In today's data-driven world, making sense of complex datasets can feel like navigating a maze. But what if you could simply ask a question in plain English and have an AI generate the perfect visualization, explaining its choices along the way? Enter V-RECS, a groundbreaking new tool that's transforming how we interact with data. Imagine typing a question like, "Which product lines generate the most revenue?" and instantly receiving a clear, insightful chart. V-RECS not only generates the visualization but also provides a detailed explanation of why specific data points were chosen, offers a caption summarizing the chart's key takeaways, and even suggests further avenues for exploration. This narrative approach not only makes the insights more accessible but also builds trust in the AI's recommendations. Traditional data visualization tools often require specialized knowledge or complex coding. V-RECS, powered by a Large Language Model (LLM) called Llama-2-7B, bridges this gap by understanding natural language queries. This innovative use of LLMs makes data exploration intuitive and efficient, empowering users of all skill levels to unlock hidden patterns and make data-driven decisions. What sets V-RECS apart is its unique "teacher-student" training method. A powerful LLM, GPT-4, acts as the teacher, providing detailed reasoning steps and explanations for various data scenarios. Llama-2-7B, the student, learns from these examples and develops the ability to generate its own insightful narratives. This approach ensures high performance while using a smaller, more cost-effective, and open-source model, making it more accessible and adaptable for wider use. While V-RECS demonstrates impressive capabilities, challenges such as refining visualization literacy coverage and expanding the forms of narrative remain. Future research aims to enhance visual support for explanations, explore alternative visualizations for the same query, and further improve the quality and diversity of suggestions. However, V-RECS represents a significant leap forward in democratizing data visualization, paving the way for a future where anyone can easily transform raw data into actionable insights.