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Omarrran
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US_GeoSpatial_Dataset_by_HNM

Tasks:
Text Classification
Feature Extraction
Modalities:
Tabular
Text
Formats:
csv
Languages:
English
Size:
< 1K
Tags:
geo
geography
US
Location
Geospatial
HNM
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files
xet
Community

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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

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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.

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