Journal 40
May 6 - May 12 This is one of the few courses I have taken where I can actually say I am excited to sit down and start learning each week. This week's lectures and videos helped me better understand how important data distributions and aggregation are in the data science field. At the start, many of the Pandas operations felt like separate tools I had to memorize, which would explain the Pandas flashcards we are given in the course modules, but after working through the homework labs (and my gosh, did that take me a while), I began to see how they connect together when analyzing datasets. I learned how to use series and dataframes, apply aggregation functions such as mean and median, how to group data with groupby(), and how to use value_counts() . These all help to summarize categorical variables, and definitely came in handy for the labs. I also got some more practice with boolean masks and vectorized operations, which I prefer over writing loops. I think the biggest thing I le...