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import streamlit as st
import pickle
import sklearn
import pandas as pd
import numpy as np
from PIL import Image
model = pickle.load(open('model.sav', 'rb'))
st.title('Player Salary Prediction')
st.sidebar.header('Player Data')
#image = Image.open('bb.jpg')
#st.image(image, '')
# FUNCTION
def user_report():
rating = st.sidebar.slider('Rating', 50,100, 1 )
jersey = st.sidebar.slider('Jersey', 0,100, 1 )
team = st.sidebar.slider('Team', 0,30, 1 )
position = st.sidebar.slider('Position', 0,10, 1 )
country = st.sidebar.slider('Country', 0,3, 1 )
draft_year = st.sidebar.slider('Draft Year', 2000,2020, 2000)
draft_round = st.sidebar.slider('Draft Round', 1,10, 1)
draft_peak = st.sidebar.slider('Draft Peak', 1,30, 1)
user_report_data = {
'rating':rating,
'jersey':jersey,
'team':team,
'position':position,
'country':country,
'draft_year':draft_year,
'draft_round':draft_round,
'draft_peak':draft_peak
}
report_data = pd.DataFrame(user_report_data, index=[0])
return report_data
user_data = user_report()
st.header('Player Data')
st.write(user_data)
salary = model.predict(user_data)
st.subheader('Player Salary')
st.subheader('$'+str(np.round(salary[0], 2)))
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