Boston housing Dataset without the racial profiling attribute

Like many data scientists, I use the UCI datasets extensively

Specifically, the Boston Housing Dataset is useful to teach Data Science

For example, I use it in the Data Science for IoT course because its a dataset which people can relate to easily(finding median value of house prices)

The attributes are

    1. CRIM      per capita crime rate by town
    2. ZN        proportion of residential land zoned for lots over 
                 25,000 sq.ft.
    3. INDUS     proportion of non-retail business acres per town
    4. CHAS      Charles River dummy variable (= 1 if tract bounds 
                 river; 0 otherwise)
    5. NOX       nitric oxides concentration (parts per 10 million)
    6. RM        average number of rooms per dwelling
    7. AGE       proportion of owner-occupied units built prior to 1940
    8. DIS       weighted distances to five Boston employment centres
    9. RAD       index of accessibility to radial highways
    10. TAX      full-value property-tax rate per $10,000
    11. PTRATIO  pupil-teacher ratio by town
    12. B        1000(Bk - 0.63)^2 where Bk is the proportion of blacks 
                 by town
    13. LSTAT    % lower status of the population
    14. MEDV     Median value of owner-occupied homes in $1000's
However, there is a problem with this dataset especially with this attribute
12. B 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town

Hence, I use a modified version of the dataset which you can find as a CSV HERE

It removes the above attribute and it does not make any difference to the dataset

You can then upload into a dataframe using the following code and changing to your directory path

# Read the data from the csv file
Boston = read.csv(“c:\\futuretext\\Boston.csv”)