- Hands-On Data Science with Anaconda
- Dr. Yuxing Yan James Yan
- 240字
- 2021-06-25 21:08:52
Importance of data visualization
For learners, users, or researchers in the areas of data science and business analytics, using various types of graphs, pie charts, bar charts, and other visual means to show some underlying trend or pattern implied by data is vital to understand data and to help researchers present their data to their audience or clients better. There are several reasons for this. First, it is sometimes difficult to describe our findings, especially when we have several patterns or influencing factors. With several separate graphs and a joint one, complex relationships can be understood or explained better.
We can use graphs or pictures to explain certain algorithms, such as the Bisection method (see the section related to dynamic visual presentation, Dynamic visualization).
We can also use relative sizes to represent different meanings. In finance, a basic concept is called time value of money (TVM). It means that a bird in the hand is worth two in the bush. Today's $100 is more valuable than a future cash flow of the same amount. With different sizes of different circles representing the present value of cash flow occurring at different points in time in the future, learners can understand this concept much more clearly.
Lastly, our data might be quite messy, and simply showing the data points would confuse audiences further. If we could have a simple graph to show its main characteristics, properties, or patterns, it would help greatly.
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