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  1. DeveloperSalary_Pred_Rgs.joblib +3 -0
  2. app.py +34 -0
DeveloperSalary_Pred_Rgs.joblib ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:ea120deb3d074caa8d3914d2fca0b0a5fd84e5af40c804acdb0897d327939b4e
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+ size 4439
app.py ADDED
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+ import pandas as pd
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+ import numpy as np
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+ import streamlit as st
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+ import joblib
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+ from sklearn.linear_model import LinearRegression
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+
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+ model = joblib.load('DeveloperSalary/DeveloperSalary_Pred_Rgs.joblib')
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+ st.title('Salary prediction in 2022')
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+ st.write("""### fill the form for prediction""")
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+
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+ columns = ['Country', 'EdLevel', 'YearsCode']
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+
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+
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+ Country = st.selectbox('Chose your country', ['United States of America', 'Australia', 'Russian Federation',
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+ 'France', 'South Africa', 'Greece', 'Poland', 'Germany', 'Denmark',
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+ 'India', 'United Kingdom of Great Britain and Northern Ireland',
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+ 'Argentina', 'Hungary', 'Switzerland', 'Brazil', 'Italy', 'Spain',
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+ 'Iran, Islamic Republic of...', 'Bangladesh', 'Israel', 'Sweden',
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+ 'Portugal', 'Netherlands', 'Canada', 'Mexico', 'Austria', 'Norway',
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+ 'Finland', 'Czech Republic', 'Belgium', 'Turkey', 'Romania',
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+ 'Ukraine', 'Colombia', 'New Zealand', 'Ireland', 'Pakistan',
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+ 'Japan'])
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+ EdLevel = st.selectbox('What is your educational level ?', ['Master’s degree', 'Bachelor’s degree', 'Less than a Bachelors',
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+ 'Post grad'])
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+ YearsOfCode = st.slider('How many years have you been coding ?', 0, 100)
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+
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+
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+ ok = st.button('Pred Salary')
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+ if ok:
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+ rows = np.array([Country, EdLevel, YearsOfCode])
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+ X_new = pd.DataFrame([rows], columns=columns)
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+ Salary = model.predict(X_new)
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+
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+ st.subheader(f'The estimate salary is ${Salary[0]:.2f}')