Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,81 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+import pandas as pd
+import re
+import io
+
+st.set_page_config(page_title="Excel to Cleaned CSV", layout="centered")
+
+st.title("📊 Clean Admission Excel Data")
+st.write("Upload the Excel file and download the cleaned CSV file.")
+
+uploaded_file = st.file_uploader("Upload your Excel file", type=["xlsx"])
+
+if uploaded_file is not None:
+    try:
+        # Read and clean data
+        df_raw = pd.read_excel(uploaded_file, skiprows=4)
+
+        df_raw.columns = [
+            'S.No', 'District', 'Institution Name',
+            'V Minorities Sanctioned', 'V Minorities Admitted',
+            'V NonMinorities Sanctioned', 'V NonMinorities Admitted',
+            'Course',
+            'Inter Minorities Sanctioned', 'Inter Minorities Admitted',
+            'Inter NonMinorities Sanctioned', 'Inter NonMinorities Admitted'
+        ]
+
+        # Remove last row
+        df_raw = df_raw.iloc[:-1]
+
+        # Clean Institution Name
+        df_raw['Institution Name'] = df_raw['Institution Name'].astype(str).apply(
+            lambda x: re.sub(r'\([^)]*\)', '', x).replace('Boys', 'B').replace('Girls', 'G').strip()
+        )
+
+        # Convert numeric cols
+        numeric_cols = [
+            'V Minorities Sanctioned', 'V Minorities Admitted',
+            'V NonMinorities Sanctioned', 'V NonMinorities Admitted',
+            'Inter Minorities Sanctioned', 'Inter Minorities Admitted',
+            'Inter NonMinorities Sanctioned', 'Inter NonMinorities Admitted'
+        ]
+        for col in numeric_cols:
+            df_raw[col] = pd.to_numeric(df_raw[col], errors='coerce').fillna(0).astype(int)
+
+        # Process Class V
+        df_v = df_raw[['S.No', 'District', 'Institution Name',
+                       'V Minorities Sanctioned', 'V Minorities Admitted',
+                       'V NonMinorities Sanctioned', 'V NonMinorities Admitted']].copy()
+        df_v['Class'] = 'V'
+        df_v['Sanctioned'] = df_v['V Minorities Sanctioned'] + df_v['V NonMinorities Sanctioned']
+        df_v['Admitted'] = df_v['V Minorities Admitted'] + df_v['V NonMinorities Admitted']
+
+        # Process Inter
+        df_inter = df_raw[['S.No', 'District', 'Institution Name',
+                           'Inter Minorities Sanctioned', 'Inter Minorities Admitted',
+                           'Inter NonMinorities Sanctioned', 'Inter NonMinorities Admitted']].copy()
+        df_inter['Class'] = 'Inter 1st Year'
+        df_inter['Sanctioned'] = df_inter['Inter Minorities Sanctioned'] + df_inter['Inter NonMinorities Sanctioned']
+        df_inter['Admitted'] = df_inter['Inter Minorities Admitted'] + df_inter['Inter NonMinorities Admitted']
+
+        # Combine and calculate
+        df_final = pd.concat([df_v, df_inter], ignore_index=True)
+        df_final['Vacancies'] = df_final['Sanctioned'] - df_final['Admitted']
+        df_final = df_final[['S.No', 'District', 'Institution Name', 'Class', 'Sanctioned', 'Admitted', 'Vacancies']]
+
+        # Download CSV
+        csv_buffer = io.StringIO()
+        df_final.to_csv(csv_buffer, index=False)
+        csv_data = csv_buffer.getvalue()
+
+        st.success("✅ File processed successfully!")
+
+        st.download_button(
+            label="📥 Download Cleaned CSV",
+            data=csv_data,
+            file_name="cleaned_admission_data.csv",
+            mime="text/csv"
+        )
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+    except Exception as e:
+        st.error(f"❌ Error processing file: {e}")