Summary
In this chapter, we presented three main points. Firstly, we figured out the relationship between raw data, information and knowledge. Due to its contribution to our lives, we continued to discuss an overview of data analysis and processing steps in the second section. Finally, we introduced a few common supported libraries that are useful for practical data analysis applications. Among those, in the next chapters, we will focus on Python libraries in data analysis.
Practice exercises
The following table describes users' rankings on Snow White movies:
|
UserID |
Sex |
Location |
Ranking |
|---|---|---|---|
|
A |
Male |
Philips |
4 |
|
B |
Male |
VN |
2 |
|
C |
Male |
Canada |
1 |
|
D |
Male |
Canada |
2 |
|
E |
Female |
VN |
5 |
|
F |
Female |
NY |
4 |
Exercise 1: What information can we find in this table? What kind of knowledge can we derive from it?
Exercise 2: Based on the data analysis process in this chapter, try to define the data requirements and analysis steps needed to predict whether user B likes Maleficent movies or not.
