app.py

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)