https://github.com/nicolasanelli/udacity-datascience-nd
Project made during the udacity data science nanodegree. It consists of analyzing data from a company that offers bicycle rentals.
https://github.com/nicolasanelli/udacity-datascience-nd
data-science jupyter-notebook python udacity
Last synced: about 2 months ago
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Project made during the udacity data science nanodegree. It consists of analyzing data from a company that offers bicycle rentals.
- Host: GitHub
- URL: https://github.com/nicolasanelli/udacity-datascience-nd
- Owner: nicolasanelli
- Created: 2019-05-02T00:24:09.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-05-07T03:32:05.000Z (about 7 years ago)
- Last Synced: 2025-04-13T05:24:05.202Z (over 1 year ago)
- Topics: data-science, jupyter-notebook, python, udacity
- Language: Jupyter Notebook
- Homepage:
- Size: 14 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Udacity datascience
This is my version of end project did in Fundamentals of Data Science Nanodegree I provided by [Udacity](https://www.udacity.com) in late 2017.
## Structure
### Jupyter Notebook
By easy design and documenting mind, this analysis was made in [Jupyter Notebook](https://jupyter.org/), which is "an amazing open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text".
** Obs: ** You can see my jupyter notebook on this project out of the box by opening the [this](bay_area_bike_share_analysis.ipynb) file.
### Libraries
The main libraries used in this project are:
- [pandas](https://pandas.pydata.org/) - "a library providing high-performance, easy-to-use data structures and data analysis tools"
- [numpy](https://www.numpy.org/) - "the fundamental package for scientific computing with Python"
- [matplotlib](https://matplotlib.org/) - "a plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments"
## Pre requisites
There are many ways of having this enviroment for running this project, I encourage you to use [python virtualenv](https://virtualenv.pypa.io/en/latest/) provided by [PIP](https://pypi.org/project/pip/), a package installer for python.
## How to play-it
First of all, you will need to create you virtualenv rather in python 3. So once you download this project, you can run in project root folder:
```
$ virtualenv --python='/usr/local/bin/python3' .ENV
```
This will create a folder called .ENV with some struct inside it. Once this has been successfully, you will need to activate you virtual env. This can be made with following code:
```
$ source .ENV/bin/activate
```
You may note that now your bash has a prefix (probably .ENV). This indicates that you are inside your virtualenv profile. You can try run 'python -V'and should get your python 3 version.
Now you need to install the project dependencies, that are stored in requirements.txt file. Fortunately, PIP has a command for this kind of files:
```
$ pip install -r requirements.txt
```
Now that all your dependencies have been resolved, you can run this jupyter notebook by running:
```
$ jupyter notebook bay_area_bike_share_analysis.ipynb
```
Now you can play-it on your browser.
## Quiting
For stop running Jupyter, you can press Ctrl+C and YES on terminal. And for quiting your virtualenv you cand type:
```
$ deactivate
```
## Authors
* **Nicolas Anelli** - [Github](https://github.com/NicolasAnelli)