Update app.py

app.py

@@ -79,18 +79,20 @@ def geocode(address):
     return lat, lon
 
 
+
 #Side Bar
-address = st.sidebar.text_input(
-    "Address", "Dallas, TX")
-date = st.sidebar.date_input(
-    "Loss Date",  pd.Timestamp(2023, 7, 14), key='date')
-date_str = date.strftime("%Y%m%d")
+address = st.sidebar.text_input("Address", "Dallas, TX")
+date = st.sidebar.date_input("Loss Date (Max)",  pd.Timestamp(2023, 7, 14), key='date')
+show_data = st.sidebar.selectbox('Show Data At Least Within:', ('Show All', '1 Mile', '3 Miles', '5 Miles'))
+show_data='3 Miles'
 
 #Geocode Addreses
+date_str=date.strftime("%Y%m%d")
+
 lat, lon = geocode(address)
 
 #Filter Data
-df_hail_cut = get_data(lat, lon, date_str)
+df_hail_cut = get_data(lat,lon, date_str)
 
 
 df_hail_cut["Lat_address"] = lat
@@ -98,6 +100,7 @@ df_hail_cut["Lon_address"] = lon
 df_hail_cut['Miles to Hail'] = [
     distance(i) for i in df_hail_cut[['LAT', 'LON', 'Lat_address', 'Lon_address']].values]
 df_hail_cut['MAXSIZE'] = df_hail_cut['MAXSIZE'].round(1)
+
 df_hail_cut = df_hail_cut.query("`Miles to Hail`<10")
 df_hail_cut['Category'] =  np.where(df_hail_cut['Miles to Hail'] < 1, "Within 1 Mile",
                                             np.where(df_hail_cut['Miles to Hail'] < 3, "Within 3 Miles",
@@ -110,15 +113,21 @@ df_hail_cut_group = pd.pivot_table(df_hail_cut, index='Date_utc',
                                    aggfunc='max')
 
 cols = df_hail_cut_group.columns
-cols_focus = [ "Within 1 Mile", "Within 3 Miles",
+cols_focus = [ "Within 1 Mile","Within 3 Miles",
               "Within 5 Miles", "Within 10 Miles"]
 
 missing_cols = set(cols_focus)-set(cols)
 for c in missing_cols:
     df_hail_cut_group[c] = np.nan
+    
+#Filter
+df_hail_cut_group2 = df_hail_cut_group[cols_focus]
 
-df_hail_cut_group2 = df_hail_cut_group[cols_focus].query(
-    "`Within 3 Miles`==`Within 3 Miles`")
+if show_data=='Show All':
+    pass
+else:
+    df_hail_cut_group2 = df_hail_cut_group2.query(
+    f"`Within {show_data}`==`Within {show_data}`")
 
 for i in range(len(cols_focus)-1):
     df_hail_cut_group2[cols_focus[i+1]] = np.where(df_hail_cut_group2[cols_focus[i+1]].fillna(0) <
@@ -129,8 +138,8 @@ for i in range(len(cols_focus)-1):
 
 df_hail_cut_group2 = df_hail_cut_group2.sort_index(ascending=False)
 
-df_hail_cut_group2.index = pd.to_datetime(
-    df_hail_cut_group2.index, format='%Y%m%d').strftime("%Y-%m-%d")
+df_hail_cut_group2.index=pd.to_datetime(df_hail_cut_group2.index,format='%Y%m%d')
+df_hail_cut_group2.index=df_hail_cut_group2.index.strftime("%Y-%m-%d")
 
 
 #Map Data