Update app.py

app.py

@@ -17,39 +17,20 @@ import streamlit as st
 # IOT
 """
 
+merge = st.checkbox("Merge US country with State ?")
 
-max_depth_input = st.slider("Max depth", 1, 100, 5)
-colsample_bytree_input = st.slider("Colsample bytree", 0.0, 1.0, 0.5)
-learning_rate_input = st.slider("Learning rate", 0.0, 1.0, 0.2)
-alpha_input = st.slider("Alpha", 1, 100, 10)
-n_estimators_input = st.slider("n estimators", 1, 100, 20)
-
-
+all_region = st.checkbox("Take all Region ?", value=True)
+all_country = st.checkbox("Take all Country ?", value=True)
+all_state = st.checkbox("Take all State ?", value=True)
+all_city = st.checkbox("Take all City ?", value=True)
 
 df = pd.read_csv("city_temperature.csv")
 
-city_input = st.selectbox(
-     'Which region do you want to predict temparature ?',
-     ("all",
-     df["Region"].unique()), index=0)
-
-city_input = st.selectbox(
-     'Which region do you want to predict temparature ?',
-     ("all",
-     df["Region"].drop_duplicates()), index=0)
-
-test = df["Region"].unique()
-test2 = df["Region"].drop_duplicates()
-
-city_input = st.selectbox(
-     'Which region do you want to predict temparature ?',
-     ("all",
-     test), index=0)
-
-city_input = st.selectbox(
-     'Which region do you want to predict temparature ?',
-     ("all",
-     test2), index=0)
+if all_region == False:
+    region = st.selectbox(
+         'Which region do you want to predict temparature ?',
+         (df["Region"].unique()), index=0)
+    df.drop(df.loc[df['Location'] != region].index, inplace=True)
 
 def mergeStateToCountry():
     df.loc[df['State'].notna(), 'Country'] = df['State']