Using NumPy to Analyze My Daily Habits (Sleep, Screen Time & Mood)

A personal project demonstrates how to use the NumPy library to analyze fictional daily habit data, including sleep, study hours, screen time, and mood over a 30-day period. The analysis involves loading the data from a .npy file, validating its integrity, and splitting the 30-day dataset into four weekly chunks using `np.array_split`. By calculating weekly averages for each metric with `np.mean`, patterns emerge, such as a correlation between study hours, screen time, and mood. The project serves as a practical tutorial to learn NumPy by applying its functions to a relatable, real-world-style problem, even with simulated data.