pretty charts!

app.py

@@ -80,7 +80,25 @@ party = (con
             .cast({"geometry": "geometry"})
             )
 
+def get_passes(party):
+    df = (party
+        .group_by("year", "party")
+        .aggregate(total=_.count(),
+                   passes = (_.Status.isin(["Pass", "Pass*"]).sum())
+                  )
+        .mutate(
+            percent_passed=(_.passes / _.total).round(2),
+            color=ibis.case()
+                .when(_.party == "DEMOCRAT", ibis.literal("#2e4a93"))
+                .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()
     
@@ -88,25 +106,88 @@ def get_summary(party, year):
         .filter(_.year == year)
         .mutate(
             # Convert 'amount' from string with '$' and ',' to numeric
-            amount_numeric=_.amount.replace('$', '').replace(',', '').cast('float64')
+            # amount_numeric=_.amount.replace('$', '').replace(',', '').cast('float64')
         )
         .group_by("party")
         .aggregate(
-            percent_passed= (_.Status.isin(["Pass", "Pass*"]).sum() / total_measures).round(2),
-            approved_funds= ibis.case()
-                            .when(_.Status.isin(["Pass", "Pass*"]), _.amount_numeric)
-                            .else_(ibis.literal(0))
-                            .end()
-                            .sum()
+            total = _.count(),
+            percent_passed= (_.Status.isin(["Pass", "Pass*"]).sum() / _.count()).round(2),
         )
         .mutate(color=ibis.case()
-            .when(_.party == "DEMOCRAT", ibis.literal("#083A90"))
+            .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):
+    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'),
+    color=alt.Color('party:N',  # Map 'party' to color
+                    scale=alt.Scale(domain=["DEMOCRAT", "REPUBLICAN"], 
+                                    range=["#1b46c2", "#E81B23"]),
+                    legend=alt.Legend(title="Party")
+                   )
+    ).properties(
+        title='% of Measures Passed'
+    )
+    
+    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())
+        .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'),
+    ).properties(
+        title='Cumulative Funding'
+    )
+    
+    st.altair_chart(chart, use_container_width=True)
+
+
 
 style_municipals = {
     "layers": [
@@ -270,12 +351,21 @@ m.add_pmtiles(
 
 m.add_layer_control()
 m.to_streamlit()
-# st.dataframe(df)
+
+df_passes = get_passes(party)
+# st.dataframe(df_passes)
+plot(df_passes)
+
 
 df = get_summary(party, year)
-st.bar_chart(df, x= "party",y = "percent_passed",color="color")
 
-st.bar_chart(df, x= "party",y = "approved_funds",color="color")
+# 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)
+
 
 # st.divider()
 # footer = st.container()