adding color shading options

app.py

@@ -2,6 +2,10 @@ import ibis
 from ibis import _
 import streamlit as st
 
+import altair as alt
+
+
+
 st.set_page_config(layout="wide",
                    page_title="TPL LandVote",
                    page_icon=":globe:")
@@ -13,6 +17,14 @@ An experimental platform for visualizing data on ballot measures for conservatio
 
 '''
 
+dark_orange = 'rgba(171, 86, 1, 1)'   # dark orange - min value 
+light_orange = 'rgba(243, 211, 177, 1)' # light orange 
+grey = 'rgba(211, 211, 211, 1)'        # grey
+light_green = 'rgba(195, 219, 195, 1)' # light green 
+dark_green = 'rgba(65, 125, 65, 1)'    # dark green  - max value 
+
+dem_blue = "#1b46c2"
+rep_red = "#E81B23"
 
 ## Chatbot
 import os
@@ -34,6 +46,7 @@ agent = Agent(
 
 with st.sidebar:
 
+
     '''
     ## Data Assistant (experimental)
 
@@ -57,22 +70,14 @@ with st.sidebar:
         
 
 
+        
 # year = st.slider("Select a year", min_value=1988, max_value=2024, value=2022, step=2)
 year = st.slider("Select a year", min_value=1988, max_value=2024, value=2022, step=1)
 
-import leafmap.maplibregl as leafmap
-m = leafmap.Map(style="positron",   center=(-100, 40), zoom=3)
 
-# url = "https://huggingface.co/datasets/boettiger-lab/landvote/resolve/main/landvote_polygons.pmtiles"
 url = "https://huggingface.co/datasets/boettiger-lab/landvote/resolve/main/votes.pmtiles"
 parties = "https://huggingface.co/datasets/boettiger-lab/landvote/resolve/main/votes.parquet"
 
-dark_orange = 'rgba(171, 86, 1, 1)'   # dark orange - min value 
-light_orange = 'rgba(243, 211, 177, 1)' # light orange 
-grey = 'rgba(211, 211, 211, 1)'        # grey
-light_green = 'rgba(195, 219, 195, 1)' # light green 
-dark_green = 'rgba(65, 125, 65, 1)'    # dark green  - max value 
-
 con = ibis.duckdb.connect(extensions=["spatial"])
 
 party = (con
@@ -82,6 +87,7 @@ party = (con
 
 def get_passes(party):
     df = (party
+        .filter(_.year >= 2000)
         .group_by("year", "party")
         .aggregate(total=_.count(),
                    passes = (_.Status.isin(["Pass", "Pass*"]).sum())
@@ -93,62 +99,13 @@ def get_passes(party):
                 .else_(ibis.literal("#E81B23"))
                 .end()
         )
-        # # .select("year","party","percent_passed","color")
-    )
-    
-    df = df.to_pandas()
-    return df
-
-def get_summary(party, year):
-    total_measures = party.filter(_.year == year).count().execute()
-    
-    df = (party
-        .filter(_.year == year)
-        .mutate(
-            # Convert 'amount' from string with '$' and ',' to numeric
-            # amount_numeric=_.amount.replace('$', '').replace(',', '').cast('float64')
-        )
-        .group_by("party")
-        .aggregate(
-            total = _.count(),
-            percent_passed= (_.Status.isin(["Pass", "Pass*"]).sum() / _.count()).round(2),
-        )
-        .mutate(color=ibis.case()
-            .when(_.party == "DEMOCRAT", ibis.literal("#92c7f5"))
-            .else_(ibis.literal("#E81B23"))
-            .end())
     )
     
     df = df.to_pandas()
     return df
-    
-# def get_cumulative(party):
-    
-#     df = (party
-#         .select("year","amount","Status")
-#         # .mutate(
-#         #     # Convert 'amount' from string with '$' and ',' to numeric
-#         #     # amount_numeric=_.amount.replace('$', '').replace(',', '').cast('float64')
-#         # )
-#         # .group_by("party")
-#         # .aggregate(
-#         #     total = _.count(),
-#         #     percent_passed= (_.Status.isin(["Pass", "Pass*"]).sum() / _.count()).round(2),
-#         # )
-#         # .mutate(color=ibis.case()
-#         #     .when(_.party == "DEMOCRAT", ibis.literal("#92c7f5"))
-#         #     .else_(ibis.literal("#E81B23"))
-#         #     .end())
-#     )
-    
-#     df = df.to_pandas()
-#     return df
-
 
-import altair as alt
-import streamlit as st
 
-def plot(df_passes):
+def percent_chart(df_passes):
     chart = alt.Chart(df_passes).mark_line(strokeWidth=3).encode(
     x=alt.X('year:N', title='Year'),
     y=alt.Y('percent_passed:Q', title='Percent Passed'),
@@ -164,23 +121,20 @@ def plot(df_passes):
     st.altair_chart(chart, use_container_width=True)
 
 
-
-
 def funding_chart(party):
-
     df = (party
         .mutate(amount=_.amount.replace('$', '').replace(',', '').cast('float64'))
         .filter(_.Status.isin(["Pass", "Pass*"]))
         .group_by("year")
         .aggregate(total_funding=_.amount.sum())
         .order_by("year")
-        .mutate(cumulative_funding=_.total_funding.cumsum())
+        .mutate(cumulative_funding=_.total_funding.cumsum()/1e9)
         .execute()
         )
   
     chart = alt.Chart(df).mark_line(strokeWidth=3).encode(
         x=alt.X('year:N', title='Year'),
-        y=alt.Y('cumulative_funding:Q', title='Cumulative Funding'),
+        y=alt.Y('cumulative_funding:Q', title='Billions of Dollars'),
     ).properties(
         title='Cumulative Funding'
     )
@@ -188,21 +142,8 @@ def funding_chart(party):
     st.altair_chart(chart, use_container_width=True)
 
 
-
-style_municipals = {
-    "layers": [
-        {
-            "id": "cities",
-            "source": "municipal",
-            "source-layer": "municipal",
-            "type": "fill-extrusion",
-            "filter": [
-                "==",
-                ["get", "year"],
-                year,
-            ],
-            "paint": {
-                "fill-extrusion-color": [
+paint_fill = {
+                "fill-color": [
                     "case",
                     # if passed, color green
                     ["==", ["get", "Status"], "Pass"],
@@ -225,26 +166,11 @@ style_municipals = {
                         67, grey # 67 is the max of data.
                     ],
                     grey  # if no match 
-                ],
-                "fill-extrusion-height": ["*", ["get", "log_amount"], 5000],
+                ]
             }
-        },
-    ],
-}
-
-style_counties = {
-    "layers": [
-        {
-            "id": "counties",
-            "source": "county",
-            "source-layer": "county",
-            "type": "fill-extrusion",
-            "filter": [
-                "==",
-                ["get", "year"],
-                year,
-            ],
-            "paint": {
+
+
+paint_extrusion = {
                 "fill-extrusion-color": [
                     "case",
                     # if passed, color green
@@ -271,100 +197,166 @@ style_counties = {
                 ],
                 "fill-extrusion-height": ["*", ["get", "log_amount"], 5000],
             }
-        },
-    ],
-}
-
-style_states = {
-    "layers": [
-        {
-            "id": "states",
-            "source": "state",
-            "source-layer": "state",
-            "type": "fill",
-            "filter": [
-                "==",
-                ["get", "year"],
-                year,
-            ],
-            "paint": {
-                "fill-color": [
-                    "case",
-                    # if passed, color green
-                    ["==", ["get", "Status"], "Pass"],
-                    [
-                        "interpolate", ["linear"], [
-                            "to-number", ["slice", ["get", "yes"], 0, -1]  # convert 'yes' string to number
-                        ],
-                        50, grey,    
-                        55, light_green,     # higher yes % -> darker green
-                        100, dark_green     # 100 is the max of data 
-                    ],
-                    # if failed, color orange
-                    ["==", ["get", "Status"], "Fail"],
-                    [
-                        "interpolate", ["linear"], [
-                            "to-number", ["slice", ["get", "yes"], 0, -1]  # convert 'yes' string to number
-                        ],
-                        0, dark_orange,     # higher yes % -> lighter orange 
-                        50, light_orange,   
-                        67, grey # 67 is the max of data.
-                    ],
-                    grey  # if no match 
-                ]
-            }
-        },
-    ],
-}
 
 
-#states are 2D and transparent, thus added separately.
-m.add_pmtiles(
-    url,
-    style=style_states,
-    visible=True,
-    opacity=0.6,
-    tooltip=True,
-    fit_bounds=False
-)
-
-#states are 2D and transparent, thus added separately.
-m.add_pmtiles(
-    url,
-    style=style_counties,
-    visible=True,
-    opacity=1.0,
-    tooltip=True,
-    fit_bounds=False
-)
+def get_style_status(jurisdiction):
+    if jurisdiction == "State":
+        name = "state"
+        label = "states"
+        paint_type = paint_fill
+        layer_type = "fill"
+
+    elif jurisdiction == "County":
+        name = "county"
+        label = "counties"
+        paint_type = paint_extrusion
+        layer_type = "fill-extrusion"
+
+    else: 
+        name = "municipal"
+        label = "cities"
+        paint_type = paint_extrusion
+        layer_type = "fill-extrusion"
+
+    print(paint_type)
+    style = {
+        "layers": [
+            {
+                "id": label,
+                "source": name,
+                "source-layer": name,
+                "type": layer_type,
+                "filter": [
+                    "==",
+                    ["get", "year"],
+                    year,
+                ],
+                "paint": paint_type
+            },
+        ],
+    }
+    return style 
+
+
+def get_style_party(jurisdiction):
+    if jurisdiction == "State":
+        name = "state"
+        label = "states"
+    elif jurisdiction == "County":
+        name = "county"
+        label = "counties"
+
+    else: 
+        name = "municipal"
+        label = "cities"
+
+
+    style_party = {
+        "layers": [
+            {
+                "id": label,
+                "source": name,
+                "source-layer": name,
+                "type": "fill",
+                "filter": [
+                    "==",
+                    ["get", "year"],
+                    year,
+                ],
+                "paint": {
+                "fill-color": 
+                    {
+                    'property': 'party',
+                    'type': 'categorical',
+                    'stops': [
+                        ["DEMOCRAT", dem_blue],
+                        ["REPUBLICAN", rep_red],
+                    ]
+                    }
+                }
+            },
+        ],
+    }
+    return style_party
+
+
+
+style_options= ["Measure Status", "Political Party"]
+
+color_choice = st.radio("Color by:", style_options)
+            
+import leafmap.maplibregl as leafmap
+m = leafmap.Map(style="positron",   center=(-100, 40), zoom=3)
 
+if color_choice == "Measure Status":
 
-m.add_pmtiles(
+        #states are 2D and transparent, thus added separately.
+    m.add_pmtiles(
+        url,
+        style=get_style_status("States"),
+        visible=True,
+        opacity=0.6,
+        tooltip=True,
+        fit_bounds=False
+    )
+    
+    #states are 2D and transparent, thus added separately.
+    m.add_pmtiles(
+        url,
+        style=get_style_status("County"),
+        visible=True,
+        opacity=1.0,
+        tooltip=True,
+        fit_bounds=False
+    )
+    
+    
+    m.add_pmtiles(
+        url,
+        style=get_style_status("Municipal"),
+        visible=True,
+        opacity=1.0,
+        tooltip=True,
+        fit_bounds=False
+    )
+    
+else:
+    m.add_pmtiles(
     url,
-    style=style_municipals,
+    style=get_style_party("States"),
     visible=True,
-    opacity=1.0,
+    opacity=0.6,
     tooltip=True,
     fit_bounds=False
-)
-
-
+    )
+    
+    m.add_pmtiles(
+        url,
+        style=get_style_party("County"),
+        visible=True,
+        opacity=1.0,
+        tooltip=True,
+        fit_bounds=False
+    )
+    
+    
+    m.add_pmtiles(
+        url,
+        style=get_style_party("Municipal"),
+        visible=True,
+        opacity=1.0,
+        tooltip=True,
+        fit_bounds=False
+    )
+    
+    
 m.add_layer_control()
+
 m.to_streamlit()
 
 df_passes = get_passes(party)
-# st.dataframe(df_passes)
-plot(df_passes)
-
-
-df = get_summary(party, year)
-
-# st.line_chart(df_passes, x= "year",y = "percent_passed",color="color")
-
-# st.bar_chart(df, x= "party",y = "percent_passed",color="color")
-# Assuming df is your dataframe with 'year', 'amount', and 'Status' columns
-# df_fund = get_cumulative(party)
-funding_chart(party)
+percent_chart(df_passes)
+funding_chart(party.filter(_.year >= 2000))
 
 
 # st.divider()