May 11, 2019

Udacity BikeShare project using python and git

Analyse bikeshare data from Motivate using python along with git to gather data from the files.

Bikeshare files (https://s3.amazonaws.com/video.udacity-data.com/topher/2018/March/5aab379c_bikeshare-2/bikeshare-2.zip) Includes bikeshare.py, a udacity template to assist students with their project. Data files in csv format, chicago.csv, washington.csv, new york city.csv can be accessed in the bikeshare files.

Included all the files related to my work with the Udacity bikeshare project. Some python files, such as city_input.py or user_types.py, show my attempts at gathering and interpreting aspects of the data files. The files with bp, bs, bikeshare, or bike_project show the various ways I tried to put the data gathered from the city files and represent it in a form that could be understood by the user.

The final project_submission takes 3 user inputs: City, Month and Day. After processing the inputs the program returns information related to:

1. trip duration
2. gender stats
3. stations beginning and end
4. popular days and months

I used many examples from pandas and numpy documentation.
I explored questions already asked in Stackoverflow to find examples. Jonathonsoma.com, classnotes on replacing values and strings helped with filling in missing values from washington.csv, on bikeshare lines 121 to 127. towardsdatascience.com, data cleaning with python and pandas:detecting missing values. An article on Oct 5, 2018, helped me explore data and missing values

1. add plots
2. run in html window
3. compare multiple city data