CST383 Learning Log #1

This was the first week of CST383 and we focused on building a strong foundation in Python for data science, especially working with NumPy and basic scripting tools. I practiced creating and manipulating arrays, including slicing, fancy indexing, and boolean masking. I also learned how vectorized operations allow computations to be performed efficiently across entire arrays without using loops. Working with both 1D and 2D arrays helped me better understand how to access specific rows and columns, as well as how to compute statistics like mean and median along different axes. In addition, I explored filtering data using conditions and using those filters to extract subsets of interest.

One concept that I found a bit confusing at first was how boolean masks need to match the shape of the array they are indexing. For example, trying to index an array with a mask of a different length results in an error, which made me realize how important array dimensions are in NumPy. This made me ask: How can I systematically check and debug shape mismatches when working with larger datasets? Overall, this week strengthened my understanding of data manipulation and prepared me for more advanced topics.

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