Explore-US-Bikeshare-Data

In this project, I made use of Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. I wrote code to import the data and answered interesting questions about it by computing descriptive statistics. I also wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.

What Software is Needed?

To complete this project, the following software requirements apply:

• You should have Python 3, NumPy, and pandas installed using Anaconda
• A text editor, like Sublime or Atom.
• A terminal application (Terminal on Mac and Linux or Cygwin on Windows).

Running the program

You can input 'python bikeshare.py' on your terminal to run this program. I use Anaconda's command prompt on a Windows 10 machine.

Statistics Computed

You will learn about bike share use in Chicago, New York City, and Washington by computing a variety of descriptive statistics. In this project, you'll write code to provide the following information:

#1 Popular times of travel (i.e., occurs most often in the start time)

• most common month
• most common day of week
• most common hour of day #2 Popular stations and trip
• most common start station
• most common end station
• most common trip from start to end (i.e., most frequent combination of start station and end station #3 Trip duration
• total travel time
• average travel time #4 User info
• counts of each user type
• counts of each gender (only available for NYC and Chicago)
• earliest, most recent, most common year of birth (only available for NYC and Chicago)

Requirements

• Language: Python 3.6 or above
• Libraries: pandas, numpy, time

Project Data

• chicago.csv - Stored in the data folder, the chicago.csv file is the dataset containing all bikeshare information for the city of Chicago provided by Udacity.

• new_york_city.csv - Dataset containing all bikeshare information for the city of New York provided by Udacity.

• washington.csv - Dataset containing all bikeshare information for the city of Washington provided by Udacity. Note: This does not include the 'Gender' or 'Birth Year' data.

Built with

• Python 3.6.6 - The language used to develop this.
• pandas - One of the libraries used for this.
• numpy - One of the libraries used for this.
• time - One of the libraries used for this.