Update app.py

app.py

@@ -4,6 +4,21 @@ import plotly.express as px
 from io import StringIO
 from datetime import date
 
+# -------------------------------
+# Helpers
+# -------------------------------
+def format_rs(amount):
+    """Format numeric amount into Rupee string with thousands separators."""
+    try:
+        # show no decimals for rupee amounts
+        return f"Rs {int(round(float(amount))):,}"
+    except Exception:
+        return str(amount)
+
+def ensure_numeric_amount(col):
+    """Convert amount column to numeric (int) safely."""
+    return pd.to_numeric(col, errors="coerce").fillna(0).astype(int)
+
 # -------------------------------
 # Page config & CSS
 # -------------------------------
@@ -35,13 +50,16 @@ st.markdown(
         border: 1px solid rgba(255,255,255,0.06);
         box-shadow: 0 6px 18px rgba(0,0,0,0.3);
     }
+    .dataframe td, .dataframe th {
+        color: #e6eef8 !important;
+    }
     </style>
     """,
     unsafe_allow_html=True,
 )
 
 st.title("💸 Expensive Tracker")
-st.caption("Track expenses, analyze spending by category and over time — attractive, simple, and portable.")
+st.caption("Track expenses in Rupees (Rs). Enter whole numbers like 100, 500, 10000.")
 
 # -------------------------------
 # Initialize in-memory storage
@@ -52,6 +70,10 @@ if "expenses" not in st.session_state:
         columns=["Date", "Category", "Amount", "Notes"]
     )
 
+# Ensure Amount column numeric if loaded previously
+if not st.session_state.expenses.empty:
+    st.session_state.expenses["Amount"] = ensure_numeric_amount(st.session_state.expenses["Amount"])
+
 # -------------------------------
 # Sidebar navigation
 # -------------------------------
@@ -65,7 +87,7 @@ CATEGORIES = ["Food", "Travel", "Shopping", "Bills", "Entertainment", "Health",
 # Add Expense
 # -------------------------------
 if page == "Add Expense":
-    st.header("Add a new expense")
+    st.header("Add a new expense (Amount in Rs)")
     with st.form("add_expense_form", clear_on_submit=True):
         c1, c2, c3 = st.columns([1, 1, 1])
         with c1:
@@ -73,36 +95,46 @@ if page == "Add Expense":
         with c2:
             category = st.selectbox("Category", options=CATEGORIES)
         with c3:
-            amount = st.number_input("Amount (₨ or your currency)", min_value=0.0, format="%.2f")
+            # Integer rupee input
+            amount = st.number_input("Amount (Rs)", min_value=0, step=1, format="%d", value=0)
         notes = st.text_area("Notes (optional)", max_chars=200, placeholder="Where/what for?")
         submitted = st.form_submit_button("➕ Add Expense")
 
     if submitted:
-        new_row = {"Date": pd.to_datetime(exp_date).date(), "Category": category, "Amount": float(amount), "Notes": notes}
+        new_row = {
+            "Date": pd.to_datetime(exp_date).date(),
+            "Category": category,
+            "Amount": int(amount),
+            "Notes": notes
+        }
         st.session_state.expenses = pd.concat([st.session_state.expenses, pd.DataFrame([new_row])], ignore_index=True)
-        st.success("Expense added ✅")
+        st.success(f"Expense added ✅ {format_rs(amount)}")
         st.balloons()
 
     if not st.session_state.expenses.empty:
         st.markdown("**Quick preview of latest expenses**")
-        st.dataframe(st.session_state.expenses.tail(6).reset_index(drop=True))
+        preview = st.session_state.expenses.tail(6).reset_index(drop=True).copy()
+        # Format Amount column for display
+        preview["Amount (Rs)"] = preview["Amount"].apply(format_rs)
+        st.dataframe(preview[["Date", "Category", "Amount (Rs)", "Notes"]])
 
 # -------------------------------
 # View Expenses
 # -------------------------------
 elif page == "View Expenses":
-    st.header("All Expenses")
+    st.header("All Expenses (Amounts in Rs)")
     if st.session_state.expenses.empty:
         st.info("No expenses yet — add some from the 'Add Expense' tab.")
     else:
         df = st.session_state.expenses.copy()
+        df["Amount"] = ensure_numeric_amount(df["Amount"])
         # Allow filtering
         st.markdown("Filter")
         cols = st.columns([1, 1, 1])
         with cols[0]:
-            min_date = st.date_input("From", value=df["Date"].min())
+            min_date = st.date_input("From", value=pd.to_datetime(df["Date"]).min().date())
         with cols[1]:
-            max_date = st.date_input("To", value=df["Date"].max())
+            max_date = st.date_input("To", value=pd.to_datetime(df["Date"]).max().date())
         with cols[2]:
             sel_cat = st.multiselect("Category", options=["All"] + CATEGORIES, default=["All"])
         filtered = df[
@@ -112,7 +144,9 @@ elif page == "View Expenses":
         if sel_cat and "All" not in sel_cat:
             filtered = filtered[filtered["Category"].isin(sel_cat)]
 
-        st.dataframe(filtered.sort_values(by="Date", ascending=False).reset_index(drop=True))
+        display_df = filtered.sort_values(by="Date", ascending=False).reset_index(drop=True).copy()
+        display_df["Amount (Rs)"] = display_df["Amount"].apply(format_rs)
+        st.dataframe(display_df[["Date", "Category", "Amount (Rs)", "Notes"]])
 
         # Option to delete last entry or clear all
         st.markdown("---")
@@ -130,53 +164,62 @@ elif page == "View Expenses":
 # Summary Dashboard
 # -------------------------------
 elif page == "Summary":
-    st.header("Summary Dashboard")
+    st.header("Summary Dashboard (Rs)")
     if st.session_state.expenses.empty:
         st.info("No data yet — add expenses to see the summary.")
     else:
         df = st.session_state.expenses.copy()
         df["Date"] = pd.to_datetime(df["Date"])
+        df["Amount"] = ensure_numeric_amount(df["Amount"])
+
         total = df["Amount"].sum()
         avg = df["Amount"].mean()
         max_exp = df["Amount"].max()
         st.markdown("<div class='card'>", unsafe_allow_html=True)
         c1, c2, c3 = st.columns(3)
-        c1.metric("Total Spent", f"{total:,.2f}")
-        c2.metric("Average Expense", f"{avg:,.2f}")
-        c3.metric("Largest Expense", f"{max_exp:,.2f}")
+        c1.metric("Total Spent", format_rs(total))
+        c2.metric("Average Expense", format_rs(avg))
+        c3.metric("Largest Expense", format_rs(max_exp))
         st.markdown("</div>", unsafe_allow_html=True)
 
         st.markdown("### 📊 Expenses by Category")
         cat_summary = df.groupby("Category", as_index=False)["Amount"].sum().sort_values("Amount", ascending=False)
+        # For plotly, keep numeric values; labels can show Rs via hover
         fig_pie = px.pie(cat_summary, names="Category", values="Amount", title="Spending by Category", hole=0.4)
+        fig_pie.update_traces(textinfo="percent+label", hovertemplate="%{label}: Rs %{value:,}<extra></extra>")
         st.plotly_chart(fig_pie, use_container_width=True)
 
         st.markdown("### 🕒 Expenses Over Time")
         timeseries = df.groupby(pd.Grouper(key="Date", freq="D"))["Amount"].sum().reset_index()
-        # Fill missing days for smooth line
         timeseries = timeseries.set_index("Date").resample("D").sum().fillna(0).reset_index()
         fig_line = px.bar(timeseries, x="Date", y="Amount", title="Daily Spending (bar)")
+        fig_line.update_traces(hovertemplate="Date: %{x}<br>Amount: Rs %{y:,}<extra></extra>")
         st.plotly_chart(fig_line, use_container_width=True)
 
         st.markdown("### 🔎 Top 5 Expenses")
-        st.dataframe(df.nlargest(5, "Amount")[["Date", "Category", "Amount", "Notes"]].reset_index(drop=True))
+        top5 = df.nlargest(5, "Amount")[["Date", "Category", "Amount", "Notes"]].reset_index(drop=True).copy()
+        top5["Amount (Rs)"] = top5["Amount"].apply(format_rs)
+        st.dataframe(top5[["Date", "Category", "Amount (Rs)", "Notes"]])
 
 # -------------------------------
 # Import / Export
 # -------------------------------
 elif page == "Import / Export":
-    st.header("Import or Export your data")
-    st.markdown("You can download your current expenses as a CSV or upload a CSV to load expenses.")
+    st.header("Import or Export your data (CSV)")
+    st.markdown("You can download your current expenses as a CSV or upload a CSV to load expenses. Amounts are stored as integers (Rs).")
 
     # Download
     if st.session_state.expenses.empty:
         st.info("No expenses to export.")
     else:
-        csv = st.session_state.expenses.to_csv(index=False)
+        # Ensure numeric amounts before export
+        export_df = st.session_state.expenses.copy()
+        export_df["Amount"] = ensure_numeric_amount(export_df["Amount"])
+        csv = export_df.to_csv(index=False)
         st.download_button("⬇️ Download CSV", data=csv, file_name="expenses.csv", mime="text/csv")
 
     st.markdown("---")
-    st.markdown("Upload a CSV file (columns: Date, Category, Amount, Notes)")
+    st.markdown("Upload a CSV file (columns: Date, Category, Amount, Notes). Amounts should be numeric (Rs).")
     uploaded = st.file_uploader("Upload CSV", type=["csv"])
     if uploaded is not None:
         try:
@@ -186,8 +229,11 @@ elif page == "Import / Export":
             if not required.issubset(set(uploaded_df.columns)):
                 st.error("CSV must include at least Date, Category, and Amount columns.")
             else:
-                # Append uploaded
-                uploaded_df = uploaded_df[["Date", "Category", "Amount", "Notes"]] if "Notes" in uploaded_df.columns else uploaded_df.assign(Notes="")
+                # Normalize columns and types
+                if "Notes" not in uploaded_df.columns:
+                    uploaded_df["Notes"] = ""
+                uploaded_df = uploaded_df[["Date", "Category", "Amount", "Notes"]]
+                uploaded_df["Amount"] = ensure_numeric_amount(uploaded_df["Amount"])
                 uploaded_df["Date"] = pd.to_datetime(uploaded_df["Date"]).dt.date
                 st.session_state.expenses = pd.concat([st.session_state.expenses, uploaded_df], ignore_index=True)
                 st.success("Uploaded expenses added to your tracker.")