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Datasets:
gvlassis
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california_housing

Tasks:
Tabular Regression
Modalities:
Tabular
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English
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10K<n<100K
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MedInc
float64
0.5
15
HouseAge
float64
1
52
AveRooms
float64
0.85
142
AveBedrms
float64
0.38
34.1
Population
float64
3
35.7k
AveOccup
float64
0.69
600
Latitude
float64
32.5
42
Longitude
float64
-124.35
-114.31
MedHouseVal
float64
0.15
5
8.3252
41
6.984127
1.02381
322
2.555556
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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")
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