How to add labels to Matplotlib images in Python
1. Add text label plt.text()
is used to add text at the specified coordinate position on the image during the drawing process. What needs to be used is the plt.text() method.
Its main parameters are three:
plt.text(x, y, s)
where x and y represent the x and y axis coordinates of the incoming point. s represents a string.
It should be noted that the coordinates here, if xticks and yticks labels are set, do not refer to the labels, but the original values of the x and axes when drawing.
Because there are too many parameters, I will not explain them one by one. Learn their usage based on the code.
ha = 'center’
means the vertical alignment is centered, fontsize = 30
means the font size is 30, rotation = -25
means rotation The angle is -25 degrees. c
Set the color, alpha
set the transparency. va
represents horizontal alignment.
1. Example
The code adds two pieces of text to the image, one is an italic watermark of "Wide on the Journey~" with an transparency of 0.4.
The other section is to mark the closing price of the day near each vertex of the polyline.
import matplotlib.pyplot as plt plt.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['axes.unicode_minus'] = False x = range(9) y = [5.12, 5.15, 5.13, 5.10, 5.2, 5.25, 5.19, 5.24, 5.31] c = 0.5 * (min(x) + max(x)) d = min(y) + 0.3 * (max(y) - min(y)) # 水印效果 plt.text(c, d, '旅途中的宽~', ha = 'center', fontsize = 30, rotation = -25, c = 'gray', alpha = 0.4) plt.plot(x, y, label = '股票A收盘价', c = 'r', ls = '-.', marker = 'D', lw = 2) plt.xticks(x, [ '2022-03-27', '2022-03-28', '2022-03-29', '2022-03-30', '2022-03-31', '2022-04-01', '2022-04-04', '2022-04-05', '2022-04-06'], rotation = 45) plt.title('某股票收盘价时序图') plt.xlabel('日期') plt.ylabel('价格') plt.grid(True) plt.legend() # 标出每天的收盘价 for a, b in zip(x, y): plt.text(a, b + 0.01, '%.2f' % b, ha = 'center', va = 'bottom', fontsize = 14) plt.show()
2. Add comments plt.annotate()
Based on the above example code, add comments. An annotation is an explanation of a certain location in the image, which can be pointed to with an arrow.
Add annotations using plt.annotate()
method
The common parameters in its syntax are as follows
plt.annotate(str,xy,xytext,xycoords,arrowcoords)
wherestr
is the string to be used in the comment, that is, the comment text; xy
refers to the coordinate point being commented; xytext
refers to the position where the comment text is to be written; xycoords
It is the coordinate system attribute of the annotated point, that is, how to describe the coordinates of the point. The setting value defaults to "data", which is described by (x, y) coordinates. Other optional setting values are as follows, where figure refers to the entire canvas as a reference system. And axes means only for one of the axes object areas.
arrowprops
is a dictionary used to set the properties of arrows. Parameters written outside this dictionary represent attributes of the annotation text.
The values that can be set in the dictionary are:
#Further explanation of these parameters: The total length of the arrow is first determined by the position coordinates of the annotated point and the annotation The length of the arrow is determined by the text position coordinates. You can further adjust the length of the arrow by adjusting the shrink key in the parameter arrowprops. shrink represents the percentage of the shortened length of the arrow to the total length (the length determined by the position coordinates of the annotated point and the annotation text position coordinates). . When shrink is not set, shrink defaults to 0, that is, no shortening. When shrink is very large, close to 1, its effect is equivalent to no shortening.
1. Example
Take marking the lowest price point on the chart as an example. Add a red arrow and the words "lowest price" at the target position.
Other parameters, such as setting the font of the annotation text, c or color represents the color, and fontsize represents the font size. Learn more about the properties and try them yourself.
import matplotlib.pyplot as plt plt.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['axes.unicode_minus'] = False x = range(9) y = [5.12, 5.15, 5.13, 5.10, 5.2, 5.25, 5.19, 5.24, 5.31] c = 0.5 * (min(x) + max(x)) d = min(y) + 0.3 * (max(y) - min(y)) # 仿水印效果 plt.text(c, d, '旅途中的宽', ha = 'center', fontsize = 30, rotation = -25, c = 'gray', alpha = 0.4) plt.plot(x, y, label = '股票A收盘价', c = 'r', ls = '-.', marker = 'D', lw = 2) # plt.plot([5.09, 5.13, 5.16, 5.12, 5.09, 5.25, 5.16, 5.20, 5.25], label='股票B收盘价', c='g', ls=':', marker='H', lw=4) plt.xticks(x, [ '2022-03-27', '2022-03-28', '2022-03-29', '2022-03-30', '2022-03-31', '2022-04-01', '2022-04-04', '2022-04-05', '2022-04-06'], rotation = 45) plt.title('某股票收盘价时序图') plt.xlabel('日期') plt.ylabel('价格') plt.grid(True) plt.legend() # 标出每天的收盘价 for a, b in zip(x, y): plt.text(a, b + 0.01, '%.3f'% b, ha = 'center', va = 'bottom', fontsize = 9) # 添加注释 plt.annotate('最低价', (x[y.index(min(y))], min(y)), (x[y.index(min(y))] + 0.5, min(y)), xycoords = 'data', arrowprops = dict(facecolor = 'r', shrink = 0.1), c = 'r',fontsize = 15) plt.show()
The following is a different effect. The added annotation arrow width is 3, the head width of the arrow is 10, the length is 20, shortened by 0.05, and the arrow is green , the annotation font is red. The code example is as follows:
import matplotlib.pyplot as plt plt.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['axes.unicode_minus'] = False x = range(9) y = [5.12, 5.15, 5.13, 5.10, 5.2, 5.25, 5.19, 5.24, 5.31] c = 0.5 * (min(x) + max(x)) d = min(y) + 0.3 * (max(y)-min(y)) plt.plot(x, y, label = '股票A收盘价', c = 'k', ls = '-.', marker = 'D', lw = 2) plt.xticks(x, [ '2022-03-27', '2022-03-28', '2022-03-29', '2022-03-30', '2022-03-31', '2022-04-01', '2022-04-04', '2022-04-05', '2022-04-06'], rotation = 45) plt.title('某股票收盘价时序图') plt.xlabel('日期') plt.ylabel('价格') plt.grid(True) plt.legend() # 标出每天的收盘价 for a, b in zip(x, y): plt.text(a, b+0.01, '%.1f'%b, ha='center', va='bottom', fontsize=9) plt.text(c, d, '旅途中的宽', ha = 'center', fontsize = 50, rotation = -25, c = 'r') plt.annotate('最低价', (x[y.index(min(y))], min(y)), (x[y.index(min(y))] + 2, min(y)), xycoords = 'data', arrowprops = dict(width = 3, headwidth = 10, headlength = 20, facecolor = 'g', shrink = 0.05), c = 'r',fontsize = 20) plt.show()
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