Update app.py

app.py

@@ -118,30 +118,40 @@ def analyze_data(data, visualization_type, class_size=10):
     prompt = generate_groq_prompt(data, visualization_type, class_size)
     return prompt
 
-# Function to generate a prompt with an indented table
 def generate_groq_prompt(data, visualization_type, class_size):
     # Limit the preview to the first 10 rows for readability
-    data_snippet = data.head(10)
+    data_snippet = data.head(10)  # Select top 10 rows for the preview
 
-    # Convert the data to a string table format with proper indentation
-    table_string = data_snippet.to_markdown(index=False, tablefmt="grid")
+    # Compute column widths for alignment
+    column_widths = [max(len(str(val)) for val in [col] + data_snippet[col].tolist()) for col in data_snippet.columns]
 
-    # Create the prompt text with the table included
+    # Create the table header with spacing
+    table_header = " ".join(f"{col:<{column_widths[i]}}" for i, col in enumerate(data_snippet.columns))
+
+    # Create the rows with spacing
+    table_rows = "\n".join(
+        "    " + " ".join(f"{str(val):<{column_widths[i]}}" for i, val in enumerate(row))  # Add indentation
+        for row in data_snippet.values
+    )
+
+    # Combine header and rows into a single table
+    formatted_table = f"    {table_header}\n{table_rows}"
+
+    # Create the textual prompt
     prompt = f"""
     The user has uploaded a dataset and selected the '{visualization_type}' visualization type with a class size of {class_size}.
     Below is a preview of the dataset:
 
-    ```
-    {table_string}
-    ```
+    {formatted_table}
 
-    Please generate Python code that achieves the requested visualization. For data, please write it directly in the code rather than using file input.
+    Please generate Python code for the analysis and visualization specified.
     """
 
     return prompt
 
 
 
+
 # Streamlit App
 st.title("Data Analysis AI")
 st.markdown("Upload a file (CSV or Excel) to analyze it.")