README.md

metadata

dataset_info:
  features:
    - name: MedInc
      dtype: float64
    - name: HouseAge
      dtype: float64
    - name: AveRooms
      dtype: float64
    - name: AveBedrms
      dtype: float64
    - name: Population
      dtype: float64
    - name: AveOccup
      dtype: float64
    - name: Latitude
      dtype: float64
    - name: Longitude
      dtype: float64
    - name: MedHouseVal
      dtype: float64
  splits:
    - name: train
      num_bytes: 1198080
      num_examples: 16640
    - name: validation
      num_bytes: 144000
      num_examples: 2000
    - name: test
      num_bytes: 144000
      num_examples: 2000
  download_size: 1056079
  dataset_size: 1486080
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
license: mit
task_categories:
  - tabular-regression
language:
  - en
size_categories:
  - 10K<n<100K
pretty_name: California Housing

California Housing

About

🏠 The California Housing dataset, first appearing in "Sparse spatial autoregressions" (1997)

Description

This is an (unofficial) Hugging Face version of the California Housing dataset from the S&P Letters paper "Sparse spatial autoregressions" (1997). It can also be found in StatLib and Luis Torgo's page. A modified version of it, used in "Hands-On Machine learning with Scikit-Learn and TensorFlow", with 9 differenfeatures and missing values, also circulates online.

The California Housing dataset comes from the California 1990 Census. It contains 20640 samples, each of which corresponds to a geographical block and the people living therein. Specifically, it contains the following 8 features:

1. MedInc: Median income of the people living in the block
2. HouseAge: Median age of the houses in a block
3. AveRooms: Average rooms of houses in a block
4. AveBedrms: Average bedrooms of houses in a block
5. Population: Number of people living in a block
6. AveOccup: Average number of people under the same roof
7. Latitude: Geographical latitude
8. Longitude: Geographical longitude

The target variable is the median house value (MedHouseVal).

Usage

import datasets

dataset = datasets.load_dataset("gvlassis/california_housing")