Logistic Regression Project - Solutions

In this project we will be working with a fake advertising data set, indicating whether or not a particular internet user clicked on an Advertisement on a company website. We will try to create a model that will predict whether or not they will click on an ad based off the features of that user.

This data set contains the following features:

'Daily Time Spent on Site': consumer time on site in minutes
'Age': cutomer age in years
'Area Income': Avg. Income of geographical area of consumer
'Daily Internet Usage': Avg. minutes a day consumer is on the internet
'Ad Topic Line': Headline of the advertisement
'City': City of consumer
'Male': Whether or not consumer was male
'Country': Country of consumer
'Timestamp': Time at which consumer clicked on Ad or closed window
'Clicked on Ad': 0 or 1 indicated clicking on Ad

Import Libraries

Import a few libraries you think you'll need (Or just import them as you go along!)

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

Get the Data

Read in the advertising.csv file and set it to a data frame called ad_data.

ad_data = pd.read_csv('advertising.csv')

Check the head of ad_data