Project 1: Explore Chicago Bikeshare Data

This is an evaluative test for Udacity's Nanadegree: Artificial Intelligence Programming with Python.

Objective

Bikeshare systems allow that its users renting a bike for a short period of time and a specific price. People can take a bike in a point A and return it to a point B or just return it to the same point if they just want to take a ride. The bikes of this system can be used for many users in a day.

Use Python to explore data related to bikeshare system from Chicago and show through descriptive statistics.

Explaining the project

Using data from Motivate, a bikeshare system provider for various United States' cities, you have to discover the use patterns of bikesharing from Chigago.

Data Set

The provided data refers to the first six months of 2017. The data file chicago.csv contains six main columns:

• Start Time, e.g. 2017-01-01 00:07:57
• End Time, e.g. 2017-01-01 00:20:53
• Trip Duration (in seconds), e.g. 776
• Start Station, e.g. Broadway & Barry Avenue
• End Station, e.g. Sedgwick St & do North Ave
• User Type, e.g. Customer or Subscriber
• Gender, e.g. Female or Male
• Birth Year, e.g. 1996

Tasks

• Task 1: Show the first 20 samples (lines) from the data set
• Task 2: Show the gender of the first 20 samples
• Task 3: Create a function that creates a list with the values of a certain column
• Task 4: Count how many people for each gender
• Task 5: Create a function that counts gender frequency
• Task 6: Show the most popular gender
• Task 7: Show a chart using the previous data
• Task 8: Answer why are there is no gender for all samples
• Task 9: Find the minimum, maximum, average and median travel duration.
• Task 10: Show all stations from data set
• Task 11: Check out if all functions have docstring
• Task 12: Create a function that counts all the column frequency (optional)

Running on your own

All code was written with Python 3.7.1, so, for a correct running, it is recommended to install this one.

1. After Python installed, it is required to install all dependencies from requirements.pip file. If you are using Virtualenv, you need to activate the environment and install from requirements.pip file with the following commands:

$ source YOUR_ENVIRONMENT_DIRECTORY/bin/activate
$ pip install -r requirements.pip

2. Extract the data set from chicago_bikeshare_data.tar.gz file.

3. Run the script with:

$ python chicago_bikeshare_pt.py