2/6/2021
Explore US Bikeshare Data
This project is a part of the course on Udacity - Programming for Data Science with Python. It contains a filtered Bikeshare data provided by means of answers to the relevant questions about it.
In order to run the program, the following files are needed to be put in one folder:
- chicago.csv;
- new_york_city.csv;
- washington.csv
The script answers the following questions about the Bikeshare data:
The most frequent times of travel:
- What is the most popular month?
- What is the most popular day of week?
- What is the most popular start hour?
Popular stations, trip and total duration:
- What is the most popular start station?
- What it the most popular end station?
- What is the most popular trip?
- What is the total trip duration?
- What is the average trip duration?
User information:
- What are the counts of each user type?
User information (only available for NYC and Chicago):
- What are the counts of gender?
- What are the earliest (oldest person), most recent (youngest person), and most popular birth years?
In order to complete the project, I used my knowledge gained during the course Programming for Data Science with Python on Udacity. If I got stuck some place, the source(s) below helped me:
- Python documentation
- Stackoverflow
- Pandas Documentation
- W3Schools Online Web Tutorials
I used Atom editor to write the code.