Update app.py

app.py

@@ -1,83 +1,49 @@
 import streamlit as st
 import pandas as pd
-import plotly.graph_objects as go
+import plotly.express as px
 
 # Title of the App
-st.title("Excel Data Visualization with Dual Y-Axis")
+st.title("Smart Data Visualization App")
 
-# Upload Section
+# File Upload Section
 uploaded_file = st.file_uploader("Upload your Excel file", type=["xlsx", "xls"])
 
 if uploaded_file:
     try:
-        # Read the Excel file into a DataFrame
+        # Load the Excel file into a DataFrame
         df = pd.read_excel(uploaded_file)
-
-        # Preview the uploaded data
         st.write("Data Preview:")
         st.dataframe(df)
 
-        # Ensure required columns are present
-        required_columns = ["Description", "Oct'24", "Nov'24", "Dec/(Inc)"]
-        if not all(column in df.columns for column in required_columns):
-            st.error(f"The uploaded file must contain the following columns: {', '.join(required_columns)}")
-        else:
-            # Plot the Graph
-            fig = go.Figure()
-
-            # Add Bar Traces for Oct'24 and Nov'24
-            fig.add_trace(go.Bar(
-                x=df["Description"],
-                y=df["Oct'24"],
-                name="Oct'24",
-                marker_color='blue'
-            ))
-
-            fig.add_trace(go.Bar(
-                x=df["Description"],
-                y=df["Nov'24"],
-                name="Nov'24",
-                marker_color='green'
-            ))
-
-            # Add Line Trace for Dec/(Inc) on Secondary Y-axis
-            fig.add_trace(go.Scatter(
-                x=df["Description"],
-                y=df["Dec/(Inc)"],
-                name="Dec/(Inc)",
-                mode="lines+markers",
-                marker=dict(color='red'),
-                yaxis="y2"
-            ))
-
-            # Update Layout for Dual Y-axis
-            fig.update_layout(
-                title="Dual Axis Chart",
-                xaxis=dict(title="Description"),
-                yaxis=dict(
-                    title="Values (Oct'24 and Nov'24)",
-                    titlefont=dict(color="blue"),
-                    tickfont=dict(color="blue"),
-                ),
-                yaxis2=dict(
-                    title="Dec/(Inc)",
-                    titlefont=dict(color="red"),
-                    tickfont=dict(color="red"),
-                    overlaying="y",
-                    side="right"
-                ),
-                barmode="group",
-                legend=dict(x=0.5, y=1.2, orientation="h"),
-                template="plotly_white"
-            )
-
-            # Render the Plot
+        # User selects columns to visualize
+        x_axis = st.selectbox("Select X-axis column", df.columns)
+        y_axis = st.multiselect("Select Y-axis column(s)", [col for col in df.columns if col != x_axis])
+
+        if x_axis and y_axis:
+            # Determine the best type of graph
+            if df[x_axis].nunique() < len(df[x_axis]) * 0.5:
+                # If the X-axis is categorical, choose a bar chart
+                chart_type = "Bar Chart"
+                fig = px.bar(df, x=x_axis, y=y_axis, barmode="group")
+            elif len(y_axis) == 1:
+                # For single numerical column, plot a line chart
+                chart_type = "Line Chart"
+                fig = px.line(df, x=x_axis, y=y_axis[0])
+            else:
+                # If multiple numerical columns are selected, use a scatter plot matrix
+                chart_type = "Scatter Matrix"
+                fig = px.scatter_matrix(df, dimensions=y_axis, color=x_axis)
+
+            # Display the selected chart type and plot
+            st.write(f"Automatically Selected Chart Type: {chart_type}")
             st.plotly_chart(fig)
+        else:
+            st.info("Please select columns for the X and Y axes to visualize.")
     except Exception as e:
         st.error(f"Error processing the file: {e}")
 else:
-    st.info("Please upload an Excel file to get started.")
+    st.info("Upload an Excel file to get started.")
 
 # Footer
 st.write("---")
-st.write("Developed using [Streamlit](https://streamlit.io) and [Hugging Face Spaces](https://huggingface.co/spaces).")
+st.write("Powered by [Streamlit](https://streamlit.io) and [Plotly](https://plotly.com).")