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## About this lesson

We need to install some more elements to do a linear regression, so we'll discuss what we need in this video.

## Exercise files

Download this lesson’s related exercise files.

Linear Regression Installation.docx59.2 KB Linear Regression Installation - Solution.docx

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## Quick reference

### Linear Regression Installation

To run Linear Regression analysis, we need to install a number of things.

### When to use

You only need to do this once. After it's all installed, you can use it whenever you like.

### Instructions

From the Terminal:

- pip install scikit-learn
- pip install matplotlib
- pip install seaborn
- pip install matplotlib

From your Jupyter Notebook, import everything:

- import numpy as np
- import pandas as pd
- %matplotlib inline
- import scipy.stats as stats
- import matplotlib.pyplot as plt
- import sklearn
- from sklearn.datasets import load_boston
- import seaborn as sns
- boston = load_boston()

Finally, create a DataFrame with the Boston Data:

bost = pd.DataFrame(boston.data, columns=boston.feature_names)

### Hints & tips

- First Install all the programs we need on the Terminal
- Next import all the modules into your Jupyter Notebook
- Load The Boston Data, then create a DataFrame with it

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