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()
    df = pd.read_csv('US.txt')
    return df

#AI Emotional State Score: Anxiety, Confusion, Trepidation, Fear, Guilt

@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['Zip'] = file['Zip'].astype(str).str.zfill(5)
    w = lambda x: (x[-5:])
    filename = "NPIProviders.xlsx"
    df = pd.read_csv('Locations.csv',header = None,names = ['Zip','TIN','Name', 'Services','Age','Gender','StartDate','Questions','Entity'], skiprows=1,converters={'Zip':w },usecols="A,B,C,D,E,F,G,H,I")  
    'Zip','TIN','Name', 'Services','Age','Gender','StartDate','Questions','Entity'
     
    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):
    print(data)
    geo = data.iloc[0]
    print(geo)
    #print(geo[7], geo[8])
    #lat = float(geo['lat'])
    #lon = float(geo['lon'])
    lat = float(geo[7])
    lon = float(geo[8])
    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>Services:</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)

if st.checkbox('Display data ?'):
    data

mapF(data)