Udacity-BikeShare-Project:

Python Project on Pro Data Analysis Track

Basic Data Exploration with pandas on Bikeshare Data

Basic Udacity project using pandas library in Python for their bikeshare data exploration.

Project Overview:

This project focuses on pandas library usage and simple statistics methods to perform a rudimentary analysis on the bikeshare data from three major U.S. cities - Chicago, Washington, and New York City - to display information such as most popular days or most common stations.

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.

Program Details:

The program takes user input for the city (e.g. Chicago), month for which the user wants to view data (e.g. January; also includes an 'all' option), and day for which the user wants to view data (e.g. Monday; also includes an 'all' option).

Upon receiving the user input, it goes ahead and asks the user if they want to view the raw data (5 rows of data initially) or not. Following the input received, the program prints the following details:

Most popular month

Most popular day

Most popular hour

Most popular start station

Most popular end station

Most popular combination of start and end stations

Total trip duration

Average trip duration

Types of users by number

Types of users by gender (if available)

users birth dates (if available)

Finally, the user is prompted with the choice of restarting the program or not.

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:

IDE : PyCharm

Python 3.9 - 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.

Author:

Belal Mohammed Ali

NANO Degree Program from FWD Initiative:

Date of Project Submission:

--Date created: 10/10/2021

--Date last modified: 3/19/2021