What is sklearn.datasets.load_boston(*[, return_X_y])?
Scikit-learn contains small datasets that are very easy to access. The Boston house-prices dataset is one of these.
Features
-
The dataset contains 506 rows and 13 columns.
-
The dataset has no
nullor missing values. -
Many machine learning papers use this dataset to address regression problems.
The dataset contains the following 13 characteristics:
| Characteristic | Description |
|---|---|
| CRIM | This is the average per person crime rate by town. |
| ZN | This is the extent of private land zoned for lots over 25,000 square feet. |
| INDUS | This is the extent of non-retail business sections of land per town. |
| CHAS | It is considered to be 1 if tract bounds river, otherwise it’s always 0. |
| NOX | This refers to the Nitric Oxide concentration. |
| RM | This is the average number of rooms per residence. |
| AGE | This is the extent of proprietor-involved units worked before 1940. |
| DIS | This is the weighted distance to five Boston business focuses. |
| RAD | This is the index of access to radial highways. |
| TAX | This is the property tax rate (full-value) per $10,000. |
| PRATIO | This tells the student-teacher ratio. |
| B | B is calculated by 1000(Bk-0.63)^2. Bk denotes the proportion of black people by town. |
| LSTAT | This tells us the percent lower status of the population. |
Parameters
return_X_y: If set to True, returns (data, target). The default value for this is False.
Code
from sklearn.datasets import load_bostonX, y = load_boston(return_X_y = True)data = load_boston()print('The DataFrame is:\n', data)print('The shape of Dataframe is: ', X.shape)
Explanation
To include the Boston-house prices dataset, we have to import it using the scikit-learn library as done in line 1 of code.
The data object holds the prices data inside the dataset. The X.shape argument holds the figure of the dataset, i.e., 506 rows and 13 columns.
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