Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+
+# Function to load data and replace missing values
+@st.cache
+def load_data():
+    # Load your data here, assuming 'recent_grads' is your DataFrame
+    # Replace 'your_data.csv' with your actual data file
+    recent_grads = pd.read_csv('your_data.csv')
+
+    # List of columns needing correction
+    columns_to_correct = ['column1', 'column2', 'column3']  # Replace these with your columns
+
+    # Replace 'UN' with NaN in specified columns
+    for column in columns_to_correct:
+        recent_grads.loc[recent_grads[column] == 'UN', column] = np.nan
+
+    return recent_grads
+
+def main():
+    st.title('Data Handling with Streamlit')
+
+    # Load data
+    data = load_data()
+
+    # Show the loaded data in Streamlit
+    st.write("Original Data:")
+    st.write(data)
+
+if __name__ == "__main__":
+    main()