CST383 - Week 2

This week we continued learning about Pandas. We learned about aggregate(), filter(), transform(), and apply(). We also learned more advanced ways to retrieve data like using 'groupby" and calculating the min, max, mean, etc of different columns. Then we started learning more about data visualizations. We saw how to create bar plotss, scatter plots, histograms, and line graphs from the data using matplotlib, Pandas, and Seaborn. We compared the different types of graphs, the different libraries, and different ways to retrieve significant data.

There were three parts to the homework. The first part was 16 questions to help us practice using Pandas series. Each question could be answered using only 1 line of code. Next, we were instructed to choose an especially effective data visualization and write about it. I chose a graph showing the percentages of women employed by major tech companies (pictured right). I wrote about the different elements and how the graphic is simple, yet both effective and visually pleasing. Lastly, we were assigned questions to answer based on Chapter 2 of the textbook. Thankfully, I was able to finish all of the homework parts relatively quickly and easily.