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"""
Example: Basic analysis of Australian Health and Geographic Data
This example demonstrates how to load and analyse the AHGD dataset
using Python and common data science libraries.
"""
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
def load_dataset(format_type='parquet'):
"""Load AHGD dataset in specified format."""
if format_type == 'parquet':
return pd.read_parquet('ahgd_data.parquet')
elif format_type == 'csv':
return pd.read_csv('ahgd_data.csv')
elif format_type == 'json':
import json
with open('ahgd_data.json', 'r') as f:
data = json.load(f)
return pd.DataFrame(data['data'])
else:
raise ValueError(f"Unsupported format: {format_type}")
def basic_analysis():
"""Perform basic statistical analysis."""
# Load data
df = load_dataset('parquet')
print(f"Dataset shape: {df.shape}")
print(f"Columns: {list(df.columns)}")
# Summary statistics
numeric_cols = df.select_dtypes(include=['float64', 'int64']).columns
print("\nSummary Statistics:")
print(df[numeric_cols].describe())
# State-level aggregations
if 'state_name' in df.columns and 'life_expectancy_years' in df.columns:
state_health = df.groupby('state_name').agg({
'life_expectancy_years': 'mean',
'smoking_prevalence_percent': 'mean',
'obesity_prevalence_percent': 'mean'
}).round(2)
print("\nHealth Indicators by State:")
print(state_health)
return df
def create_visualisations(df):
"""Create basic visualisations."""
plt.style.use('seaborn-v0_8')
# Life expectancy distribution
plt.figure(figsize=(10, 6))
plt.subplot(2, 2, 1)
df['life_expectancy_years'].hist(bins=20, alpha=0.7)
plt.title('Distribution of Life Expectancy')
plt.xlabel('Years')
# Health indicators correlation
if all(col in df.columns for col in ['life_expectancy_years', 'smoking_prevalence_percent']):
plt.subplot(2, 2, 2)
plt.scatter(df['smoking_prevalence_percent'], df['life_expectancy_years'], alpha=0.6)
plt.xlabel('Smoking Prevalence (%)')
plt.ylabel('Life Expectancy (Years)')
plt.title('Smoking vs Life Expectancy')
plt.tight_layout()
plt.savefig('ahgd_analysis.png', dpi=300, bbox_inches='tight')
plt.show()
if __name__ == "__main__":
# Run basic analysis
data = basic_analysis()
# Create visualisations
create_visualisations(data)
print("\nAnalysis complete! Check ahgd_analysis.png for visualisations.")
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