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import streamlit as st
import pandas as pd
import datetime
import numpy as np
import datetime
import all_model
def show_information():
# Show Information about the selected Stock
st.header('🤫Did you know💡')
st.caption("Analyzing data from 2015 to 2021")
st.text("1) There is a 60% chance of gap up opening in any random trade in Reliance 😮 ")
st.text("2) 1% of the gap up is more than Rs:15.00 i.e more quantity == more profit😇")
st.text("3) Median, Q3 or 75th percentile have increased from 2015(1.8) to 2021(11.55)💰")
def select_date():
# Select the date for Prediction
selected_date = st.date_input(
"Which date you want to check",
datetime.date(2022, 3, 6))
st.write('Your selected date is:', selected_date)
return selected_date
# @st.cache
# def prepare_data_for_selected_date():
# df = pd.read_csv("dataset/reliance_30min.csv")
# df = helper.format_date(df)
# df = helper.replace_vol(df)
# df = helper.feature_main(df)
# df.to_csv('dataset/processed_reliance30m.csv')
# return df
@st.cache
def freature_data(date):
# st.dataframe(df.loc[str(date)])
df = pd.read_csv("processed_reliance30m.csv",parse_dates=['Datetime']).set_index('Datetime')
df = df.loc[str(date)]
df = df.drop(columns=['date'],axis=1)
return df
def show_prediction_result(prepared_data):
model = all_model.load_model()
result = all_model.prediction(model,prepared_data)
return result
def main():
st.title('PROFIT IN THE MORNING!')
option = st.selectbox(
'Which stock would you like to analyze?',
('None','Reliance', 'Airtel', 'State Bank Of India'))
st.write('You selected:', option)
if option=="Reliance":
data_link = ("C:/Users/Rajdeep Borgohain.000/Desktop/reliance_30min.csv")
dateSelect = False
# About Reliance Stock
show_information()
selected_date = select_date()
# prepared_data = prepare_data_for_selected_date()
prepared_data = freature_data(selected_date)
score = show_prediction_result(prepared_data)
st.write(score)
selected_date+=datetime.timedelta(days=1)
if score == 'nan':
text = f'No data avaliable for the selected date {selected_date}'
st.warning(text)
elif score >= 0.5:
score = np.round(score,4)*100
text = f'The chances of Gap up on: {selected_date} is {score}%'
st.success(text)
elif score < 0.5:
text = f'The chances of Gap up on: {selected_date} is {score}'
st.error(text)
else:
st.text('Data Not Avaliable!')
if __name__ == "__main__":
main() |