As the saying goes ： Words are not as good as words , Chart is not as good as table .
Human beings are naturally visual animals . Imagine a textbook , If there is no chart 、 Illustration or flow chart , It will become more boring and difficult to understand . Visual effects for data analysis 、 It's crucial to communicate the results .
Data visualization is through easy to read 、 Easy to understand chart , Make it easier for users to understand , In order to achieve the purpose of telling a story to users with numbers .
Take a look at the following works , You'll understand the power of data visualization better ：
「 reach ・ Finch manuscript 」
author >> The Visual Agency
Those remarks >> 《 Atlantic manuscript 》 It's the largest of Leonardo da Vinci's manuscripts , common 12 volume ,1119 Zhang . Each block on the top represents the manuscript , Color represents the subject involved , Including geometry and Algebra 、 Physics and Natural Science 、 Tools and machines 、 Architecture and Applied Arts and Humanities .
author >> frédérik ruys
Those remarks >> This visualization helps friends fans look back on their relationships .Ross and Rachel Between the opening and closing of the opening and closing of …… Closing, opening and closing , The most ancient and weird Phoebe Finally found true love Mike ！ And sexy Monica And sweetie Chandler From the fifth season, the inseparable sweetness like the twist .
How to realize data visualization ？
Data visualization , The steps are not complicated , We take the most commonly used data analysis tools Python For example ：
1、 Data acquisition
one can't make bricks without straw , So step one , We need to get the data we need according to our goals .
Data acquisition can be divided into external data and internal data . External data can be queried from public data websites , Another way is to use reptiles , This approach will be more flexible .
Internal data is the internal data of the enterprise itself , As a data analyst , Need to use sql And other tools to extract the data .
2、 Data analysis
The second step , We need to clean up the data and analyze the data .
Data cleaning is mainly to solve the problem of data quality , In data collection , Data tends to be messy , Be commonly called “ Dirty data ”, Data cleaning is needed , Including completion of missing values 、 Delete the outliers 、 duplicate value 、 Data conversion and so on .
After processing the data , You can start to analyze , According to your goal , Choose the right method to analyze .
3、 Data visualization
After drawing a conclusion through data analysis , It also needs to be shown graphically , As the saying goes ,“ Not as good as the table , Chart is not as good as table ", Use a chart to show your conclusion more clearly .
Here I want to learn Python Data visualization students recommend a course ：《11 A case study Python Data visualization 》.
Study this course , You can go through 11 A practical one Python Data analysis project , To master in actual combat Python Every aspect of Visualization , At the same time, accumulate project experience . You will do the following projects yourself ：
Interested students , Welcome to the laboratory building while typing the code ～
Course address ：11 A case study Python Data visualization www.lanqiao.cn