This project requires Python and the following Python libraries installed:
You will also need to have software installed to run and execute a Jupyter Notebook
If you do not have Python installed yet, it is highly recommended that you install the Anaconda distribution of Python, which already has the above packages and more included.
This project contains three files:
boston_housing.ipynb
: This is the main file where you will be performing your work on the project.housing.csv
: The project dataset. You'll load this data in the notebook.visuals.py
: This Python script provides supplementary visualizations for the project. Do not modify.
The modified Boston housing dataset consists of 489 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.
Features
RM
: average number of rooms per dwellingLSTAT
: percentage of population considered lower statusPTRATIO
: pupil-teacher ratio by town
Target Variable
4. MEDV
: median value of owner-occupied homes