Update app.py

revise title and notes; remove sig filtering from topline numbers; fix errors with download

app.py

@@ -38,10 +38,10 @@ ui.include_css( Path(__file__).parent.joinpath("www") / "style.css")
 
 
 # this text appears in the browser tab
-TITLE = "CRA Window Tracker - GW Regulatory Studies Center"
+TITLE = "CRA Window Exploratory Dashboard - GW Regulatory Studies Center"
 
 # page header above main content
-HEADER = "Rules in the Congressional Review Act (CRA) Window"
+HEADER = "Congressional Review Act (CRA) Window Exploratory Dashboard"
 page_header = ui.HTML(
     f"""
     <div class="header">
@@ -82,7 +82,7 @@ with ui.sidebar(open={"desktop": "open", "mobile": "closed"}):
 
     with ui.tooltip(placement="right", id="window_tooltip"):
         ui.input_date("start_date", "Select start of window", value=WINDOW_OPEN_DATE, min=START_DATE, max=date.today())
-        "The estimated CRA window open date is May 23. See the notes for more information."
+        "The estimated lookback window open date is May 22. This dashboard allows users to explore how different lookback window dates would affect the set of rules available for congressional review. See the notes for more information."
 
     ui.input_select("menu_significant", "Select rule significance", choices=["all", "3f1-significant", "other-significant"], selected="all", multiple=True, size=3)
 
@@ -127,7 +127,7 @@ with ui.navset_card_underline(title=""):
         with ui.card(full_screen=True):
             @render.data_frame
             def table_rule_detail():
-                df = filtered_df().copy()
+                df = filter_significance().copy()
                 df.loc[:, "date"] = df.loc[:, "publication_date"].apply(lambda x: f"{x.date()}")
                 char, limit = " ", 10
                 df.loc[:, "title"] = df["title"].apply(lambda x: x if len(x.split(char)) < (limit + 1) else f"{char.join(x.split(char)[:limit])}...")
@@ -234,22 +234,24 @@ with ui.accordion(open=False):
                 "title", 
                 "type", 
                 "action", 
-                "abstract", 
-                "docket_ids", 
                 "json_url", 
                 "html_url", 
                 "agencies", 
                 "independent_reg_agency", 
-                "parent_slug", 
-                "subagency_slug", 
+                "parent_agencies", 
+                "subagencies", 
                 "president_id", 
                 "significant", 
                 "3f1_significant", 
                 "other_significant"
                 )
             ):
+            filt_df = filtered_df().copy()
+            filt_df.loc[:, "agencies"] = filt_df.loc[:, "agency_slugs"].apply(lambda x: "; ".join(x))
+            filt_df.loc[:, "parent_agencies"] = filt_df.loc[:, "parent_slug"].apply(lambda x: "; ".join(x))
+            filt_df.loc[:, "subagencies"] = filt_df.loc[:, "subagency_slug"].apply(lambda x: "; ".join(x))
             await asyncio.sleep(0.25)
-            yield filtered_df().loc[:, output_cols].to_csv(index=False)
+            yield filt_df.loc[:, [c for c in output_cols if c in filt_df.columns]].to_csv(index=False)
 
 # notes
 with ui.accordion(open=False):
@@ -258,9 +260,14 @@ with ui.accordion(open=False):
         
         ui.markdown(
             f"""
-            Rule data retrieved from the [Federal Register API](https://www.federalregister.gov/developers/documentation/api/v1).
+            Rule data are retrieved daily from the [Federal Register API](https://www.federalregister.gov/developers/documentation/api/v1), which publishes new editions of the Federal Register each business day. 
             
-            The window for the CRA lookback period is [estimated](https://www.huntonak.com/the-nickel-report/federal-agencies-face-looming-congressional-review-act-deadline) to open on May 23, 2024.
+            The [Congressional Review Act](http://uscode.house.gov/view.xhtml?req=granuleid%3AUSC-prelim-title5-chapter8&saved=%7CKHRpdGxlOjUgc2VjdGlvbjo4MDEgZWRpdGlvbjpwcmVsaW0pIE9SIChncmFudWxlaWQ6VVNDLXByZWxpbS10aXRsZTUtc2VjdGlvbjgwMSk%3D%7CdHJlZXNvcnQ%3D%7C%7C0%7Cfalse%7Cprelim&edition=prelim) (CRA) “lookback window” refers to the period starting [60 working days](https://crsreports.congress.gov/product/pdf/R/R46690#page=8) (either session days in the Senate or legislative days in the House of Representatives) before the current session of Congress adjourns and ending the day the subsequent session of Congress first convenes. 
+            Rules that are published in the Federal Register and submitted to Congress during that time period are made available for review in the subsequent session of Congress. 
+            
+            Due to the retrospective calculation of the window, lookback window dates prior to Congress adjourning are inherently estimates. 
+            Based on the published Congressional calendar for the second session of the 118th Congress, the current lookback window date [estimate](https://www.huntonak.com/the-nickel-report/federal-agencies-face-looming-congressional-review-act-deadline) is **May 22, 2024**. 
+            This dashboard allows users to explore how different lookback window dates would affect the set of rules available for congressional review.
             """
             )
 
@@ -288,6 +295,16 @@ def filtered_df():
         bool_agency = [True if sum(selected in agency for selected in input.menu_agency()) > 0 else False for agency in filt_df["parent_slug"]]
         filt_df = filt_df.loc[bool_agency]
     
+    # return filtered dataframe
+    return filt_df
+
+
+@reactive.calc
+def filter_significance():
+
+    # get data filtered by date and agency
+    filt_df = filtered_df()
+
     # filter significance
     bool_ = []
     if (input.menu_significant() is not None) and ("all" not in input.menu_significant()):
@@ -296,21 +313,21 @@ def filtered_df():
         if "other-significant" in input.menu_significant():
             bool_.append((filt_df["other_significant"] == 1).to_numpy())
         filt_df = filt_df.loc[array(bool_).any(axis=0)]
-    
+
     # return filtered dataframe
     return filt_df
 
 
 @reactive.calc
 def grouped_df_month():
-    filt_df = filtered_df()
+    filt_df = filter_significance()
     grouped = groupby_date(filt_df, significant=GET_SIGNIFICANT)
     return grouped
 
 
 @reactive.calc
 def grouped_df_day():
-    filt_df = filtered_df()
+    filt_df = filter_significance()
     date_col = "publication_date"
     grouped = groupby_date(filt_df, group_col=date_col, significant=GET_SIGNIFICANT)
     grouped = pad_missing_dates(
@@ -327,7 +344,7 @@ def grouped_df_day():
 
 @reactive.calc
 def grouped_df_week():
-    filt_df = filtered_df()
+    filt_df = filter_significance()
     filt_df = add_weeks_to_data(filt_df)
     try:
         grouped = groupby_date(filt_df, group_col=("week_number", "week_of"), significant=GET_SIGNIFICANT)
@@ -347,7 +364,7 @@ def grouped_df_week():
 
 @reactive.calc
 def grouped_df_agency():
-    filt_df = filtered_df()
+    filt_df = filter_significance()
     grouped = groupby_agency(filt_df, metadata=METADATA, significant=GET_SIGNIFICANT)
     return grouped