Add deploy assets and update telemetry datasets

Prepare deployment package and clean telemetry/lab data: add deploy/ (README, datasaurus.csv, datasets and lab01 notebooks), add new lab02 dataset notebook variants (lab02_task1_datasets_v2/ v2b) and solutions for task3, and update multiple lab02 telemetry and git-activity notebooks. Clean and normalize claude/dataset_A_indie_game_telemetry_clean.csv (fill/standardize timestamps, session lengths and other fields) to improve consistency for downstream analysis.

deploy/README.md

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+# Lab 02 — Environment Setup
+
+This document explains how to set up your Python environment and install all required packages before the lab session.
+
+---
+
+## Requirements
+
+- **Python 3.10 or higher** (3.11 recommended or live wildly and go for the latest one. I have not tested it...)
+- **pip** (comes bundled with Python)
+- A code editor with Jupyter notebook support — [VS Code](https://code.visualstudio.com/) with the [Jupyter extension](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter) is recommended
+
+---
+
+## Step 1: Create a virtual environment
+
+It is strongly recommended to work inside a virtual environment to avoid conflicts with other Python projects on your machine.
+
+Open a terminal in the folder where you will work and run:
+
+```bash
+# Create the environment (only needed once)
+python -m venv .venv
+```
+
+Then activate it:
+
+```bash
+# On Windows
+.venv\Scripts\activate
+
+# On macOS / Linux
+source .venv/bin/activate
+```
+
+You should see `(.venv)` appear at the start of your terminal prompt. **You need to activate the environment every time you open a new terminal.**
+
+---
+
+## Step 2: Install required packages
+
+With the environment active, run the following commands:
+
+```bash
+# Core data libraries
+pip install "numpy<2.0"
+pip install pandas matplotlib seaborn
+
+# Automated EDA and profiling
+pip install sweetviz
+
+# Interactive dataframe explorer
+pip install dtale
+
+# Jupyter notebook support
+pip install notebook ipykernel
+```
+
+> **Why `numpy<2.0`?** Several packages (including dtale and sweetviz) are not yet fully compatible with NumPy 2.x. Pinning to a 1.x version avoids runtime errors that can be difficult to diagnose.
+
+Alternatively, you can install everything in a single command:
+
+```bash
+pip install "numpy<2.0" pandas matplotlib seaborn sweetviz dtale notebook ipykernel
+```
+
+---
+
+
+## Step 3: Verify the installation
+
+Run the following in a terminal (with the environment active) to confirm everything is working:
+
+```bash
+python -c "
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+import sweetviz as sv
+import dtale
+import numpy as np
+print('numpy   :', np.__version__)
+print('pandas  :', pd.__version__)
+print('seaborn :', sns.__version__)
+print('sweetviz: OK')
+print('dtale   : OK')
+print('All packages installed successfully.')
+"
+```
+
+---
+
+## Step 4: D-Tale in VS Code (Windows)
+
+D-Tale opens in a browser tab via a local server. On Windows, VS Code may not automatically forward the port if D-Tale binds to a network adapter other than the loopback address. All lab notebooks already include the correct launch code:
+
+```python
+d = dtale.show(df, host='127.0.0.1', subprocess=False, open_browser=False)
+print('Open D-Tale at:', d._url)
+```
+
+If the URL does not open automatically, copy it from the output and paste it into your browser. If the page does not load, check the **Ports** panel at the bottom of VS Code and confirm port `40000` is being forwarded.
+
+---
+
+## Files for this lab
+
+| File | Description |
+|---|---|
+| `lab01_task1_datasets.ipynb` | Task 1 — Datasaurus Dozen: why visualisation is essential |
+| `lab01_task2_telemetry.ipynb` | Task 2 — Guided EDA and cleaning of game telemetry data |
+| `lab01_task3_git_activity.ipynb` | Task 3 — Independent EDA and cleaning of Git classroom activity data |
+| `datasaurus.csv` | Dataset for Task 1 |
+| `dataset_A_indie_game_telemetry.csv` | Dataset for Task 2 |
+| `dataset_D_git_classroom_activity.csv` | Dataset for Task 3 |
+
+---
+
+## Troubleshooting
+
+**`ModuleNotFoundError` when running a notebook**  
+The notebook is using a different Python kernel, not the one from your virtual environment. In VS Code, click the kernel name in the top right of the notebook and select **Python (lab02)**.
+
+**NumPy version conflict errors**  
+Make sure you installed `numpy<2.0` as described in Step 2. If you already have a newer version, downgrade with:
+```bash
+pip install "numpy<2.0" --force-reinstall
+```