Datasets:

gvlassis
/

california_housing

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	37.88	-122.23	4.526
8.3014	21	6.238137	0.97188	2,401	2.109842	37.86	-122.22	3.585
7.2574	52	8.288136	1.073446	496	2.80226	37.85	-122.24	3.521
5.6431	52	5.817352	1.073059	558	2.547945	37.85	-122.25	3.413
3.8462	52	6.281853	1.081081	565	2.181467	37.85	-122.25	3.422
4.0368	52	4.761658	1.103627	413	2.139896	37.85	-122.25	2.697
3.6591	52	4.931907	0.951362	1,094	2.128405	37.84	-122.25	2.992
3.12	52	4.797527	1.061824	1,157	1.788253	37.84	-122.25	2.414
2.0804	42	4.294118	1.117647	1,206	2.026891	37.84	-122.26	2.267
3.6912	52	4.970588	0.990196	1,551	2.172269	37.84	-122.25	2.611
3.2031	52	5.477612	1.079602	910	2.263682	37.85	-122.26	2.815
3.2705	52	4.77248	1.024523	1,504	2.049046	37.85	-122.26	2.418
3.075	52	5.32265	1.012821	1,098	2.346154	37.85	-122.26	2.135
2.6736	52	4	1.097701	345	1.982759	37.84	-122.26	1.913
1.9167	52	4.262903	1.009677	1,212	1.954839	37.85	-122.26	1.592
2.125	50	4.242424	1.07197	697	2.640152	37.85	-122.26	1.4
2.775	52	5.939577	1.048338	793	2.39577	37.85	-122.27	1.525
2.1202	52	4.052805	0.966997	648	2.138614	37.85	-122.27	1.555
1.9911	50	5.343675	1.085919	990	2.362768	37.84	-122.26	1.587
2.6033	52	5.465455	1.083636	690	2.509091	37.84	-122.27	1.629
1.3578	40	4.524096	1.108434	409	2.463855	37.85	-122.27	1.475
1.7135	42	4.478142	1.002732	929	2.538251	37.85	-122.27	1.598
1.725	52	5.096234	1.131799	1,015	2.123431	37.84	-122.27	1.139
2.1806	52	5.193846	1.036923	853	2.624615	37.84	-122.27	0.997
2.6	52	5.270142	1.035545	1,006	2.383886	37.84	-122.27	1.326
2.4038	41	4.495798	1.033613	317	2.663866	37.85	-122.28	1.075
2.4597	49	4.728033	1.020921	607	2.539749	37.85	-122.28	0.938
1.808	52	4.780856	1.060453	1,102	2.775819	37.85	-122.28	1.055
1.6424	50	4.401691	1.040169	1,131	2.391121	37.84	-122.28	1.089
1.6875	52	4.703226	1.032258	395	2.548387	37.84	-122.28	1.32
1.9274	49	5.068783	1.18254	863	2.283069	37.84	-122.28	1.223
1.9615	52	4.882086	1.090703	1,168	2.648526	37.84	-122.28	1.152
1.7969	48	5.737313	1.220896	1,026	3.062687	37.84	-122.27	1.104
1.375	49	5.030395	1.112462	754	2.291793	37.83	-122.27	1.049
2.7303	51	4.972015	1.070896	1,258	2.347015	37.83	-122.27	1.097
1.4861	49	4.602273	1.068182	570	2.159091	37.83	-122.27	0.972
1.0972	48	4.807487	1.15508	987	2.639037	37.83	-122.27	1.045
1.4103	52	3.74938	0.967742	901	2.235732	37.83	-122.28	1.039
3.48	52	4.757282	1.067961	689	2.229773	37.83	-122.26	1.914
2.5898	52	3.494253	1.027299	1,377	1.978448	37.83	-122.26	1.76
2.0978	52	4.21519	1.060759	946	2.394937	37.83	-122.26	1.554
1.2852	51	3.759036	1.248996	517	2.076305	37.83	-122.26	1.5
1.025	49	3.772487	1.068783	462	2.444444	37.84	-122.26	1.188
3.9643	52	4.79798	1.020202	467	2.358586	37.84	-122.26	1.888
3.0125	52	4.941781	1.065068	660	2.260274	37.83	-122.26	1.844
2.6768	52	4.335079	1.099476	718	1.879581	37.83	-122.26	1.823
2.026	50	3.700658	1.059211	616	2.026316	37.83	-122.26	1.425
1.7348	43	3.980237	1.233202	558	2.205534	37.82	-122.27	1.375
0.9506	40	3.9	1.21875	423	2.64375	37.82	-122.26	1.875
1.775	40	2.6875	1.065341	700	1.988636	37.82	-122.27	1.125
0.9218	21	2.045662	1.034247	735	1.678082	37.82	-122.27	1.719
1.5045	43	4.589681	1.120393	1,061	2.60688	37.82	-122.27	0.938
1.1108	41	4.473611	1.184722	1,959	2.720833	37.82	-122.27	0.975
1.2475	52	4.075	1.14	1,162	2.905	37.82	-122.27	1.042
1.6098	52	5.021459	1.008584	701	3.008584	37.82	-122.28	0.875
1.4113	52	4.295455	1.104545	576	2.618182	37.82	-122.28	0.831
1.5057	52	4.779923	1.111969	622	2.401544	37.82	-122.28	0.875
0.8172	52	6.102459	1.372951	728	2.983607	37.82	-122.28	0.853
1.2171	52	4.5625	1.121711	1,074	3.532895	37.82	-122.28	0.803
2.5625	2	2.77193	0.754386	94	1.649123	37.82	-122.29	0.6
3.3929	52	5.994652	1.128342	554	2.962567	37.83	-122.29	0.757
6.1183	49	5.869565	1.26087	86	3.73913	37.82	-122.29	0.75
0.9011	50	6.229508	1.557377	377	3.090164	37.81	-122.29	0.861
1.191	52	7.698113	1.490566	521	3.27673	37.81	-122.3	0.761
2.5938	48	6.225564	1.368421	392	2.947368	37.81	-122.3	0.735
1.1667	52	5.40107	1.117647	604	3.229947	37.81	-122.3	0.784
0.8056	48	4.38253	1.066265	788	2.373494	37.81	-122.3	0.844
2.6094	52	6.986395	1.659864	492	3.346939	37.8	-122.29	0.813
1.8516	52	6.97561	1.329268	274	3.341463	37.81	-122.3	0.85
0.9802	46	4.584288	1.05401	1,823	2.983633	37.81	-122.29	1.292
1.7719	26	6.047244	1.19685	392	3.086614	37.81	-122.29	0.825
0.7286	46	3.375451	1.072202	582	2.101083	37.81	-122.29	0.952
1.75	49	5.552632	1.342105	560	3.684211	37.81	-122.29	0.75
0.4999	46	1.714286	0.571429	18	2.571429	37.81	-122.29	0.675
2.483	20	6.278195	1.210526	290	2.180451	37.81	-122.29	1.375
0.9241	17	2.817768	1.052392	762	1.735763	37.81	-122.28	1.775
2.4464	36	5.724951	1.104126	1,236	2.428291	37.81	-122.28	1.021
1.1111	19	5.830918	1.173913	721	3.483092	37.81	-122.28	1.083
0.8026	23	5.369231	1.150769	1,054	3.243077	37.81	-122.29	1.125
2.0114	38	4.412903	1.135484	344	2.219355	37.8	-122.28	1.313
1.5	17	3.197232	1	609	2.107266	37.81	-122.28	1.625
1.1667	52	3.75	1	183	3.267857	37.81	-122.27	1.125
1.5208	52	3.908046	1.114943	200	2.298851	37.81	-122.28	1.125
0.8075	52	2.490323	1.058065	346	2.232258	37.81	-122.28	1.375
1.8088	35	5.609467	1.088757	467	2.763314	37.81	-122.28	1.188
2.4083	52	6.721739	1.243478	377	3.278261	37.81	-122.28	0.982
0.977	40	2.315789	1.186842	582	1.531579	37.81	-122.27	1.188
0.76	10	2.651515	1.054545	546	1.654545	37.81	-122.27	1.625
0.9722	10	2.692308	1.076923	125	3.205128	37.8	-122.27	1.375
1.2434	52	2.929412	0.917647	396	4.658824	37.8	-122.27	5.00001
2.0938	16	2.745856	1.082873	800	2.209945	37.8	-122.27	1.625
0.8668	52	2.443182	0.988636	904	10.272727	37.8	-122.28	1.375
0.75	52	2.823529	0.911765	191	5.617647	37.8	-122.28	1.625
2.6354	27	3.493377	1.149007	718	2.377483	37.79	-122.27	1.875
1.8477	39	3.672377	1.334047	1,327	2.841542	37.8	-122.27	1.792
2.0096	36	2.294016	1.066294	3,469	1.493328	37.8	-122.26	1.3
2.8345	31	3.894915	1.127966	2,048	1.735593	37.82	-122.26	1.838
2.0062	29	3.681319	1.175824	202	2.21978	37.81	-122.26	1.25
1.2185	22	2.9456	1.016	2,024	1.6192	37.82	-122.26	1.7
2.6104	37	3.707143	1.107143	1,838	1.87551	37.82	-122.26	1.931

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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:

MedInc: Median income of the people living in the block
HouseAge: Median age of the houses in a block
AveRooms: Average rooms of houses in a block
AveBedrms: Average bedrooms of houses in a block
Population: Number of people living in a block
AveOccup: Average number of people under the same roof
Latitude: Geographical latitude
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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Size of downloaded dataset files:

1.06 MB

Size of the auto-converted Parquet files:

1.06 MB

Number of rows:

20,640

Models trained or fine-tuned on gvlassis/california_housing

sadhaklal/mlp-california-housing

Tabular Regression • Updated 5 days ago