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| # modules/text.py | |
| # -*- coding: utf-8 -*- | |
| # | |
| # PROJECT: CognitiveEDA v5.0 - The QuantumLeap Intelligence Platform | |
| # | |
| # DESCRIPTION: Specialized module for basic text analysis, focused on generating | |
| # a word cloud visualization from a text-heavy column. | |
| import base64 | |
| import io | |
| import logging | |
| import pandas as pd | |
| from wordcloud import WordCloud | |
| def generate_word_cloud(df: pd.DataFrame, text_col: str) -> str: | |
| """ | |
| Generates a word cloud from a text column and returns it as an HTML object. | |
| The function processes the text, generates a word cloud image, encodes it | |
| in Base64, and embeds it within an HTML string for display in Gradio. | |
| Args: | |
| df: The input DataFrame. | |
| text_col: The name of the column containing text data. | |
| Returns: | |
| An HTML string containing the word cloud image or a status/error message. | |
| """ | |
| # 1. Input Validation | |
| if not text_col: | |
| return "<p style='text-align:center; padding: 20px;'>Select a text column to generate a word cloud.</p>" | |
| if text_col not in df.columns: | |
| return f"<p style='text-align:center; color:red; padding: 20px;'>Error: Column '{text_col}' not found in the dataset.</p>" | |
| try: | |
| logging.info(f"Generating word cloud for column '{text_col}'") | |
| # 2. Text Corpus Preparation | |
| # Concatenate all non-null text entries into a single string | |
| text_corpus = ' '.join(df[text_col].dropna().astype(str)) | |
| if not text_corpus.strip(): | |
| logging.warning(f"Column '{text_col}' contains no text data to generate a cloud.") | |
| return "<p style='text-align:center; padding: 20px;'>No text data available in this column to generate a cloud.</p>" | |
| # 3. Word Cloud Generation | |
| wordcloud = WordCloud( | |
| width=800, | |
| height=400, | |
| background_color='white', | |
| colormap='viridis', | |
| max_words=150, | |
| collocations=False # Avoids generating two-word phrases | |
| ).generate(text_corpus) | |
| # 4. Image Encoding | |
| buf = io.BytesIO() | |
| wordcloud.to_image().save(buf, format='png') | |
| img_str = base64.b64encode(buf.getvalue()).decode('utf-8') | |
| # 5. HTML Output | |
| # The style attribute makes the image responsive to container width | |
| html_content = ( | |
| f'<div style="text-align:center; padding: 10px;">' | |
| f'<img src="data:image/png;base64,{img_str}" alt="Word Cloud for {text_col}" ' | |
| f'style="border-radius: 8px; max-width: 100%; height: auto;">' | |
| f'</div>' | |
| ) | |
| return html_content | |
| except Exception as e: | |
| logging.error(f"Word cloud generation failed for column '{text_col}': {e}", exc_info=True) | |
| error_msg = f"Could not generate word cloud. An unexpected error occurred: {e}" | |
| return f"<p style='text-align:center; color:red; padding: 20px;'>❌ **Error:** {error_msg}</p>" |