Post #5: Automating Map Exports for Each Feature in Python

 

Title: Automatically Export One Map per Feature Using Python & GeoPandas

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📍Introduction

Ever had to manually export 100+ maps—one for each zone, district, or parcel?
Let’s stop doing it manually. With Python, you can loop through your features and save one map per feature as a PNG, PDF, or even a web map.

We’ll automate:

• Filtering your layer

• Plotting one feature at a time

• Exporting maps with custom titles and names

Let’s build your own map production engine. 🛠️

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🧰 Step 1: Load the Shapefiles

python
import geopandas as gpd
import matplotlib.pyplot as plt
import os

# Load polygons (e.g., districts) and points (e.g., wells)
districts = gpd.read_file("data/districts.shp")
wells = gpd.read_file("data/water_wells.shp")

# Make sure CRS matches
districts = districts.to_crs("EPSG:4326")
wells = wells.to_crs("EPSG:4326")

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🗂️ Step 2: Create an Output Folder

python
output_folder = "output/maps"
os.makedirs(output_folder, exist_ok=True)

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🔁 Step 3: Loop Through Features and Export Maps

python
for idx, district in districts.iterrows():
    district_name = district["district_name"]
    single_district = gpd.GeoDataFrame([district], crs=districts.crs)

    # Filter wells inside the district
    wells_in_district = wells[wells.within(district.geometry)]

    # Plot
    fig, ax = plt.subplots(figsize=(10, 10))
    single_district.plot(ax=ax, color='lightgreen', edgecolor='black')
    wells_in_district.plot(ax=ax, color='blue', markersize=20)

    ax.set_title(f"Wells in {district_name}", fontsize=14)
    plt.axis("off")
    plt.tight_layout()

    # Save
    filename = os.path.join(output_folder, f"map_{district_name}.png")
    plt.savefig(filename, dpi=300)
    plt.close()

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💡 Bonus: Clean Up Filenames

python
from slugify import slugify

filename = os.path.join(output_folder, f"map_{slugify(district_name)}.png")

Install python-slugify with:

bash
pip install python-slugify

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🧠 What Can You Use This For?

• One PDF/PNG per municipality, parcel, plot, project area

• Batch mapping for client reports

• Export thematic maps for schools, wells, or zoning

• Save per-feature maps to share on email, Google Drive, etc.

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📌 Want to Go Further?

• Add labels using plt.text()

• Include basemaps using contextily

• Create PDFs with PdfPages

• Combine multiple maps into a dashboard layout with subplot2grid

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🎯 Conclusion

Map production doesn’t need to be manual. With just a loop and some Python logic, you can export hundreds of clean, high-quality maps—customized for each feature.

This is how GIS automation adds real productivity to your workflow.

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📌 Next Up:

➡️ Post 6: Add Basemaps to Your Maps with Contextily and XYZ Tiles