I need a well-structured exploratory analysis of a dataset that combines numerical columns with free-text fields. The work will live in a single, clearly commented Jupyter Notebook and should make full use of the Python stack I already rely on: pandas and NumPy for wrangling, matplotlib and seaborn for plots, scikit-learn for vectorisation and any basic modelling, plus NLTK or spaCy for text cleaning and tokenisation. Should deeper experimentation help, feel free to reach for TensorFlow/Keras or XGBoost, but only if they add insight. Here is what I’d like to see when you hand the notebook back: • Cleaned and well-documented preprocessing steps for both the numeric and text portions • Informative visuals that highlight key distributions, correlations, and any interesting patterns you uncover • A concise narrative of findings embedded in Markdown so the story is readable alongside the code Everything must run end-to-end with no broken cells on a vanilla Python 3 install. When you reply, point me to past work that proves you have done similar mixed-data analyses; links to GitHub notebooks are perfect.