https://github.com/jonad/boston_housing_price

Predicting Boston Housing Prices.
https://github.com/jonad/boston_housing_price

boston-housing-dataset jupyter-notebook matplotlib numpy pandas python3 scikit-learn

Last synced: 19 days ago
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Predicting Boston Housing Prices.

• Host: GitHub
• URL: https://github.com/jonad/boston_housing_price
• Owner: jonad
• Created: 2017-01-13T02:04:24.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2017-11-28T20:47:13.000Z (about 7 years ago)
• Last Synced: 2024-11-07T06:28:11.398Z (2 months ago)
• Topics: boston-housing-dataset, jupyter-notebook, matplotlib, numpy, pandas, python3, scikit-learn
• Language: Jupyter Notebook
• Homepage:
• Size: 1.83 MB
• Stars: 0
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Project: Predicting Boston Housing Prices

### Install

This project requires **Python 2.7** and the following Python libraries installed:

- [NumPy](http://www.numpy.org/)

- [Pandas](http://pandas.pydata.org/)

- [matplotlib](http://matplotlib.org/)

- [scikit-learn](http://scikit-learn.org/stable/)

-  [Jupyter Notebook](http://ipython.org/notebook.html)

### Run

In a terminal or command window, navigate to the top-level project directory,  and run one of the following commands:

```bash

ipython notebook boston_housing.ipynb

```  

or

```bash

jupyter notebook boston_housing.ipynb

```

### Data

The modified Boston housing dataset consists of 490 data points, with each datapoint having 3 features. This dataset is a modified version of the Boston Housing dataset found on the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/Housing).

**Features**

1.  `RM`: average number of rooms per dwelling

2. `LSTAT`: percentage of population considered lower status

3. `PTRATIO`: pupil-student ratio by town

**Target Variable**

4. `MEDV`: median value of owner-occupied homes