Ensure your Lambda has s3:PutObject permissions if you want to save the file to Amazon S3 .
To create this automation, you will typically use with the pandas and openpyxl libraries. 1. Prepare Your Environment Download EARTHQUAKE MAGNIDUTE DATA with lambda (1) xlsx
If you don't need automation, you can download pre-filtered data directly from the USGS Earthquake Catalog in , which opens natively in Excel. Ensure your Lambda has s3:PutObject permissions if you
This script fetches real-time data for earthquakes with a magnitude of 1.0 or higher from the last 24 hours: Prepare Your Environment If you don't need automation,
import json import pandas as pd import requests import boto3 from io import BytesIO def lambda_handler(event, context): # 1. Fetch data from USGS API (GeoJSON format) url = "https://usgs.gov" response = requests.get(url) data = response.json() # 2. Extract relevant magnitude and location details features = data['features'] quakes = [] for f in features: prop = f['properties'] quakes.append({ 'Magnitude': prop['mag'], 'Place': prop['place'], 'Time': pd.to_datetime(prop['time'], unit='ms'), 'Type': prop['type'] }) # 3. Convert to Excel using Pandas df = pd.DataFrame(quakes) excel_buffer = BytesIO() with pd.ExcelWriter(excel_buffer, engine='openpyxl') as writer: df.to_excel(writer, index=False, sheet_name='Earthquakes') # 4. Upload to S3 (optional, for storage) s3 = boto3.client('s3') bucket_name = "your-bucket-name" s3.put_object(Bucket=bucket_name, Key="earthquakes.xlsx", Body=excel_buffer.getvalue()) return { 'statusCode': 200, 'body': "XLSX file successfully generated and stored." } Use code with caution.
You can store your target BUCKET_NAME as an environment variable for better flexibility. Alternative: Manual Download