MobilePrice / app.py
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import joblib
import pandas as pd
EDU_DICT = {'Preschool': 1,
'1st-4th': 2,
'5th-6th': 3,
'7th-8th': 4,
'9th': 5,
'10th': 6,
'11th': 7,
'12th': 8,
'HS-grad': 9,
'Some-college': 10,
'Assoc-voc': 11,
'Assoc-acdm': 12,
'Bachelors': 13,
'Masters': 14,
'Prof-school': 15,
'Doctorate': 16
}
model = joblib.load('model.joblib')
unique_values = joblib.load('unique_values.joblib')
unique_class = unique_values["workclass"]
unique_education = unique_values["education"]
unique_marital_status = unique_values["marital.status"]
unique_relationship = unique_values["relationship"]
unique_occupation = unique_values["occupation"]
unique_sex = unique_values["sex"]
unique_race = unique_values["race"]
unique_country = unique_values["native.country"]
def main():
st.title("Adult Income")
with st.form("questionaire"):
age = st.slider("AGE",min_value=10,max_value=100)
workclass = st.selectbox("WorkClass",options=unique_class)
education = st.selectbox("Eduation",options=unique_education)
Marital_Status = st.selectbox("Marital status",options=unique_marital_status)
occupation = st.selectbox("occupation",options=unique_occupation)
relationship = st.selectbox("relationship",options=unique_relationship)
race = st.selectbox("Race",options=unique_race)
sex = st.selectbox("Sex",options=unique_sex)
hours_per_week = st.slider("Hours per week",min_value=1,max_value=100)
native_country = st.selectbox("Native Country",options=unique_country)
# clicked==True only when the button is clicked
clicked = st.form_submit_button("Predict income")
if clicked:
result=model.predict(pd.DataFrame({"age": [age],
"workclass": [workclass],
"education": [EDU_DICT[education]],
"marital.status": [Marital_Status],
"occupation": [occupation],
"relationship": [relationship],
"race": [race],
"sex": [sex],
"hours.per.week": [hours_per_week],
"native.country": [native_country]}))
result = '>50k' if result[0] == 1 else '<50k'
st.success("Your predicted income is " +result)
if __name__ == "__main__":
main()
# Show prediction
# Run main()