Date Created: Tuesday, 07/16/2019

Project Title: Python and While Loop

Project Description:

According to python.org, "Python is a programming language that lets you work more quickly and integrate your systems more effectively." Python provides control flow tools to help with controlling the flow of coding and applying any changes within the workspace environment. There are three control flow statements avalable in Python: (1) if, (2) for and (3) while (https://python.swaroopch.com/control_flow.html). For the Python Bikeshare Project, the while loop was applied to an "indefinite iteration, which is when a loop repeats an unknown number of times and ends when a condition is met" (Udacity Lesson 4: Control Flow, Sub- Lesson on While Loops). Once the user selects their city and month option, and is presented with a set of data applicable to their selection, he or she is provided with the option of viewing five (5) rows of raw data at a time. If the user opts to not have the raw data displayed for him or her, then the next option is offered to either restart the entire process (beginning at selecting city and month) or exiting altoge- ther.

Files Used:

To install Python, the most recent (and past versions) are available via python.org with instructions pro- vided for easy step-by-step instructions. Files used for this particular portion of the Bikeshare Project were three datasets available via .csv file: chicago, new_york_city, and washington. These files were down- loaded directly from Udacity with the links provided in the project sub-lessons, so anyone enrolled in the programming course can access them (Chicago Dataset- https://www.divvybikes.com/system-data; NYC Dataset- https://www.citibikenyc.com/system-data; DC Dataset- https://www.capitalbikeshare.com/system-data).

Additionally, Pandas and NumPy were imported in order to provide an open-sourced library and scientific computing package needed to complete the project. Per pandas.pydata.org, "the easiest way to install pandas is to install it as part of the Anaconda distribution...This is the recommended installation method for most users." As for NumPy, numpy.org "strongly recommend[s] using a scientific Python distribution."

Furthermore, Code Writer allowed for thorough construction and tracking of the applied code, and the use of the Udacity workspace environment was employed for Python scripting and project submission. Code Writer is a free text and code editor app available to download via microsoft.com.

Credits:

Several sources were utilized during the project completion process, mainly the videos and transcripts made available throughout the Python course. Secondary to these Udacity resources were the Student Hub and Know- ledge posts that provided a better understanding of any issues encountered when carrying out each project task, and solutions to said problems. If any answers to questions could not be answered directly from the resources directly provided by Udacity, then articles were read and reviewed via stackoverflow.com.