CONTENETS OF THIS FILE ---------------------------------- * Introduction * Softwares Used * Statistics Computed * Useful Resources I used in Completing the Project INTRODUCTION 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 several lines of code to import the data and answer interesting questions about it by computing descriptive statistics. I also write a script that takes in raw input to create an interactive experience in the terminal to present these statistics. SOFTWARES USED Most of my scripting was done on jupyer notebook. I installed python, numpy, and pandas using Anaconda I downloaded the text editor Atom, which i used to create the final .py file I used git bash for windows as my terminal application to view the .py project file to ensure that it runs without errors. STATISTICS COMPUTED I learned about bike share use in Chicago, New York City, and Washington by computing a variety of descriptive statistics. In this project, I wrote several lines of code to provide the following statistics: #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) USEFUL RESOURCES I USED IN COMPLETING PROJECT 1. Project Walkthrough - Explore US Bikeshare - 12.7.2022 - US [Video]. Available at https://vimeo.com/729550011/e9d42ba53c 2. Pandas API reference. Available at https://pandas.pydata.org/docs/reference/index.html 3. Combine two columns of text in pandas dataframe. Available at https://stackoverflow.com/questions/19377969/combine-two-columns-of-text-in-pandas-dataframe 4. Lessons and practices in the Udcatiy - Masterschool Data Analysis Pre-Course Nanodegree Program 5. Recordings from the Pre-course student guide 6. Slack - Data Analysis Pre-Course Channel Resourcs. Including pre_course_project_intro.ipynb file available at https://masterschool-campus.slack.com/archives/C03HKR2D6MU/p1657654420347839 7. __main__ — Top-level code environment. Available at https://docs.python.org/3/library/__main__.html
nsikan-udoma/bikeshare-exploration-project-python
Using Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington
Jupyter Notebook