Add a university demographics page

app.py

@@ -1,6 +1,7 @@
 import streamlit as st
 import page_home
 import page_likert
+import page_demographics
 from urllib.parse import quote, unquote
 
 # Default to wide mode
@@ -15,9 +16,11 @@ if 'page' not in st.session_state:
 
 # Sidebar navigation using buttons
 st.sidebar.title("Navigation")
-if st.sidebar.button("Home"):
+if st.sidebar.button("Introduction"):
     st.session_state['page'] = 'Home'
-if st.sidebar.button("Likert"):
+if st.sidebar.button("Demographics"):
+    st.session_state['page'] = 'Demographics'
+if st.sidebar.button("Student Attitudes"):
     st.session_state['page'] = 'Likert'
 
 # Update the query parameters based on the session state
@@ -28,6 +31,8 @@ if st.session_state['page'] == 'Home':
     page_home.show()
 elif st.session_state['page'] == 'Likert':
     page_likert.show()
+elif st.session_state['page'] == 'Demographics':
+    page_demographics.show()
 
 # Rerun Calculations
 if st.sidebar.button("Rerun Calculations"):

page_demographics.py

@@ -0,0 +1,26 @@
+import streamlit as st
+import pandas as pd
+from datasets import load_dataset
+
+@st.cache_data
+def show():
+    # Load data from Huggingface
+    dataset = load_dataset(
+        "krishaamer/taiwanese-college-students", data_files={'train': 'clean.csv'})
+
+    # Convert the loaded dataset to a pandas DataFrame
+    df = dataset['train'].to_pandas()
+
+    # Generate and display the university ranking table
+    generate_university_ranking_table(df)
+
+
+@st.cache_data
+def generate_university_ranking_table(df):
+    # Count the number of respondents for each university and sort them
+    university_counts = df["你/妳在哪所大學念書？"].value_counts(
+    ).sort_values(ascending=False).reset_index()
+    university_counts.columns = ['University', 'Number of Respondents']
+
+    # Display the table in Streamlit
+    st.table(university_counts)