Update app.py

app.py

@@ -2,67 +2,84 @@ import joblib
 import pandas as pd
 import streamlit as st
 
-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"]
+unique_country =  unique_values["country"]
+unique_returning =  unique_values["returning"]
+unique_GImg1 =  unique_values["GImg1"]
+unique_GImg2 =  unique_values["GImg2"]
+unique_GImg3 =  unique_values["GImg3"]
+unique_PImg1 =  unique_values["PImg1"]
+unique_PImg2 =  unique_values["PImg2"]
+unique_PImg3 =  unique_values["PImg3"]
+unique_PImg4=  unique_values["PImg4"]
+unique_PImg5 =  unique_values["PImg5"]
+unique_TAudio1  =  unique_values["TAudio1"]
+unique_TAudio2  =  unique_values["TAudio2"]
+unique_TAudio3  =  unique_values["TAudio3"]
+unique_QAudio1  =  unique_values["QAudio1"]
+unique_QAudio2  =  unique_values["QAudio2"]
+unique_QAudio3  =  unique_values["QAudio3"]
+unique_Proxemics  =  unique_values["Proxemics"]
+unique_Authoritative  =  unique_values["Authoritative .anarchic"]
 
 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("Education", 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)
+        sex = st.selectbox("Sex",options = unique_sex)
+        age = st.slider("Age",min_value=10,max_values=100)
+        country = st.selectbox("Country of the client United Nations admitted countries",options = unique_country)
+        GImg1 = st.selectbox("Handshake Indifferent",options = unique_GImg1)
+        GImg2 = st.selectbox("Hug Indifferent",options = unique_GImg2)
+        GImg3 = st.selectbox("Kiss Indifferent",options = unique_GImg3)
+        PImg1 = st.selectbox("Consent posture Indifferent",options = unique_PImg1)
+        PImg2 = st.selectbox("Interest posture Indifferent",options = unique_PImg2)
+        PImg3 = st.selectbox("Neutral posture Indifferent",options = unique_PImg3)
+        PImg4 = st.selectbox("Reflexive posture Indifferent",options = unique_PImg4)
+        PImg5 = st.selectbox("Negative posture Indifferent",options = unique_PImg5)
+        Tense= st.slider("Observed emotional clime",min_value=1,max_values=10)
+        Authoritativean = st.selectbox("anarchic Observed emotional clime",options = unique_Authoritativean)
+        Hostile = st.slider("friendly Observed emotional clime",min_value=1,max_values=10)
+        TAudio1 = st.selectbox("Authoritative Indifferent",options = unique_TAudio1)
+        TAudio2 = st.selectbox("Sarcastic Indifferent",options = unique_TAudio2)   
+        TAudio3 = st.selectbox("Friendly Indifferent",options = unique_TAudio3)   
+        QAudio1 = st.selectbox("Spitting Indifferent",options = unique_QAudio1)   
+        QAudio2 = st.selectbox("Hum Indifferent",options = unique_QAudio1)   
+        QAudio3 = st.selectbox("Sigh Indifferent",options = unique_QAudio1)   
+        Proxemics = st.selectbox("Physical distance preferred for the client : A. intimate: 15cm-45cm; B. per-sonal: 46cm-122cm; C. social:123cm-360cm; D. public: > 360cm",options = unique_Proxemics)
+        
+
 
         # clicked==True only when the button is clicked
-        clicked = st.form_submit_button("Predict income")
+        clicked = st.form_submit_button("Predict Type of Client")
         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=model.predict(pd.DataFrame({"sex":[sex],
+                                               "age": [age],
+                                               "country": [country],
+                                               "GImg1" : [GImg1],
+                                               "GImg2" : [GImg2],
+                                               "GImg3" : [GImg3],
+                                               "PImg1" : [PImg1],
+                                               "PImg2" : [PImg2],
+                                               "PImg3" : [PImg3],
+                                               "PImg4" : [PImg4],
+                                               "PImg5" : [PImg5],
+                                               "Tense-relaxed" :[Tense],
+                                               "Authoritative-anarchic" : [Authoritative],
+                                               "Hostile-friendly" : [Hostile],
+                                               "TAudio1" : [TAudio1],
+                                               "TAudio2" : [TAudio2],
+                                               "TAudio3" : [TAudio3],
+                                               "QAudio1" : [QAudio1],  
+                                               "QAudio2" : [QAudio1],  
+                                               "QAudio3" : [QAudio1],
+                                               "Proxemics" : [Proxemics]}))
             # Show prediction
-            result = '>50K' if result[0] == 1 else '<=50K'
-            st.success("Your predicted income is "+result) #แสดงผล
+            result = 'low' if result[0] == 1 else 'high'
+            st.success("Predict Type of Client is "+result) #แสดงผล
             
 # Run main()
 if __name__ == "__main__":