https://github.com/marcosvbras/udacity-nd109-project-one
Data Exploitation project to Udacity Nanodegree's course: Artificial Intelligence Programming with Python.
https://github.com/marcosvbras/udacity-nd109-project-one
nanodegree nanodegree-project python udacity udacity-nanodegree
Last synced: 3 months ago
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Data Exploitation project to Udacity Nanodegree's course: Artificial Intelligence Programming with Python.
- Host: GitHub
- URL: https://github.com/marcosvbras/udacity-nd109-project-one
- Owner: marcosvbras
- License: apache-2.0
- Created: 2018-12-09T23:59:11.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2018-12-16T23:12:11.000Z (over 6 years ago)
- Last Synced: 2025-02-01T08:47:37.930Z (5 months ago)
- Topics: nanodegree, nanodegree-project, python, udacity, udacity-nanodegree
- Language: Python
- Homepage:
- Size: 25.5 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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](https://www.motivateco.com/), 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:
```bash
$ 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:
```bash
$ python chicago_bikeshare_pt.py
```