mkhorasani

df = pd.read_csv('C:/Users/..../data.csv')
    
for i in range(0,len(df)):
    while len(str(df.iloc[i][1]).replace('.0','')) < 4:
        df.iloc[i,1] = '0' + str(df.iloc[i][1]).replace('.0','')

    temp = datetime.datetime.strptime(str(df.iloc[i][0]).replace('.0','') + str(df.iloc[i][1]).replace('.0',''),'%Y%m%d%H%M')
    df.iloc[i,0] = temp.strftime('%B')
    df.iloc[i,1] = temp.strftime('%I%p')

mkhorasani

df = df.groupby(['Month','Hour'],sort=False,as_index=False).mean().round(1)

mkhorasani

month_hours = {'January': {'12AM': None, '01AM': None, '02AM': None, '03AM': None, '04AM': None, '05AM': None,
        '06AM': None, '07AM': None, '08AM': None, '09AM': None, '10AM': None, '11AM': None,
        '12PM': None, '01PM': None, '02PM': None, '03PM': None, '04PM': None, '05PM': None,
        '06PM': None, '07PM': None, '08PM': None, '09PM': None, '10PM': None, '11PM': None},
        
....
                
'December': {'12AM': None, '01AM': None, '02AM': None, '03AM': None, '04AM': None, '05AM': None,
        '06AM': None, '07AM': None, '08AM': None, '09AM': None, '10AM': None, '11AM': None,
        '12PM': None, '01PM': None, '02PM': None, '03PM': None, '04PM': None, '05PM': None,

mkhorasani

for i in range(len(df)):
    month_hours[df.iloc[i][0]][df.iloc[i][1]] = df.loc[i]['Value']
        
data_rows = list(month_hours.values())
data = []

for i in range(0,len(data_rows)):
    data.append(list(data_rows[i].values()))

mkhorasani

fig = px.imshow(data,
                labels=dict(x="Hour", y="Month", color="Value"),
                x=['12AM','01AM','02AM','03AM','04AM','05AM',
                '06AM','07AM','08AM','09AM','10AM','11AM',
                '12PM','01PM','02PM','03PM','04PM','05PM',
                '06PM','07PM','08PM','09PM','10PM','11PM'],
                y=['January','February','March','April','May','June',
                    'July','August','September','October','November','December']
                )
                            

mkhorasani

st.title('Month vs. Hour Heatmap')
st.title('Dataframe')
st.dataframe(df)
st.markdown(download_csv('Heatmap Dataframe',pd.DataFrame(df)),unsafe_allow_html=True)

mkhorasani

def download_csv(name,df):
    
    csv = df.to_csv()
    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

from sqlalchemy import create_engine
import psycopg2
import pandas as pd
import streamlit as st

mkhorasani

engine = create_engine("postgresql://<username>:<password>@localhost:5432/records_db")
engine_dataset = create_engine("postgresql://<username>:<password>@localhost:5432/datasets_db")
engine.execute("CREATE TABLE IF NOT EXISTS records (name text PRIMARY KEY, details text[])")

mkhorasani

def write_record(name,details,engine):
    engine.execute("INSERT INTO records (name,details) VALUES ('%s','%s')" % (name,details))

def read_record(field,name,engine):
    result = engine.execute("SELECT %s FROM records WHERE name = '%s'" % (field,name))
    return result.first()[0]
    
def update_record(field,name,new_value,engine):
    engine.execute("UPDATE records SET %s = '%s' WHERE name = '%s'" % (field,new_value,name))