This Python program allows users to explore and analyze US bikeshare data from three major cities: Chicago, New York City, and Washington. The program computes and displays various statistics on trip durations, popular stations, and user demographics.
Load Data: Load data from CSV files for Chicago, New York City, and Washington. Time Statistics: Calculate and display statistics on the most frequent times of travel. Station Statistics: Calculate and display statistics on the most popular stations and trips. Trip Duration Statistics: Calculate and display statistics on total and average trip durations. User Statistics: Calculate and display statistics on bikeshare users, including user types, gender, and birth years.
The program uses the following CSV files:
- chicago.csv
- new_york_city.csv
- washington.csv These files should be placed in the same directory as the bikeshare.py script.
Hello! Let's explore some US bikeshare data! Would you like to see data for Chicago, New York, or Washington? chicago Which month? all, january, february, march, april, may, or june? all Which day? all, monday, tuesday, wednesday, thursday, friday, saturday, or sunday? all
Calculating The Most Frequent Times of Travel...
Most common month: June Most common day of week: Wednesday Most common start hour: 17
Calculating The Most Popular Stations and Trip...
Most commonly used start station: Streeter Dr & Grand Ave Most commonly used end station: Streeter Dr & Grand Ave Most frequent combination of start station and end station trip: Lake Shore Dr & Monroe St to Streeter Dr & Grand Ave
Calculating Trip Duration...
Total travel time: 2808 Mean travel time: 940.94
Calculating User Stats...
Counts of user types: Subscriber: 238889 Customer: 61110
This is all for now! Have a great day!
Python 3.x Pandas library
This project is part of a Udacity course on Python programming and data analysis.