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Data Analyst Nanodegree Project (Visualization). This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area. The project starts reading the dataset, preprocessing, and making more than 15 visualization and insights and with more than 5 polished visualizations.

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Data Visualization

Ford GoBike System Data Exploration

by Akubagi Gebremariam

Dataset

This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area.

Summary of Findings

Majority (90.5%) of the user type are subscribers. Customer are only 9.5% of total user types

Gender wise distribution bike service usage.

  • 74.6% are Men
  • 23.3% are Feamle
  • 2.08% are Other

Only 9.9% of the total bikes are used for all kind of trips.

The most widely used start and end station name

  • Market St at 10th St is the most widely used start station name
  • San Francisco Caltrain Station 2 (Townsend St at 4th St) is the most widely used end start station name

The start and end station name which is least used

  • 16th St Depot is least used start station name
  • Willow St at vine St is least used end station name

The most bike service hour usage is 17 (rush time) and the second most hour is 8(2:00 AM). These hours are time for moving to home from works places or offices and entering to work places respectively.

Most of the user types are subscribers and Thursday is the day in which both user type are widely using bike services.

Some interesting observation between the most interested catagorical varibles

  • Most of the subscribers are male
  • Most males use bike service on Thursday and Tuesday
  • Most females use bike service on same day as males
  • Thursday is the day mostly used for bike usage by the Subscribers

Some interesting observation about duration usage

  • Duration usage on weekends is higher comparing to weekdays
  • Duration usage by Customers is higher than Subscribers
  • Sunday is the day which users take more duration in the bike usage.

Key Insights for Presentation

I start trying to introduce the distribution user type, duration usage and date analysis to identify the insights with the help of ploting functions. Relationship among the most interested between the qualitative and quantitative data is conducted. So the type of user, duration usage, hours and days has an impact on the overall bike service usage in the fordGo Bike sytem.

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Data Analyst Nanodegree Project (Visualization). This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area. The project starts reading the dataset, preprocessing, and making more than 15 visualization and insights and with more than 5 polished visualizations.

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