Update app.py

app.py

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