Summary
In this chapter, we first discussed sources of open data, which included The Bureau of Labor Statistics, the Census Bureau, Professor French's data library, the Federal Reserve's data library, and the UCI Machine Learning Depository. After that, we showed you how to input data; how to deal with missing data; how to sort, slice, and dice the datasets; and how to merge different datasets. Data output was discussed in detail. For different languages, such as Python, R, and Julia, several relevant packages for data manipulation were introduced and discussed.
In Chapter 4, Data Visualization, we will discuss data visualization in R, Python, and Julia separately. To make our visual presentation more eye catching, we will show how you to ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access