I will provide you with a raw export of our sales data, and I need a clear, actionable analysis that highlights key trends and patterns. Using NumPy, Pandas, and Matplotlib as the core tool-set, please: • Clean and structure the dataset so it is analysis-ready (handle missing values, normalize column names, parse dates, etc.). • Explore the data to surface seasonality, growth or decline segments, and any outliers worth flagging. • Produce a concise narrative report (PDF or Markdown) that explains your findings in plain language and includes actionable recommendations for our sales strategy. • Create a set of high-resolution visualizations—specifically line charts, bar graphs, scatter plots, and histogram plots—that illustrate the most important insights. Save each figure as both PNG and the original editable format. • Deliver a fully reproducible Jupyter Notebook (or .py script) that contains all code, comments, and step-by-step explanations so my team can rerun or extend the analysis later. Accuracy, clarity, and clean coding practices are essential. If you prefer to enhance the visuals with Seaborn or plotly, feel free, as long as the core requirements above are met.