tweak tooltip

app.py

@@ -18,6 +18,16 @@ import ibis
 from ibis import _
 import ibis.selectors as s
 
+st.set_page_config(layout="wide", page_title="Protected Areas Explorer", page_icon=":globe:")
+
+#pad_pmtiles = "https://data.source.coop/cboettig/pad-us-3/pad-stats.pmtiles"
+#parquet = "https://data.source.coop/cboettig/pad-us-3/pad-stats.parquet"
+#pad_pmtiles = "https://huggingface.co/spaces/boettiger-lab/pad-us/resolve/main/pad-stats.pmtiles"
+#parquet = "https://huggingface.co/spaces/boettiger-lab/pad-us/resolve/main/pad-stats.parquet"
+pad_pmtiles = "https://huggingface.co/datasets/boettiger-lab/pad-us-3/resolve/main/pad-stats.pmtiles"
+parquet = "https://huggingface.co/datasets/boettiger-lab/pad-us-3/resolve/main/pad-stats.parquet"
+
+
 # defaults, consider user palette via st.color_picker()
 private_color = "#DE881E" # orange #"#850101" # red
 tribal_color = "#BF40BF" # purple
@@ -32,20 +42,66 @@ style_choice = "Manager Type"
 us_lower_48_area_m2 = 7.8e+12
 
 
-st.set_page_config(layout="wide", page_title="Protected Areas Explorer", page_icon=":globe:")
+@st.cache_resource
+def ibis_connection(parquet):
+    return ibis.read_parquet(parquet)
+pad_data = ibis_connection(parquet)
+
+@st.cache_data()
+def summary_table(column, colors):
+    df = (pad_data
+        .rename(area = "area_square_meters")
+        .group_by(_[column])
+        .aggregate(hectares_protected =  (_.area.sum() / 10000).round(),
+                   percent_protected =  100 * _.area.sum() / us_lower_48_area_m2,
+                   mean_richness = (_.richness * _.area).sum() / _.area.sum(),
+                   mean_rsr = (_.rsr * _.area).sum() / _.area.sum(),
+                   carbon_lost = (_.deforest_carbon * _.area).sum() / _.area.sum(),
+                   crop_expansion = (_.crop_expansion * _.area).sum() / _.area.sum(),
+                   human_impact =  (_.human_impact * _.area).sum() / _.area.sum(),
+                   )
+        .mutate(percent_protected = _.percent_protected.round(1))
+        .inner_join(colors, column)
+        )
+    df = df.to_pandas()
+    df[column] = df[column].astype(str)
+    return df
+
+def bar_chart(df, x, y):
+    chart = alt.Chart(df).mark_bar().encode(
+        x=x,
+        y=y,
+        color=alt.Color('color').scale(None)
+    ).properties(width="container", height=300)
+    return chart
+
+
+def area_plot(df, column):
+    base = alt.Chart(df).encode(
+        alt.Theta("percent_protected:Q").stack(True),
+    )
+    pie = ( base
+           .mark_arc(innerRadius= 40, outerRadius=70)
+           .encode(alt.Color("color:N").scale(None).legend(None),
+                   tooltip=['percent_protected', 'hectares_protected', column])
+    )
+    text = ( base
+            .mark_text(radius=60, size=12, color="white")
+            .encode(text = column + ":N")
+    )
+    plot = pie # pie + text
+    return plot.properties(width=180, height=180)
+
+
+
+
+
 
 '''
 # US Protected Area Database Explorer
 
 '''
 
-#pad_pmtiles = "https://data.source.coop/cboettig/pad-us-3/pad-stats.pmtiles"
-#parquet = "https://data.source.coop/cboettig/pad-us-3/pad-stats.parquet"
-pad_pmtiles = "https://huggingface.co/spaces/boettiger-lab/pad-us/resolve/main/pad-stats.pmtiles"
-parquet = "https://huggingface.co/spaces/boettiger-lab/pad-us/resolve/main/pad-stats.parquet"
-pad_pmtiles = "https://huggingface.co/datasets/boettiger-lab/pad-us-3/resolve/main/pad-stats.pmtiles"
-parquet = "https://huggingface.co/datasets/boettiger-lab/pad-us-3/resolve/main/pad-stats.parquet"
-
 
 m = leafmap.Map(center=[35, -100], zoom=4, layers_control=True)
 
@@ -66,14 +122,6 @@ mutate(percent_protected = _.percent_protected.round())
 )
 '''
 
-def bar_chart(df, x, y):
-    chart = alt.Chart(df).mark_bar().encode(
-        x=x,
-        y=y,
-        color=alt.Color('color').scale(None)
-    ).properties(width="container", height=300)
-    return chart
-
 manager = {
             'property': 'manager_type',
             'type': 'categorical',
@@ -320,9 +368,10 @@ select_colors = {
                 "Manager Type": manager["stops"],
                 "Fee/Easement": easement["stops"],
                 "Public Access": access["stops"],
-                "Mean Richness": manager["stops"],
-                "Mean RSR": manager["stops"],
-                "custom": manager["stops"]}
+                "Mean Richness": gap["stops"],
+                "Mean RSR": gap["stops"],
+                "custom": gap["stops"]}
+                
 colors = (ibis
           .memtable(select_colors[style_choice], columns = [column, "color"])
           .to_pandas()
@@ -337,45 +386,8 @@ with main:
     with map_col:
         m.to_streamlit(height=700)
 
-
-    @st.cache_resource
-    def ibis_connection(parquet):
-        return ibis.read_parquet(parquet)
-    pad_data = ibis_connection(parquet)
-
-    @st.cache_data()
-    def summary_table(column = column, colors = colors):
-        df = (pad_data
-            .rename(area = "area_square_meters")
-            .group_by(_[column])
-            .aggregate(percent_protected =  100 * _.area.sum() / us_lower_48_area_m2,
-                        mean_richness = (_.richness * _.area).sum() / _.area.sum(),
-                        mean_rsr = (_.rsr * _.area).sum() / _.area.sum(),
-                        carbon_lost = (_.deforest_carbon * _.area).sum() / _.area.sum(),
-                        crop_expansion = (_.crop_expansion * _.area).sum() / _.area.sum(),
-                        human_impact =  (_.human_impact * _.area).sum() / _.area.sum(),
-                        )
-            .mutate(percent_protected = _.percent_protected.round())
-            .inner_join(colors, column)
-            )
-        df = df.to_pandas()
-        df[column] = df[column].astype(str)
-        return df
-
     df = summary_table(column, colors)
     total_percent = df.percent_protected.sum()
-
-
-    base = alt.Chart(df).encode(
-        alt.Theta("percent_protected:Q").stack(True),
-        alt.Color("color:N").scale(None).legend(None)
-    )
-
-    area_chart = (
-    base.mark_arc(innerRadius=40, outerRadius=70)
-    ).properties(width=180, height=180)
-
-
     richness_chart = bar_chart(df, column, 'mean_richness')
     rsr_chart = bar_chart(df, column, 'mean_rsr')
     carbon_lost = bar_chart(df, column, 'carbon_lost')
@@ -387,7 +399,7 @@ with main:
             col1, col2, col3 = st.columns(3)
             with col1:
                 f"{total_percent}% Continental US Covered"
-                st.altair_chart(area_chart, use_container_width=False)
+                st.altair_chart(area_plot(df, column), use_container_width=False)
 
             with col2:
                 "Species Richness"