Update app.py

app.py

@@ -2,26 +2,28 @@ import pandas as pd
 import streamlit as st
 
 # Read the CSV file into a Pandas DataFrame
-df = pd.read_csv('cph_airbnb_listings.csv')
-
-# Sort the DataFrame by 'neighbourhood' and then by 'price'
-sorted_df = df.sort_values(by=['neighbourhood', 'price'])
+df = pd.read_csv('your_file.csv')
 
 # Create a Streamlit app
-st.title('my_first_app')
+st.title('Sorted and Filtered Data by Neighbourhood and Price')
 
-# Allow user to select a specific neighbourhood
-selected_neighbourhood = st.selectbox('Select Neighbourhood', sorted_df['neighbourhood'].unique())
+# Allow user to add filters for neighbourhoods
+selected_neighbourhoods = st.sidebar.multiselect('Select Neighbourhood(s)', df['neighbourhood'].unique())
 
-# Filter the DataFrame based on selected neighbourhood
-filtered_df = sorted_df[sorted_df['neighbourhood'] == selected_neighbourhood]
+# Allow user to add filter for room type
+selected_room_type = st.sidebar.selectbox('Select Room Type', ['Private room', 'Entire home/apt'])
 
 # Allow user to set a price range filter
-price_range = st.slider('Select Price Range', min_value=0, max_value=10000, step=10, value=(0, 1000))
-
-# Filter the DataFrame based on selected price range
+price_range = st.sidebar.slider('Select Price Range', min_value=0, max_value=1000, step=10, value=(0, 1000))
+
+# Filter the DataFrame based on selected filters
+filtered_df = df.copy()
+if selected_neighbourhoods:
+    filtered_df = filtered_df[filtered_df['neighbourhood'].isin(selected_neighbourhoods)]
+if selected_room_type:
+    filtered_df = filtered_df[filtered_df['room_type'] == selected_room_type]
 filtered_df = filtered_df[(filtered_df['price'] >= price_range[0]) & (filtered_df['price'] <= price_range[1])]
 
 # Display the filtered DataFrame
 st.write('Below is the sorted and filtered data:')
-st.write(filtered_df)
+st.write(filtered_df)