Update app.py

app.py

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+from cmath import pi
+from json import load, tool
+from os import stat
+from telnetlib import RCP
+import streamlit as st
+import pandas as pd
+import numpy as np
+import pydeck as pdk
+from typing import Dict, Union
+import streamlit.components.v1 as components
+#import streamlit_shared_funcs as my
+
+st.title("Live 3D Map")
+location = st.checkbox('Location Filter')
+queried_zip_code = None
+queried_city = None
+queried_state = None
+queried_age = None
+if location:
+    queried_zip_code = st.text_input('Zip Code:')
+    queried_city = st.text_input('City')
+    queried_state = st.selectbox('State:',  ('AL', 'AK', 'AZ', 'AR', 'AS','CA','CO','CT','DE','DC','FL','GA','GU','HI','ID','IL',
+    'IN','IA','KS','KY','LA','ME','MD','MA','MI','MN','MS','MO','MT','NE','NV','NH','NJ','NM','NY','NC','ND','CM','OH',
+    'OK','OR','PA','PR','RI','SC','SD','TN','TX','UT','VT','VA','VI','WA','WV','WI','WY'))
+ageBox = st.checkbox("Age Filter")
+if ageBox:
+    queried_age = st.slider("Age",0,200,(0,200))
+
+queried_male = st.checkbox("Male",value=True)
+queried_female = st.checkbox("Female",value=True)
+
+@st.cache(allow_output_mutation=True)
+def gen_load() -> pd.DataFrame:
+    df = my.get_data()
+    return df
+
+@st.cache(allow_output_mutation=True)
+def gen_load_old() -> pd.DataFrame:
+    # file = pd.read_csv('us-zip-code-latitude-and-longitude.txt',names = ['Zip','City','State','lat','lon','Timezone',"Daylight Savings", "Geo point"], skiprows=1, delimiter=";")
+    filename = "US.txt"
+    file = pd.read_csv(filename,names = ['Country','Zip','City','State','Abb','Name1','Code1','Name2','Code2','lat','lon','Accuracy'], delimiter="\t",usecols=["Zip","City","State","Abb","lat","lon"])
+    #file = pd.read_csv('US.txt',names = ['Country','Zip','City','State','Abb','Name1','Code1','Name2','Code2','lat','lon','Accuracy'], delimiter="\t",usecols=["Zip","City","State","Abb","lat","lon"])
+    file['Zip'] = file['Zip'].astype(str).str.zfill(5)
+    w = lambda x: (x[-5:])
+    filename = "NPIProviders.xlsx"
+    df = pd.read_excel('...xlsx',header = None,names = ['Zip','FCTIN','FCName', 'Procedures','Age','Gender','Admitted','Form','Cohort'], skiprows=1,converters={'Zip':w },usecols="A,B,C,D,E,F,G,H,I")   
+    df = df.merge(file, left_on = 'Zip', right_on = 'Zip', how='inner')
+    df = df.fillna(" ")
+    return df
+
+#queried_ctss = st.multiselect("Ctss",options=gen_load()["Ctss"].value_counts().reset_index())
+
+@st.cache(allow_output_mutation=True)
+def load_data(state = None,zip_code = None,city = None,age = None,male  = None,female = None,selected_cohorts = None) -> pd.DataFrame:
+    df = gen_load()
+    try:
+        if (male or female) and not (male and female):
+            df = df.loc[df['Gender'] == ("Male" if male else ("Female" if female else ""))]
+        elif not (male or female):
+            df = df.loc[df['Gender'] == "(null)"]
+    except:
+        pass
+    try:
+        df = df[(df['Age'].gt(age[0]) & df['Age'].lt(age[1]))]
+    except:
+        pass
+    try:
+        if zip_code or state or city:
+            val = "Zip" if zip_code != "" else "City" if city != "" else "Abb"
+            df = df.loc[df[val] == (zip_code or city or state)]
+    except:
+        pass
+
+    try:
+        if len(selected_cohorts) > 0:
+            df = df.loc[df['Cohort'].isin(selected_ctss)]
+                
+    except:
+        pass
+
+    value_counts = df["FCName"].value_counts()
+    df2 = pd.DataFrame(value_counts)
+    df2 = df2.reset_index()
+    df2.columns = ['FCName', 'Count']
+    df = df.merge(df2, left_on = 'FCName', right_on = 'FCName',how='left')
+
+    return df
+
+def mapF(data):
+    geo = data.iloc[0]
+    lat = float(geo['lat'])
+    lon = float(geo['lon'])
+    max = data['Count'].max()
+    view_state = pdk.ViewState(
+        pitch = 40.5,
+        bearing = -27.36,
+        latitude = lat,
+        longitude = lon,
+        zoom = 4,
+    )
+
+    layer = pdk.Layer(
+            'ColumnLayer',
+            data=data,
+            get_position='[lon, lat]',
+            pickable=True,
+            extruded=True,
+            auto_highlight=True,
+            get_elevation="Count",
+            # cell_size=200,
+            radius = 1000,
+            elevation_scale=1000000/ max,
+            get_fill_color='[255, 255 - (Count/3500) * 255, 0,100]',
+            coverage=10
+    )                 
+
+    r = pdk.Deck(
+        # map_style = x,
+        layers=[layer],
+        initial_view_state= view_state,
+        tooltip = {
+            "html": "<b>City,State:</b> {City} </br> <b>Procedures:</b> {Count} </br> <b>F:</b> {FCName}",
+           "style": {
+                "backgroundColor": "steelblue",
+                "color": "white"
+           }
+        },
+    )
+    # st.pydeck_chart(r)
+    components.html(r.to_html(as_string=True), height=600)
+
+data = load_data(state=queried_state,zip_code=queried_zip_code,city=queried_city,age=queried_age,male=queried_male,female=queried_female,selected_cohorts=queried_cohorts)
+
+if st.checkbox('Display data ?'):
+    data
+
+mapFs(data)
+