I have a single CSV file that contains a mix of numerical columns and categorical labels. Before I can move on to analysis, the data needs a solid clean-up: remove or impute missing values, fix obvious data-entry anomalies, standardise text categories, and ensure each field is in the correct type. Once the dataset is tidy, I want to explore it visually. I am especially interested in bar charts, line graphs and scatter plots that help surface the main trends and relationships hidden in the numbers and categories. Feel free to suggest any additional plots that would add real insight; however, the three mentioned above are the minimum I need delivered. Python with pandas, NumPy and either Matplotlib or Seaborn is perfectly fine, but I am open to R or another proven toolset if you prefer—it just has to be reproducible. Deliverables • Cleaned CSV ready for downstream work • The code or notebook used (well-commented so I can rerun it) • High-resolution bar charts, line graphs and scatter plots (PNG or PDF) with brief captions explaining the findings If the work is done in a notebook, a quick summary section that interprets the visuals will be appreciated.