Datasets:

Omarrran
/

US_GeoSpatial_Dataset_by_HNM

license: mit
task_categories:
  - text-classification
  - feature-extraction
language:
  - en
size_categories:
  - 1K<n<10K
tags:
  - geo
  - geography
  - US
  - Location
  - Geospatial
  - HNM
  - Numerical
  - catageorical
  - demographic
  - social
  - economic

US_GeoSpatial_dataset_by_HNM

Dataset Description

This dataset contains 56 records with 16 features.

Dataset Summary

Metric	Value
Total Rows	56
Total Columns	16
Numeric Columns	10
Categorical Columns	6
Missing Values	0 (0.00%)
Duplicate Rows	0
Memory Usage	19.51 MB

Dataset Structure

Data Fields

Column	Type	Sample/Range	Unique Values	Missing %
`geo_id`	int64	Range: [1.00, 78.00]	56	0.0%
`region_code`	int64	Range: [1.00, 9.00]	5	0.0%
`division_code`	int64	Range: [0.00, 9.00]	10	0.0%
`state_fips_code`	int64	Range: [1.00, 78.00]	56	0.0%
`state_gnis_code`	int64	Range: [68085.00, 1802710.00]	56	0.0%
`state`	object	Example: 'GU'	56	0.0%
`state_name`	object	Example: 'Guam'	56	0.0%
`lsad_code`	int64	Range: [0.00, 0.00]	1	0.0%
`mtfcc_feature_class_code`	object	Example: 'G4000'	1	0.0%
`functional_status`	object	Example: 'A'	1	0.0%
`area_land_meters`	int64	Range: [158340389.00, 1478927050067.00]	56	0.0%
`area_water_meters`	int64	Range: [18687196.00, 245394222619.00]	56	0.0%
`int_point_lat`	float64	Range: [-14.27, 63.35]	56	0.0%
`int_point_lon`	float64	Range: [-170.67, 145.60]	56	0.0%
`int_point_geom`	object	Example: 'POINT(144.7719021 13.4417451)'	56	0.0%
`state_geom`	object	Example: 'POLYGON((144.563426 13.448065, 144.56355 13.445248'	56	0.0%

Data Splits

This dataset contains a single split with all 56 examples.

This is the US Census Bureau Geographic Data - specifically the state-level geographic identifiers and measurements dataset.

What This Dataset Contains

Column	Meaning
`geo_id`, `state_fips_code`	Federal Information Processing Standard codes for US states/territories
`region_code`, `division_code`	Census Bureau regional classifications (4 regions, 9 divisions)
`state_gnis_code`	Geographic Names Information System identifiers
`area_land_meters`, `area_water_meters`	Land and water area measurements
`int_point_lat`, `int_point_lon`	Internal centroid coordinates (center point of each state)

Practical Use Cases

1. Geospatial Analysis & Mapping

Creating choropleth maps of US states
Calculating distances between state centers
Building location-based services that need state boundaries

2. Data Enrichment & Joins

Joining with other datasets (population, economic, health data) using FIPS codes
Standardizing geographic identifiers across multiple data sources
Linking Census data with external APIs

3. Regional Analytics

Comparing metrics across Census regions/divisions (Northeast, Midwest, South, West)
Grouping states for regional market analysis
Understanding geographic distribution patterns

4. Environmental & Land Use Studies

Calculating land-to-water ratios by state
Analyzing state sizes for resource allocation models
Comparing population density (when combined with population data)

5. Machine Learning Features

Geographic features for predictive models
Clustering states by location or size
Spatial autocorrelation analysis

This dataset is essentially a foundational geographic reference dataset - most valuable when joined with demographic, economic, or social datasets for spatial analysis.

Usage

Loading the Dataset

from datasets import load_dataset

# Load from Hugging Face Hub
dataset = load_dataset("Omarrran/US_GeoSpatial_Dataset_by_HNM")

# Access the data
train_data = dataset['train']
print(train_data[0])

Loading as Pandas DataFrame

import pandas as pd
from datasets import load_dataset

dataset = load_dataset("Omarrran/US_GeoSpatial_Dataset_by_HNM")
df = dataset['train'].to_pandas()

Statistical Summary

Numeric Columns

          geo_id  region_code  division_code  state_fips_code  state_gnis_code  lsad_code  area_land_meters  area_water_meters  int_point_lat  int_point_lon
count  56.000000    56.000000      56.000000        56.000000     5.600000e+01       56.0      5.600000e+01       5.600000e+01      56.000000      56.000000
mean   32.535714     3.232143       4.660714        32.535714     1.522958e+06        0.0      1.635888e+11       1.245427e+10      36.944973     -85.299146
std    19.075891     2.080132       2.830206        19.075891     4.648599e+05        0.0      2.173973e+11       3.503733e+10      11.055418      49.717199
min     1.000000     1.000000       0.000000         1.000000     6.808500e+04        0.0      1.583404e+08       1.868720e+07     -14.267159    -170.668267
25%    17.750000     2.000000       2.750000        17.750000     1.423460e+06        0.0      2.483234e+10       1.502762e+09      34.376997    -101.722698
50%    31.500000     3.000000       5.000000        31.500000     1.779784e+06        0.0      1.285501e+11       3.706434e+09      38.996207     -87.998035
75%    46.250000     4.000000       7.000000        46.250000     1.779800e+06        0.0      2.007729e+11       8.964466e+09      42.932463     -76.931011
max    78.000000     9.000000       9.000000        78.000000     1.802710e+06        0.0      1.478927e+12       2.453942e+11      63.347356     145.601021

Additional Information

Dataset Creation

Source: /content/us_state_boundaries_56_20251126_191744.csv
Created: 2025-11-28
Format: CSV

Licensing Information

This dataset is released under the MIT License.

Citation Information

@dataset{us_geospatial_dataset_by_hnm},
  title = {US_GeoSpatial_dataset_by_HNM},
  year = {2025},
  Author = {Haq Nawaz Malik}
  publisher = {Hugging Face},
  Link = {https://huggingface.co/datasets/Omarrran/US_GeoSpatial_Dataset_by_HNM}
}

Contributions

Thanks to the contributors who helped in creating this dataset.