CST 383 - Intro to Data Science | Week 1
Learning log 1: This week I learned the basics of the course, the homework policy, and how Python is used in data science. The biggest topic for me was NumPy. I learned that NumPy arrays are useful because they make it easier to work with a lot of numbers at once. Instead of writing loops for everything, I can use vectorized operations like tuition > 12000 or x * 10, and NumPy applies it to the whole array. One thing that made more sense after doing the labs was slicing versus fancy indexing. Slicing is like x[:3] or x[-3:], where I am taking a range of values. Fancy indexing is when I choose specific positions, like x[[0, 2, 4]]. At first these felt similar, but now I see that slicing is more about a continuous section and fancy indexing is more about picking exact values. Boolean masks were probably the most important idea for me this week. A mask is an array of True and False values that can filter another array. For example, tuition[tuition > 12000] gives only the tuition val...