adding map

Author: amandaha8

gtfs_digest/27_fct_monthly_schedule_route_direction_summary.ipynb

@@ -1274,7 +1274,13 @@
    "execution_count": 48,
    "id": "be5a3d9c-aaac-49fe-9eee-124325782c24",
    "metadata": {
-    "tags": []
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "parameters"
+    ]
    },
    "outputs": [],
    "source": [

gtfs_digest/31_download_prep_data.ipynb

@@ -1889,7 +1889,15 @@
    "cell_type": "code",
    "execution_count": 76,
    "id": "1439705e-d3b5-4036-8719-62725c257d1f",
-   "metadata": {},
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "parameters"
+    ]
+   },
    "outputs": [],
    "source": [
     "monthly_routes_gdf = gpd.read_parquet(monthly_routes_url,storage_options={\"token\": credentials.token})"

gtfs_digest/32_districts.ipynb

@@ -42,6 +42,7 @@ def create_text_table(df: pd.DataFrame) -> pd.DataFrame:
     text_table_df["Direction"] = text_table_df.Direction.astype(str)
 
     return text_table_df
+
 
 """
 Charts
@@ -143,7 +144,7 @@ def create_hourly_summary(df: pd.DataFrame, day_type: str):
         scale=alt.LegendResolveMap(color=alt.ResolveMode("independent"))
     )
 )
-    chart = _report_operator_visuals.configure_chart(
+    chart = _portfolio_charts.configure_chart(
     chart,
     width=400,
     height=250,
@@ -166,6 +167,7 @@ def create_route_dropdown(df: pd.DataFrame):
     )
     return xcol_param
 
+
 def create_scheduled_minutes(df: pd.DataFrame):
     df2 = df.loc[df["Day Type"] == "Weekday"]
     chart_dict = readable_dict.avg_scheduled_minutes
@@ -219,6 +221,7 @@ def create_scheduled_minutes(df: pd.DataFrame):
     chart = alt.hconcat(dir_0_chart, dir_1_chart)
     return chart
 
+
 def create_scheduled_trips(df: pd.DataFrame):
     df2 = df.loc[df["Day Type"] == "Weekday"]
     chart_dict = readable_dict.scheduled
@@ -272,6 +275,7 @@ def create_scheduled_trips(df: pd.DataFrame):
     chart = alt.hconcat(dir_0_chart, dir_1_chart)
     return chart
 
+
 def create_frequency(df: pd.DataFrame):
     df2 = df.loc[df["Day Type"] == "Weekday"]
     chart_dict = readable_dict.frequency
@@ -325,6 +329,20 @@ def create_frequency(df: pd.DataFrame):
     chart = alt.hconcat(dir_0_chart, dir_1_chart)
     return chart
 
+
+def text_table(df: pd.DataFrame) -> alt.Chart:
+
+    # Create the chart
+    text_chart = (
+        alt.Chart(df)
+        .mark_text()
+        .encode(x=alt.X("Zero:Q", axis=None), y=alt.Y("combo_col", axis=None))
+    )
+
+    text_chart = text_chart.encode(text="combo_col:N")
+    return text_chart
+
+    
 def create_text_graph(df: pd.DataFrame):
     chart_dict = readable_dict.avg_scheduled_minutes
 
@@ -361,5 +379,5 @@ def create_text_graph(df: pd.DataFrame):
         .add_params(selection)
         .transform_filter(selection)
     )
-
-    return chart
+    return chart
+    

gtfs_digest/_new_operator_report_utils.py

@@ -15,6 +15,8 @@ hourly_summary:
     subtitle: "Use the legend to highlight a particular month and hover over the line for additional information."
     tooltip: ["Date", 'Departure Hour', "N Trips"] 
     colors: []
+background_graph:
+    colors: ${color_palettes.full_color_scale} 
 
 # fct_monthly_operator_summary
 trip_updates_minute:

gtfs_digest/new_readable.yml

@@ -4,7 +4,15 @@
    "cell_type": "code",
    "execution_count": 1,
    "id": "89102e7d-7aa7-4897-ba5d-e09d0bd08fac",
-   "metadata": {},
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "parameters"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%capture\n",