python matplotlib画图
L-M-Y 人气:01.引入matpltlib库
matplotlib
是一种优秀的python
数据可视化第三方库
使用matpltlib
库画图时,先将它引入,加载里面的pyplot,并命名为plt,然后使用plot
函数画图
import matplotlib.pyplot as plt #plt是引入模块的别名
2.pyplot基础图标函数总结
3.plot函数画图语法规则
plot函数参数:plot([x],y,[format],**kwargs)
各类语法太多啦,偷几张MOOC的图放上来~
4.折线图
from matplotlib import pyplot as plt
#生成数据 #横坐标数据从2017到2022,第三个参数可控制步长,可写可不写 x = range(2017, 2022) #y对应纵坐标的值 y1 = [49, 48, 45, 52, 50] y2 = [60, 62, 61, 65, 63] #生成图形 plt.title("LMY and her mother's weight") plt.xlabel('year') plt.ylabel('kg') plt.plot(x, y1, color='green', label='LMY') plt.plot(x, y2, color='purple', label='mother') plt.grid(alpha=0.5) plt.legend(loc='upper right') #显示图形 plt.show()
4.散点图
from matplotlib import pyplot as plt import numpy as np # 生成数据 # 横坐标数据从2017到2022,第三个参数可控制步长,可写可不写 x = range(2017, 2022) # y对应纵坐标的值 y1 = [49, 48, 45, 52, 50] y2 = [60, 62, 61, 65, 63] # 生成图形 plt.title("LMY and her mother's weight") plt.xlabel('year') plt.ylabel('kg') # 点的大小 area = np.pi*4**2 plt.scatter(x, y1, s=area, c='yellow', alpha=1) plt.scatter(x, y2, s=area, c='blue', alpha=1) plt.legend() plt.yticks(()) plt.show()
5.直方图
from matplotlib import pyplot as plt import numpy as np # 生成数据 # 横坐标数据从2017到2022,第三个参数可控制步长,可写可不写 x = [2017, 2018, 2019, 2020, 2021] # y对应纵坐标的值 y1 = [49, 48, 45, 52, 50] y2 = [60, 62, 61, 65, 63] # 生成图形 plt.title("LMY and her mother's weight") plt.ylabel('frequency') plt.xlabel('kg') # 点的大小 plt.hist(y1, bottom=None, color='purple') plt.hist(y2, bottom=None, color='pink') plt.show() # n, bins, patches = plt.hist(arr, bins=50, normed=1, facecolor='green', alpha=0.75) ''' arr:需要计算直方图的一维数组 bins:直方图的柱数,可选项,默认为10 normed:是否将得到的直方图向量归一化,默认为0 facecolor:直方图颜色 alpha:透明度 '''
6.条形图
纵向
from matplotlib import pyplot as plt import numpy as np arr = np.arange(2017, 2022) x = [49, 48, 45, 52, 50] # x轴 y = [2017, 2018, 2019, 2020, 2021] rect = plt.bar(arr, x, width=0.5) plt.title('LMY') plt.xlabel('weight') plt.ylabel('year') plt.legend() plt.show()
横向
多条
from matplotlib import pyplot as plt import numpy as np arr = np.arange(2017, 2022) x1 = [49, 48, 45, 52, 50] # x轴 x2 = [60, 62, 61, 65, 63] y = [2017, 2018, 2019, 2020, 2021] rects1 = plt.bar(arr, x1, 0.5, color='purple', label='LMY') rects2 = plt.bar(arr, x2, 0.5, color='yellow', label='Mother', alpha=0.3) plt.title("LMY and her mother's weight") plt.xlabel('weight') plt.ylabel('year') plt.legend() plt.show()
7.饼图
from matplotlib import patches, pyplot as plt import numpy as np label_list = ['49', '48', '45', '52', '50'] size = [20, 20, 20, 20, 20] # 各部分的颜色 color = ['red', 'pink', 'blue', 'green', 'purple'] explode = [0, 0, 0.15, 0, 0] patches, l_text, p_text = plt.pie(size, explode=explode, colors=color, labels=label_list, labeldistance=1.2, autopct="%1.2f%%", shadow=False, startangle=90, pctdistance=0.6) plt.axis('equal') plt.title("LMY's weight") plt.legend(loc='upper left') plt.show()
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