Turkana Comprehensive schools Accessibility

# You can use .explore() to interactively explore the data or .plot() to plot the data
# destinations_schools.plot()
Schools.explore()

# Or instead, you can use explore for an interactive plot.
join.explore(column="Access_Comprehensive Schools", scheme='natural_breaks',cmap="plasma")

import folium
from folium.plugins import MarkerCluster
from IPython.display import display

# Convert merged GeoDataFrame to WGS84 (EPSG:4326) for compatibility with Folium
merged = merged.to_crs(epsg=4326)

# Ensure consistent category naming to match color dictionary
merged["Access_Category"] = merged["Access_Category"].replace({
    "Accessible": "With Access",
    "Not Accessible": "Without Access"
})

# Define colors matching Access_Category
colors = {"With Access": "orange", "Without Access": "green"}

# Define the center of the map
map_center = [merged.geometry.centroid.y.mean(), merged.geometry.centroid.x.mean()]

# Create a folium map
m = folium.Map(location=map_center, zoom_start=10)

# Create feature groups for better control
accessible_group = folium.FeatureGroup(name="With Access")
non_accessible_group = folium.FeatureGroup(name="Without Access")

# Add points to the appropriate feature group
for _, row in merged.iterrows():
    marker = folium.CircleMarker(
        location=[row.geometry.y, row.geometry.x],  # Extract lat/lon
        radius=2,  # Adjusted size for clarity
        color=colors[row["Access_Category"]],
        fill=True,
        fill_color=colors[row["Access_Category"]],
        fill_opacity=0.7,
        popup=f"Access: {row['Access_Category']}"
    )

    # Add to the respective group
    if row["Access_Category"] == "With Access":
        accessible_group.add_child(marker)
    else:
        non_accessible_group.add_child(marker)

# Add feature groups to the map
m.add_child(accessible_group)
m.add_child(non_accessible_group)

# Add layer control to toggle visibility
folium.LayerControl().add_to(m)

# Display the map in Jupyter Notebook
display(m)