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View Code? Open in Web Editor NEWUsing Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington
Using Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington
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
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