I. Introduction
In the last few articles, we have learned that "data" is a huge system (as shown in the figure below), and used the example of the vegetable market to explain the meaning of data sources; use the example of buying vegetables to explain the data for everyone The steps of collection; using the example of washing and choosing dishes, I will explain the method of data cleaning...
Today, I will mainly explain to you how to teach cooking methods to others in a simple and easy-to-understand manner after we learn how to cook, that is , the process of data visualization.
2. What is data visualization (definition)
We know that humans are natural visual animals, and our sensitivity to colors and diagrams is much higher than pure numbers...
Data visualization is actually the process of visually expressing abstract concepts and visualizing abstract indicators and data in concrete graphics.
As far as the classification of the " data visualization " family is concerned, there are mainly the following three major branches, the details are as follows~
This article mainly focuses on information visualization. Firstly, because information visualization is the closest to our lives; secondly, scientific visualization and visual analytics do require an academic foundation. For example, "visual text mining" is currently popular in the field of visual analytics; This involves K-Means, text mining and other technologies. It is basically impossible to thoroughly explain it without an academic foundation.
We often hear words like "content visualization" and "report visualization" in our workplace work reports. These requirements are actually in the category of "information visualization".
First look at the picture below. It is the annual ticket sales data of a certain company. The left side is pure data, and the right side is the line chart after information visualization. I don't need to say which one is clearer~
But, have you ever thought about bar graphs, pie graphs, bubble graphs... Why do we use line graphs here? This involves the selection of visual charts, and I will focus on explaining them later~
3. Common mistakes and pitfalls of data visualization (misunderstanding warnings that novices must see)
Have you been shot for the wrong demonstrations used in the following diagrams?
Case 1: The following is the ticketing situation of a company. The bar chart on the left is before the chart is modified; the line chart on the right is after the chart is modified.
So, what is the problem with the histogram on the left?
- The subject is not clear (Is it trying to show the monthly change trend of the Received and Processed states within a year and 12 months, or the monthly gap between the Received and Processed states?);
- The trend is not obvious (the histogram on the left, at first glance, I only know that there are two different states of red and blue, but the level of the histogram is not uniform, and the specific trends of the two states of Received and Processed cannot be seen at a glance);
- Visual fatigue (in the histogram on the left, if I want to
compare the trend of the Received Ticket, I need the human eye to "automatically block" each red histogram. Visual fatigue is really not a little bit...);
So, what problem does the line chart on the right solve?
It cleverly displays the two trend states that the histogram on the left "brakes my brain" through the line chart. If you want to know the chain trend of the Received and Processed states in 12 months, just look at a broken line. That's enough; if you want to know the data difference between the Received and Processed states in a single month, just look at the corresponding y-axis intercept.
Case 2: The following is the trend chart of the retail value of 5 products of a company in the seven years from 2008 to 2014.
Imagine that you are the chairman of this retail company. Two marketing directors, A and B, come up with two analysis reports on the left and right. Which chart would you like to look at? The answer is obvious, B beats A!
As a boss, you just want to get the following information. First, the sales trends of these 5 products in 7 years; second, the sales contribution and ranking of these 5 products in 7 years; third, the average sales of the 5 products The gap between.
The above three types of information can be clearly displayed in Figure B, while Figure A requires the chairman to draw a trend chart to find out.
Fourth, the conclusion
After reading the above two cases, is there a feeling of bliss?
In fact, in daily life, many workplace novices think that the data that I have presented is as long as it is not "pure data" like the following. As everyone knows, inserting a few misleading charts indiscriminately makes it even more professional that you are not professional enough!
So what are the rules behind the chart specification?
The next issue will continue to reveal the secret for you!