Survey Data Analysis Pipeline with Python

Act as a data analyst. Write a complete Python pipeline to analyze survey data from a CSV file. The pipeline should: (1) **Data cleaning**: Handle missing values (drop vs impute based on column type), remove duplicate responses, validate email format, flag suspicious entries (completed in <30 seconds, all same answers). (2) **Likert scale analysis**: For 5-point scale questions, calculate mean, median, mode, and standard deviation. Generate a diverging stacked bar chart showing response distribution. (3) **Cross-tabulation**: Create crosstabs between demographic variables (age group, department) and satisfaction scores. Include chi-squared test for statistical significance. (4) **Open-ended response analysis**: Use simple NLP (word frequency, bigrams) to identify common themes in free-text responses. Generate a word cloud. (5) **Automated report**: Generate a PDF report with all charts, key findings (auto-generated summary sentences), and a methodology section. Use pandas, matplotlib/seaborn, scipy, and fpdf2. Include sample CSV structure and example output screenshots description.