import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn import linear_model


Stock_Market = {'Year': [2022,2022,2022,2022,2022,2022,2022,2022,2022,2022,2022,2022,2021,2021,2021,2021,2021,2021,2021,2021,2021,2021,2021,2021],
                'Month': [12, 11,10,9,8,7,6,5,4,3,2,1,12,11,10,9,8,7,6,5,4,3,2,1],
                'EconomicGrowth_Rate': [2.75,2.5,2.5,2.5,2.5,2.5,2.5,2.25,2.25,2.25,2,2,2,1.75,1.75,1.75,1.75,1.75,1.75,1.75,1.75,1.75,1.75,1.75],
                'Unemployment_Rate': [5.3,5.3,5.3,5.3,5.4,5.6,5.5,5.5,5.5,5.6,5.7,5.9,6,5.9,5.8,6.1,6.2,6.1,6.1,6.1,5.9,6.2,6.2,6.1],
                'Stock_Index_Price': [1464,1394,1357,1293,1256,1254,1234,1195,1159,1167,1130,1075,1047,965,943,958,971,949,884,866,876,822,704,719]        
                }

df = pd.DataFrame(Stock_Market,columns = ['Year','Month','EconomicGrowth_Rate','Unemployment_Rate','Stock_Index_Price'])

x = df[['EconomicGrowth_Rate','Unemployment_Rate']]
y = df['Stock_Index_Price']

lr = linear_model.LinearRegression()
lr.fit(x,y)


st.title("Stock Index Prediction using Linear Regression")

st.text(" ")
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st.image('stockindex.jpeg',width=700)

st.text(" ")
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st.text(" ")
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st.subheader("Relationship between Stock Index Price and Economic Growth Rate")

st.text(" ")
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plt.figure(figsize=(9,6))
plt.xlabel("Economic Growth Rate")
plt.ylabel("Stock Index Price")
plt.scatter(df['EconomicGrowth_Rate'],df['Stock_Index_Price'],color='g')
plt.tight_layout()
st.set_option('deprecation.showPyplotGlobalUse',False)
st.pyplot()


st.text(" ")
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st.subheader("Relationship between Stock Index Price and unemployment Rate")

st.text(" ")
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plt.figure(figsize=(9,6))
plt.xlabel("Unemployment Rate")
plt.ylabel("Stock Index Price")
plt.scatter(df['Unemployment_Rate'],df['Stock_Index_Price'],color='g')
plt.tight_layout()
st.set_option('deprecation.showPyplotGlobalUse',False)
st.pyplot()

st.text(" ")
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i = st.number_input("Enter Economic Growth Rate")
st.text(" ")
st.text(" ")
u = st.number_input("Enter Unemployment Rate")
st.text(" ")
st.text(" ")

if st.button("Predict"):
    st.subheader("Predicted Value of Stock Index")
    st.text(lr.predict([[i,u]]))