011 to present. Data includes start and stop timestamps, station names and ride duration. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

In 2022, the number of bike-share users in the United Kingdom amounted to nearly 1.6 million. According to Statista Market Insights, the number of users is projected to increase by about 21 percent in 2027.

Project: Providing cycling information for visitors/tourists. Viewers will be able to have general sense to know where they should start.The biggest problem I had was creating shaepfile with less than 1000 feature, as arcgis doesn't take any shape file has more than 1000 features.The one of many regret is, arcgis deploy from arcMap wasn't working properly all the time, which stopped me from creating a more sophisticated map.Also maybe after graduation, I will be able to look at API of UK.gov to make many of these maps available online.API data was available and was able to make Tableau project to create location of each bikeshare locations, but wasn't able to find clean way to introduce the project into ArcGIS.Datasets:[DATASET1] - Central London Boundary Shapefile[DATASET2] - England Load ShapefileThese two datasets were intersected to get only load data on Central London Boundary. Then this new data was exported to shapefile, which was uploaded to WebApp later on.[DATASET3] - Cycle infrastructure data was only chosen for the Central London.[DATASET4] - temperature data of Summer 2006 heatwaveSources:Thumbnail: http://gudphoto.com/bikenyc/wp-content/uploads/2012/04/20120418-DSCF0792.jpg0. Introductionhttps://en.wikipedia.org/wiki/Big_Benhttps://www.londoneye.com/https://en.wikipedia.org/wiki/London_Eyehttps://en.wikipedia.org/wiki/Buckingham_Palacehttps://en.wikipedia.org/wiki/Tower_of_Londonhttps://en.wikipedia.org/wiki/Tower_Bridge1. London Roadmap[Combined - Spatial Analysis][DATASET1] - Central London Boundary Shapefilehttps://data.london.gov.uk/dataset/statistical-gis-boundary-files-london[DATASET2] - England Load Shapefilehttps://mapcruzin.com/free-england-arcgis-maps-shapefiles.htm2. London Detail information[DATASET3]https://data.gov.uk/dataset/5a0e003a-829a-4e51-95cf-8157cb47fd89/tree-preservation-ordershttps://keyassets.timeincuk.net/inspirewp/live/wp-content/uploads/sites/2/2017/06/security-barriers-blackfriars-bridge-picture-credit-evo-lucas-twitter-2-630x420.jpeg3. Weatherhttps://www.telegraph.co.uk/content/dam/news/2016/06/14/100562956_People_ride_bikes_in_the_rain_in_Westminster_London_PRESS_ASSOCIATION_Photo_Picture_da_trans_NvBQzQNjv4BqpiVx42joSuAkZ0bE9ijUnGH28ZiNHzwg9svuZLxrn1U.jpg?imwidth=450https://weather.com/weather/tenday/l/UKXX0085:1:UK[DATASET4] - heatmap data of summer 2006https://www.europeandataportal.eu/data/en/dataset/london-s-urban-heat-island4. Air pollutionhttps://www.londonair.org.uk/LondonAir/nowcast.aspx5. Accidentshttps://tfl.gov.uk/traffic/status/https://www.telegraph.co.uk/news/2018/08/14/car-crashes-barrier-outside-parliament-armed-police-surround/https://en.wikipedia.org/wiki/2017_London_Bridge_attack5. Cycle Hirehttp://mappinglondon.co.uk/2014/cycle-hire-journeys-the-central-london-grid/bikes.oobrien.com/city/london/#zoom=12&lon=-0.1587&lat=51.5141https://api.tfl.gov.uk/bikepointhttps://media.timeout.com/images/105191661/image.jpg

https://media.data.world/OSkqtJC1TPapfFJMtaGp_Screen%20Shot%202018-06-21%20at%2012.19.45%20pm.png" alt="Screen Shot 2018-06-21 at 12.19.45 pm.png">

About this Dataset

• DATA SOURCE: Transport for London
• DESIGNER: Sophie Sparks
• INTERACTIVE VERSION: Tableau Public

NOTES

1. To connect to Exasol data source (50M+ records from 2012-2018) use the Tableau Data Source here.
2. Details for connecting to Exasol can be found in this blog post.
3. If you have trouble downloading the CSV from data.world, you can download it here instead.
4. The CSV only contains data for 2017.

Objectives

• What works and what doesn't work with this chart?
• How can you make it better?
• Post your alternative on the discussions page.

Dataset

This dataset was created by Mohamed Youssef

Contents

In 2022, 27 percent of the bike sharing market in the United Kingdom (U.K.) was held by the Estonian mobility company Bolt. Bolt, Lime and Voi, the top three brands in the bike sharing market alone, account for 60 percent bike sharing market in the UK.

The average duration for a Transport for London bicycle hire fluctuated between 17 to 22 minutes in 2019, with users generally spending more time on their bike in the summer months. July 2016 and July 2018 saw the most time spent on a single ride, at 23 minutes.

Estimated change in the London bike-sharing scheme.

The number of bicycles sold in Great Britain reached over two million in 2022. Sales had been decreasing between 2014 and 2018, dropping to 2.2 million that year. From 2018 sales began rising again, peaking at 3.3 million in 2021.

The end of the pandemic bike boom? As in many countries across Europe, the United Kingdom experienced an increased demand for bicycles during the COVID-19 pandemic, leading to the spike in demand for new bicycles in 2021. As the pandemic waned in 2022, bicycle traffic also began decreasing across the country. This decrease was, however, not nearly as strong as the decrease in bicycle sales. Next to changes in exercise and travel behavior in 2022, supply chain issues, which could lead to months-long waits for the delivery of bicycles, also impacted sales. Bike-sharing increasingly popular Bike sharing schemes have been spreading to cities across the UK in recent years, no longer making ownership of a bike a prerequisite to cycling. Relative to its population size, London has one of the largest shared bike fleets in the country, which is dominated by station-based bicycles. Manchester, however, has a particularly large free-floating shared bike fleet, with 35 bikes per 10,000 inhabitants. By 2027, the revenue from the bike sharing sector in the UK is expected to reach 78 million euros, a 50 percent increase compared to 2022.

The United Kingdom E-bike Market is segmented by Propulsion Type (Pedal Assisted, Speed Pedelec, Throttle Assisted), by Application Type (Cargo/Utility, City/Urban, Trekking) and by Battery Type (Lead Acid Battery, Lithium-ion Battery, Others). Market Volume in Units and Market Value in USD is presented. Key data points observed include the number of e-bike sold by propulsion, application type for each propulsion type; and, battery type for each propulsion type.