Trees open data : More information in table.

python_scripts/parse_wurzburg_open_data/parse_open_data.py

@@ -38,18 +38,27 @@ else:
 df = pd.read_parquet(INPUT_FILE, engine='fastparquet')
 
 
-interactive_map = folium.Map()
 species = 'species_latin'
 coordinates = ['latitude', 'longitude']
 interesting_columns = ['tree_number', 'species_latin', 'latitude', 'longitude']
 lat_min, lon_min, lat_max, lon_max = df[coordinates].agg(['min', 'max']).stack().values
+
+interactive_map = folium.Map()
 interactive_map.fit_bounds([(lat_min, lon_min), (lat_max, lon_max)])
 
-for same, grouped_df in df[interesting_columns].drop_duplicates().groupby(species):
-    for row in grouped_df.itertuples():
+for same, grouped_df in df.groupby('tree_number'):
+    tree = grouped_df.iloc[0]
+    table = grouped_df.drop(coordinates, axis=1).describe().to_html()
+    tree_id = tree['tree_number']
+    lat = tree['latitude']
+    lon = tree['longitude']
+    species = tree['species_latin']
+    species_de = tree['species_german']
+    soil = tree['soil_composition']
+    times = grouped_df['timestamp'].agg(['min', 'max'])
     folium.Circle(
-            location=[row.latitude, row.longitude],
-            tooltip=row.species_latin,
+        location=[lat, lon],
+        tooltip=f"{species} ({species_de})",
         radius=50,  # [m]
         color="black",
         weight=1,
@@ -57,7 +66,8 @@ for same, grouped_df in df[interesting_columns].drop_duplicates().groupby(specie
         opacity=1,
         fill_color="green",
         fill=False,  # gets overridden by fill_color
-            popup=f"Tree #{row.tree_number} ({row.species_latin})",
+        popup=f"Tree #{tree_id}, {species} ({species_de}). From {times['min']} to {times['max']}\n{table}",
+
     ).add_to(interactive_map)
 
 output_map = OUTPUT_DIR / INPUT_FILE.with_suffix('.html').name