mkhorasani

def write_state(column,value,engine,session_id):
    engine.execute("UPDATE %s SET %s='%s'" % (session_id,column,value))

def write_state_df(df,engine,session_id):
    df.to_sql('%s' % (session_id),engine,index=False,if_exists='replace',chunksize=1000)

def read_state(column,engine,session_id):
    state_var = engine.execute("SELECT %s FROM %s" % (column,session_id))
    state_var = state_var.first()[0]
    return state_var

mkhorasani

import streamlit as st
import time
import random
import plotly.express as px
import pandas as pd

mkhorasani

placeholder = st.empty()
start_button = st.empty()

mkhorasani

def radar_chart():  
    df = pd.DataFrame(dict(
    r=[random.randint(0,22),
       random.randint(0,22),
       random.randint(0,22),
       random.randint(0,22),
       random.randint(0,22)],
    theta=['processing cost','mechanical properties','chemical stability',
           'thermal stability', 'device integration']))
    fig = px.line_polar(df, r='r', theta='theta', line_close=True)

mkhorasani

if start_button.button('Start',key='start'):
    start_button.empty()
    if st.button('Stop',key='stop'):
        pass
    while True:
        radar_chart()
        time.sleep(0.5)

mkhorasani

import pandas as pd
import streamlit as st
import datetime
import re
import base64

mkhorasani

def df_filter(message,df):

        slider_1, slider_2 = st.slider('%s' % (message),0,len(df)-1,[0,len(df)-1],1)

        while len(str(df.iloc[slider_1][1]).replace('.0','')) < 4:
            df.iloc[slider_1,1] = '0' + str(df.iloc[slider_1][1]).replace('.0','')
            
        while len(str(df.iloc[slider_2][1]).replace('.0','')) < 4:
            df.iloc[slider_2,1] = '0' + str(df.iloc[slider_1][1]).replace('.0','')

mkhorasani

def download_csv(name,df):
    
    csv = df.to_csv(index=False)
    base = base64.b64encode(csv.encode()).decode()
    file = (f'<a href="data:file/csv;base64,{base}" download="%s.csv">Download file</a>' % (name))
    
    return file

mkhorasani

if __name__ == '__main__':

    df = pd.read_csv('file_path')

    st.title('Datetime Filter')
    filtered_df = df_filter('Move sliders to filter dataframe',df)

    column_1, column_2 = st.beta_columns(2)

    with column_1:

mkhorasani

import streamlit as st
import pandas as pd
import plotly.express as px
import datetime
import base64