How to understand Python Visualization Matplotlib
How to understand Python visual Matplotlib, in view of this problem, this article introduces the corresponding analysis and solution in detail, hoping to help more partners who want to solve this problem to find a more simple and feasible method.
1. What is Matplotlib?
Matplotlib is specifically used to develop 2D charts (including 3D charts) to achieve data visualization in a gradual and interactive manner. Using python to operate the matplotlib library makes it very convenient to display the graphics.
Visualization is a key auxiliary tool in the whole data mining, which can clearly understand the data and adjust our analysis methods.
The data can be visualized and presented more intuitively.
Make the data more objective and persuasive
two。 Implement the simplest Matplotlib drawing with a line chart as an example 2.1 matplotlib.pyplot module
Matplotlib.pytplot contains a series of drawing functions similar to matlab. So the first step is to import the matplotlib package.
Import matplotlib.pyplot as plt2.2 graphic drawing process
The three most basic steps of graphics rendering can be summarized as follows: creating a canvas, drawing an image, and displaying an image.
1. Create canvas-plt.figure () plt.figure (figsize= (), dpi=) figsize: specify the length and width of the graph dpi: the sharpness of the image returns fig object 2. Draw image-plt.plot (x, y) plt.figure (figsize= (), dpi=) figsize: specify the length and width of the graph dpi: the sharpness of the image returns fig object 3. Display Image-plt.show () 2.3 Line Chart drawing and display
For example: show the weather of a week in Jiangsu, for example, the weather temperature from Monday to Sunday is as follows
Import matplotlib.pyplot as pltimport randomplt.figure (figsize= (20,8), dpi=100) x = range (7) y_jiangsu = [random.uniform (10,25) for i in x] # take the random number plt.plot (x, y_jiangsu) plt.show () from 10 to 24
This is the answer to the question about how to understand Python visualization Matplotlib. I hope the above content can be of some help to you. If you still have a lot of doubts to be solved, you can follow the industry information channel to learn more about it.
