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sb_dashboard
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import streamlit as st
import numpy as np
import plotly.figure_factory as ff
import plotly.express as px
import pandas as pd
import plotly.graph_objects as go
import streamlit_authenticator as stauth
from st_aggrid import GridOptionsBuilder, AgGrid, GridUpdateMode, DataReturnMode
from streamlit_extras.stylable_container import stylable_container 
from streamlit_extras.metric_cards import style_metric_cards
import warnings
from streamlit_extras.switch_page_button import switch_page
import pickle
import time
import plotly.io as pio
import os
import requests

def check_and_download_file(file_path, url):
    if os.path.exists(file_path):
        print(f"The file '{file_path}' already exists.")
    else:
        print(f"The file '{file_path}' does not exist. Downloading...")
        try:
            response = requests.get(url)
            response.raise_for_status()  # Check if the request was successful
            with open(file_path, 'wb') as file:
                file.write(response.content)
            print(f"File downloaded successfully and saved as '{file_path}'.")
        except requests.exceptions.RequestException as e:
            print(f"An error occurred while downloading the file: {e}")

# Example usage


pio.templates.default = 'plotly' 
warnings.filterwarnings('ignore')

st.set_page_config(layout="wide")
color = {'Unknown/Other':'#3a393a', 'Black or African American': '#2993A3', 'White':'#666766', 'Native American':'#f4b780', 'Hispanic':'#a0cd7c', 'Pacific Islander':'#a680ba','Asian':'#f37e85'}

file = open("login_state.pkl",'rb')
st.session_state['logged_in'] = pickle.load(file)
file.close()

#----------------------------NavBar-------------------------------#
hide_menu_style = """
        <style>
        #MainMenu {visibility: hidden;}
        header {visibility: hidden;}
        </style>
        """
st.markdown(hide_menu_style, unsafe_allow_html=True)

if st.session_state.get("logged_in") == False or st.session_state.get("logged_in") == None:
    st.switch_page("app.py")

st.markdown('<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">', unsafe_allow_html=True)
st.markdown("""
            <head>
            <script defer src="https://pyscript.net/latest/pyscript.js"></script>
            </head>
<nav class="navbar fixed-top navbar-expand-lg navbar-dark" style="background-color: #3498DB;">
  <a class="navbar-brand" href="https://www.ipr.northwestern.edu/who-we-are/faculty-experts/redbird.html" target="_blank">RJA Dashboard</a>
  <button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation">
    <span class="navbar-toggler-icon"></span>
  </button>
  <div class="collapse navbar-collapse" id="navbarNav" style="width:100%;">
    <ul class="navbar-nav">
      <li class="nav-item active">
        <a class="nav-link disabled" href="https://sanbernardinorja.streamlit.app/page_0" target="_self">Arrest Summary<span class="sr-only">(current)</span></a>
      </li>
      <li class="nav-item">
        <a class="nav-link" href="https://sanbernardinorja.streamlit.app/page_1" target="_self">Charge By Race</a>
      </li>
      <li class="nav-item">
        <a class="nav-link" href="https://sanbernardinorja.streamlit.app/page_2" target="_self">Download Data</a>
      </li>
      </ul>
      <ul class="navbar-nav ml-auto">
        <li class="nav-item mr-auto" style="padding-left:5px;padding-right:5px;outline-color:#f0f2f5;border: 2px solid white;border-radius:10px;"> 
            <a class="nav-link" href="https://sanbernardinorja.streamlit.app/" target="_self" >Logout</a>
     </li>
    </ul>
  </div>

</nav>

""", unsafe_allow_html=True)

#------------------------------- Metric Cards ------------------------#
file_path = "Population.csv"
url = 'https://rja-sanbernardino.s3.us-east-1.amazonaws.com/dashboard/Population.csv?response-content-disposition=inline&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEM%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIFmSNoakzC4hQlNV2NcIpccGqt1lJiw7dumO58Kv5HHaAiBCHRkYbyL09%2BOEofcZF%2Bns9A09PO6x%2B0OxiYD2hpoX9SrkAghnEAAaDDg5MTM3NzEzNDQwMCIMZmel5gOdx72MuskSKsECTeZ5%2BcyfkQg%2B%2B3A7JvIv%2BC1gROoz%2FDXmPWbU%2FSAZeVnNm52uZ%2BqIMs%2BwWYZetz3c6yCs4jAoaTtG5m%2BQUFHX0y8bA131w1uOZUPrG8vFPXNHWSgPIc2G%2BZoXdzeipp2WUaTIGlCwyWXDI0XfP9qVjd6Xq4HLnggPA4oSEu1YwgK%2B47jO0XM%2BucrzhxuqSmi6wVGtzHp93KmPFT6jVAyM%2Bl6kb3apdWTa8YHjAzVRSLF7Zz%2Fp%2BMqMHJu4rqCAxFjNHzYu6iNqfLa17QRksNm6ceMouz8Hmv3npsckPC47fZLRmUn1RHdT0lNBOq%2BqiQzrSDxhGIpVUsH9S8rVkSMsGKupUo8Hj18GsuAsTeqtIICu9QrV%2F0yEnkpMbv4YBkbIP06fCLDbvEOFYkR6E8%2BCNduIk2IsaFdCuA%2FrBojQ9DSdMLCbo7MGOrQCUO2zBp8Ayj4ia9p0LjRwbGHDNtKhAQzxdILs%2BTn%2BTREt231CGQ119MkAhv4MeK685Da%2F8VOpav58HESVRdNqcYh%2B3AYuXsCwnC2WHYIpsgz5VssWUvwH%2BvPMwkzzIgXcdwNVBNS4m67c5pcya%2BQIVR3ShsBOv4BiTESmnjwUlxORB%2ByYvdfTz5gkVx3IA97wri%2FEKTH5prAsLR80ue2ayQDYnciX8awXYavJ7ypQa4nXgiyzOoy8ZJ5eA5yDeGiZG9rGkopMkjLVgrZeDfK7LH87Vetx3Jcxrwwwh7NVIvXQ0rnf5nJEweuW7EcgRSEeyB11pMUsSZC3f4NCRFt%2B6FcwqpJsY%2FxJBLgtroXp3XBHcZlH4pmx6hcHqFRAYav6ZSUdjfavsbSA5gaarEscJfaQrdk%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240611T224039Z&X-Amz-SignedHeaders=host&X-Amz-Expires=43200&X-Amz-Credential=ASIA47CRXVNAOF2MQFR4%2F20240611%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=96c7384f7b881f1b201abc0689608231042ce46b076fdf75e2c3e009efc26cb7'

check_and_download_file(file_path, url)

pop = pd.read_csv("Population.csv")
cols = st.columns(2)
cols[0].metric(label="Felony Convicitons for the Population (2015-2023)", value=32979, delta='inc')
v = int(pop.loc[0, pop.columns.str.contains("Black")].values[0]) / int(pop.loc[0, pop.columns.str.contains("White")].values[0])
cols[1].metric(label="Black : White Population ratio", value=str(round(v*100, 2))+"/100", delta = "As per 2020")
style_metric_cards()

#------------------------------- Page 0 ------------------------------#
Page0 = st.container(border=True)
Page0 = stylable_container(key="Page0", css_styles=[""" {box-shadow: rgba(0, 0, 0, 0.24) 0px 3px 25px;}"""])#, """{background-color:white;opacity:0.8;}"""])#, """  {border: 2px solid rgba(49, 51, 63, 0.2); border-radius: 10px;}"""])

cols = Page0.columns([0.5,5.5,0.2,3.3,0.5])
cols[1].header("Most Common Charges Booked in the County", anchor='section-1', help="A Graph to understrand the most commnly charged crimes in the county by racial distribution. The graph gives a yearly estimates of the crimes. You can choose to see the data by Race/Race and see upto top 300.")

cols = Page0.columns([0.5,3, 3,3,0.5])
Race = cols[1].selectbox('Select Race', tuple(color.keys()), index=None)
Dec = cols[2].selectbox('Change Data', tuple(['Court Data', 'Curently Incarcerated']), index=0)

st.markdown("""
    <style>
    .stSlider [data-baseweb=slider]{
        width: 100%;
    }
    </style>
    """,unsafe_allow_html=True)
timeline = cols[3].slider('Select Timeline for Cases', 1990, 2022, (2015,2021))

cols = Page0.columns([6.5,3.5])
file_path = "Population.csv"
url = 'https://rja-sanbernardino.s3.us-east-1.amazonaws.com/dashboard/Population.csv?response-content-disposition=inline&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEM%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIFmSNoakzC4hQlNV2NcIpccGqt1lJiw7dumO58Kv5HHaAiBCHRkYbyL09%2BOEofcZF%2Bns9A09PO6x%2B0OxiYD2hpoX9SrkAghnEAAaDDg5MTM3NzEzNDQwMCIMZmel5gOdx72MuskSKsECTeZ5%2BcyfkQg%2B%2B3A7JvIv%2BC1gROoz%2FDXmPWbU%2FSAZeVnNm52uZ%2BqIMs%2BwWYZetz3c6yCs4jAoaTtG5m%2BQUFHX0y8bA131w1uOZUPrG8vFPXNHWSgPIc2G%2BZoXdzeipp2WUaTIGlCwyWXDI0XfP9qVjd6Xq4HLnggPA4oSEu1YwgK%2B47jO0XM%2BucrzhxuqSmi6wVGtzHp93KmPFT6jVAyM%2Bl6kb3apdWTa8YHjAzVRSLF7Zz%2Fp%2BMqMHJu4rqCAxFjNHzYu6iNqfLa17QRksNm6ceMouz8Hmv3npsckPC47fZLRmUn1RHdT0lNBOq%2BqiQzrSDxhGIpVUsH9S8rVkSMsGKupUo8Hj18GsuAsTeqtIICu9QrV%2F0yEnkpMbv4YBkbIP06fCLDbvEOFYkR6E8%2BCNduIk2IsaFdCuA%2FrBojQ9DSdMLCbo7MGOrQCUO2zBp8Ayj4ia9p0LjRwbGHDNtKhAQzxdILs%2BTn%2BTREt231CGQ119MkAhv4MeK685Da%2F8VOpav58HESVRdNqcYh%2B3AYuXsCwnC2WHYIpsgz5VssWUvwH%2BvPMwkzzIgXcdwNVBNS4m67c5pcya%2BQIVR3ShsBOv4BiTESmnjwUlxORB%2ByYvdfTz5gkVx3IA97wri%2FEKTH5prAsLR80ue2ayQDYnciX8awXYavJ7ypQa4nXgiyzOoy8ZJ5eA5yDeGiZG9rGkopMkjLVgrZeDfK7LH87Vetx3Jcxrwwwh7NVIvXQ0rnf5nJEweuW7EcgRSEeyB11pMUsSZC3f4NCRFt%2B6FcwqpJsY%2FxJBLgtroXp3XBHcZlH4pmx6hcHqFRAYav6ZSUdjfavsbSA5gaarEscJfaQrdk%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240611T224039Z&X-Amz-SignedHeaders=host&X-Amz-Expires=43200&X-Amz-Credential=ASIA47CRXVNAOF2MQFR4%2F20240611%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=96c7384f7b881f1b201abc0689608231042ce46b076fdf75e2c3e009efc26cb7'

check_and_download_file(file_path, url)

file_path = "Court_appA.csv"
url = 'https://rja-sanbernardino.s3.us-east-1.amazonaws.com/dashboard/Court_appA.csv?response-content-disposition=inline&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEM%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIFmSNoakzC4hQlNV2NcIpccGqt1lJiw7dumO58Kv5HHaAiBCHRkYbyL09%2BOEofcZF%2Bns9A09PO6x%2B0OxiYD2hpoX9SrkAghnEAAaDDg5MTM3NzEzNDQwMCIMZmel5gOdx72MuskSKsECTeZ5%2BcyfkQg%2B%2B3A7JvIv%2BC1gROoz%2FDXmPWbU%2FSAZeVnNm52uZ%2BqIMs%2BwWYZetz3c6yCs4jAoaTtG5m%2BQUFHX0y8bA131w1uOZUPrG8vFPXNHWSgPIc2G%2BZoXdzeipp2WUaTIGlCwyWXDI0XfP9qVjd6Xq4HLnggPA4oSEu1YwgK%2B47jO0XM%2BucrzhxuqSmi6wVGtzHp93KmPFT6jVAyM%2Bl6kb3apdWTa8YHjAzVRSLF7Zz%2Fp%2BMqMHJu4rqCAxFjNHzYu6iNqfLa17QRksNm6ceMouz8Hmv3npsckPC47fZLRmUn1RHdT0lNBOq%2BqiQzrSDxhGIpVUsH9S8rVkSMsGKupUo8Hj18GsuAsTeqtIICu9QrV%2F0yEnkpMbv4YBkbIP06fCLDbvEOFYkR6E8%2BCNduIk2IsaFdCuA%2FrBojQ9DSdMLCbo7MGOrQCUO2zBp8Ayj4ia9p0LjRwbGHDNtKhAQzxdILs%2BTn%2BTREt231CGQ119MkAhv4MeK685Da%2F8VOpav58HESVRdNqcYh%2B3AYuXsCwnC2WHYIpsgz5VssWUvwH%2BvPMwkzzIgXcdwNVBNS4m67c5pcya%2BQIVR3ShsBOv4BiTESmnjwUlxORB%2ByYvdfTz5gkVx3IA97wri%2FEKTH5prAsLR80ue2ayQDYnciX8awXYavJ7ypQa4nXgiyzOoy8ZJ5eA5yDeGiZG9rGkopMkjLVgrZeDfK7LH87Vetx3Jcxrwwwh7NVIvXQ0rnf5nJEweuW7EcgRSEeyB11pMUsSZC3f4NCRFt%2B6FcwqpJsY%2FxJBLgtroXp3XBHcZlH4pmx6hcHqFRAYav6ZSUdjfavsbSA5gaarEscJfaQrdk%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240611T225407Z&X-Amz-SignedHeaders=host&X-Amz-Expires=43200&X-Amz-Credential=ASIA47CRXVNAOF2MQFR4%2F20240611%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=5bd3a6b5fd9339bdd1828c445f171d57c1a5c29b6b8505f13386dcc6565013b5'

check_and_download_file(file_path, url)

file_path = "Incarceration_appA.csv"
url = 'https://rja-sanbernardino.s3.us-east-1.amazonaws.com/dashboard/Incarceration_appA.csv?response-content-disposition=inline&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEM%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIFmSNoakzC4hQlNV2NcIpccGqt1lJiw7dumO58Kv5HHaAiBCHRkYbyL09%2BOEofcZF%2Bns9A09PO6x%2B0OxiYD2hpoX9SrkAghnEAAaDDg5MTM3NzEzNDQwMCIMZmel5gOdx72MuskSKsECTeZ5%2BcyfkQg%2B%2B3A7JvIv%2BC1gROoz%2FDXmPWbU%2FSAZeVnNm52uZ%2BqIMs%2BwWYZetz3c6yCs4jAoaTtG5m%2BQUFHX0y8bA131w1uOZUPrG8vFPXNHWSgPIc2G%2BZoXdzeipp2WUaTIGlCwyWXDI0XfP9qVjd6Xq4HLnggPA4oSEu1YwgK%2B47jO0XM%2BucrzhxuqSmi6wVGtzHp93KmPFT6jVAyM%2Bl6kb3apdWTa8YHjAzVRSLF7Zz%2Fp%2BMqMHJu4rqCAxFjNHzYu6iNqfLa17QRksNm6ceMouz8Hmv3npsckPC47fZLRmUn1RHdT0lNBOq%2BqiQzrSDxhGIpVUsH9S8rVkSMsGKupUo8Hj18GsuAsTeqtIICu9QrV%2F0yEnkpMbv4YBkbIP06fCLDbvEOFYkR6E8%2BCNduIk2IsaFdCuA%2FrBojQ9DSdMLCbo7MGOrQCUO2zBp8Ayj4ia9p0LjRwbGHDNtKhAQzxdILs%2BTn%2BTREt231CGQ119MkAhv4MeK685Da%2F8VOpav58HESVRdNqcYh%2B3AYuXsCwnC2WHYIpsgz5VssWUvwH%2BvPMwkzzIgXcdwNVBNS4m67c5pcya%2BQIVR3ShsBOv4BiTESmnjwUlxORB%2ByYvdfTz5gkVx3IA97wri%2FEKTH5prAsLR80ue2ayQDYnciX8awXYavJ7ypQa4nXgiyzOoy8ZJ5eA5yDeGiZG9rGkopMkjLVgrZeDfK7LH87Vetx3Jcxrwwwh7NVIvXQ0rnf5nJEweuW7EcgRSEeyB11pMUsSZC3f4NCRFt%2B6FcwqpJsY%2FxJBLgtroXp3XBHcZlH4pmx6hcHqFRAYav6ZSUdjfavsbSA5gaarEscJfaQrdk%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240611T225455Z&X-Amz-SignedHeaders=host&X-Amz-Expires=43200&X-Amz-Credential=ASIA47CRXVNAOF2MQFR4%2F20240611%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=61363e9a187b82e2c6001d849bd9156bca839ba76ea4fdfecbff26c95190fa80'

check_and_download_file(file_path, url)

file_path = "Incarceration_appB.csv"
url = 'https://rja-sanbernardino.s3.us-east-1.amazonaws.com/dashboard/Incarceration_appB.csv?response-content-disposition=inline&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEM%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIFmSNoakzC4hQlNV2NcIpccGqt1lJiw7dumO58Kv5HHaAiBCHRkYbyL09%2BOEofcZF%2Bns9A09PO6x%2B0OxiYD2hpoX9SrkAghnEAAaDDg5MTM3NzEzNDQwMCIMZmel5gOdx72MuskSKsECTeZ5%2BcyfkQg%2B%2B3A7JvIv%2BC1gROoz%2FDXmPWbU%2FSAZeVnNm52uZ%2BqIMs%2BwWYZetz3c6yCs4jAoaTtG5m%2BQUFHX0y8bA131w1uOZUPrG8vFPXNHWSgPIc2G%2BZoXdzeipp2WUaTIGlCwyWXDI0XfP9qVjd6Xq4HLnggPA4oSEu1YwgK%2B47jO0XM%2BucrzhxuqSmi6wVGtzHp93KmPFT6jVAyM%2Bl6kb3apdWTa8YHjAzVRSLF7Zz%2Fp%2BMqMHJu4rqCAxFjNHzYu6iNqfLa17QRksNm6ceMouz8Hmv3npsckPC47fZLRmUn1RHdT0lNBOq%2BqiQzrSDxhGIpVUsH9S8rVkSMsGKupUo8Hj18GsuAsTeqtIICu9QrV%2F0yEnkpMbv4YBkbIP06fCLDbvEOFYkR6E8%2BCNduIk2IsaFdCuA%2FrBojQ9DSdMLCbo7MGOrQCUO2zBp8Ayj4ia9p0LjRwbGHDNtKhAQzxdILs%2BTn%2BTREt231CGQ119MkAhv4MeK685Da%2F8VOpav58HESVRdNqcYh%2B3AYuXsCwnC2WHYIpsgz5VssWUvwH%2BvPMwkzzIgXcdwNVBNS4m67c5pcya%2BQIVR3ShsBOv4BiTESmnjwUlxORB%2ByYvdfTz5gkVx3IA97wri%2FEKTH5prAsLR80ue2ayQDYnciX8awXYavJ7ypQa4nXgiyzOoy8ZJ5eA5yDeGiZG9rGkopMkjLVgrZeDfK7LH87Vetx3Jcxrwwwh7NVIvXQ0rnf5nJEweuW7EcgRSEeyB11pMUsSZC3f4NCRFt%2B6FcwqpJsY%2FxJBLgtroXp3XBHcZlH4pmx6hcHqFRAYav6ZSUdjfavsbSA5gaarEscJfaQrdk%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240611T225559Z&X-Amz-SignedHeaders=host&X-Amz-Expires=43200&X-Amz-Credential=ASIA47CRXVNAOF2MQFR4%2F20240611%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=90a515117cf5813700d9fd9129bde62adf37de225a6cf4769914b5b6d0ff0b14'

check_and_download_file(file_path, url)

if Race != None:
    df1 = pd.read_csv("Court_appA.csv") if Dec == 'Court Data' else pd.read_csv("Incarceration_appA.csv")
    df1 = df1[df1['Race'] == Race]
    df1 = df1[(df1['year'] >= timeline[0]) & (df1['year'] <= timeline[1])]
    df1 = df1[['Charges', 'Race', 'count']].groupby('Charges').agg({'count':'sum'}).reset_index()
    df1['count'] = (df1['count'] / (timeline[1] - timeline[0])) if timeline[1] != timeline[0] else df1['count']
    df1 = df1.sort_values('count')
    fig = px.bar(pd.DataFrame(df1[-40:]), y='Charges', x='count', orientation='h')
    fig.update_traces(marker_color=color[Race])
else:
    df1 = pd.read_csv("Court_appB.csv") if Dec == 'Court Data' else pd.read_csv("Incarceration_appB.csv")
    df1 = df1[(df1['year'] >= timeline[0]) & (df1['year'] <= timeline[1])]
    df1 = df1[['Charges', 'Race', 'count']].groupby(['Charges','Race']).agg({'count':'sum'}).reset_index()
    df1['count'] = (df1['count'] / (timeline[1] - timeline[0])) if timeline[1] != timeline[0] else df1['count']
    df1 = df1.sort_values(['Charges', 'count'])
    fig = px.bar(df1, y='Charges', x='count', orientation='h', color_discrete_map=color, color='Race')
    fig.update_layout(barmode='stack', yaxis={'categoryorder':'total ascending'})

if Dec == 'Court Data':
  fig.update_layout(width=900, height=900, xaxis = {'side':'top'},title_y=0.99, xaxis_title="Number of Cases Per Year", yaxis_title="Charges")
else:
   fig.update_layout(width=900, height=900, xaxis = {'side':'top'},title_y=0.99, xaxis_title="Total Cases", yaxis_title="Charges")

fig.update_layout(legend=dict(yanchor="top", y=0.7, xanchor="left", x=0.6)) 

cols[0].plotly_chart(fig, theme=None)

# df = pd.read_excel("California Penal Code .xlsx")
# # dfx = pd.read_csv("Court_appB.csv") 
# # df1 = df1[['Charges', 'count']].groupby(['Charges']).agg({'count':'sum'}).reset_index()
# # df1 = df1.sort_values(['Charges', 'count'])

# cols[1].markdown('######')
# cols[1].markdown('####')
# cols[1].dataframe(df, height=760)

# if st.session_state["authentication_status"]:
#   st.session_state.auth.logout()
# else:
#    switch_page('app')