Tapanat commited on
Commit
f6588aa
1 Parent(s): 4c8c9a8

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +12 -51
app.py CHANGED
@@ -2,65 +2,26 @@ import joblib
2
  import pandas as pd
3
  import streamlit as st
4
 
5
- EDU_DICT = {'Preschool': 1,
6
- '1st-4th': 2,
7
- '5th-6th': 3,
8
- '7th-8th': 4,
9
- '9th': 5,
10
- '10th': 6,
11
- '11th': 7,
12
- '12th': 8,
13
- 'HS-grad': 9,
14
- 'Some-college': 10,
15
- 'Assoc-voc': 11,
16
- 'Assoc-acdm': 12,
17
- 'Bachelors': 13,
18
- 'Masters': 14,
19
- 'Prof-school': 15,
20
- 'Doctorate': 16
21
- }
22
-
23
  model = joblib.load('model.joblib')
24
  unique_values = joblib.load('unique_values.joblib')
25
 
26
- unique_class = unique_values["workclass"]
27
- unique_education = unique_values["education"]
28
- unique_marital_status = unique_values["marital.status"]
29
- unique_relationship = unique_values["relationship"]
30
- unique_occupation = unique_values["occupation"]
31
- unique_sex = unique_values["sex"]
32
- unique_race = unique_values["race"]
33
- unique_country = unique_values["native.country"]
34
 
35
  def main():
36
- st.title("Adult Income Analysis")
37
 
38
  with st.form("questionaire"):
39
- age = st.slider("Age", min_value=10, max_value=100)
40
- workclass = st.selectbox("Workclass", unique_class)
41
- education = st.selectbox("Education", unique_education)
42
- Marital_Status = st.selectbox("Marital Status", unique_marital_status)
43
- occupation = st.selectbox("Occupation", unique_occupation)
44
- relationship = st.selectbox("Relationship", unique_relationship)
45
- race = st.selectbox("Race", unique_race)
46
- sex = st.selectbox("Sex", unique_sex)
47
- hours_per_week = st.slider("Hours per week", min_value=1, max_value=100)
48
- native_country = st.selectbox("Country", unique_country)
49
-
50
- clicked = st.form_submit_button("Predict income")
51
  if clicked:
52
- result=model.predict(pd.DataFrame({"age": [age],
53
- "workclass": [workclass],
54
- "education": [EDU_DICT[education]],
55
- "marital.status": [Marital_Status],
56
- "occupation": [occupation],
57
- "relationship": [relationship],
58
- "race": [race],
59
- "sex": [sex],
60
- "hours.per.week": [hours_per_week],
61
- "native.country": [native_country]}))
62
- result = '>50K' if result[0] == 1 else '<=50K'
63
- st.success('The predicted income is {}'.format(result))
64
 
65
  if __name__=='__main__':
66
  main()
 
2
  import pandas as pd
3
  import streamlit as st
4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5
  model = joblib.load('model.joblib')
6
  unique_values = joblib.load('unique_values.joblib')
7
 
8
+ unique_color = unique_values["color"]
 
 
 
 
 
 
 
9
 
10
  def main():
11
+ st.title("Colors Prediction")
12
 
13
  with st.form("questionaire"):
14
+ color = st.selectbox("Color", unique_color)
15
+
16
+ clicked = st.form_submit_button("Predict Color")
 
 
 
 
 
 
 
 
 
17
  if clicked:
18
+ result=model.predict(pd.DataFrame({"room": [room],
19
+ "partitions": [partition],
20
+ "Rows": [row],
21
+ "Columns": [Columns],
22
+ "Color": [Color]}))
23
+ result = 'Red' if result[0] == 1 else 'Blue'
24
+ st.success('The predicted color is {}'.format(result))
 
 
 
 
 
25
 
26
  if __name__=='__main__':
27
  main()