python数据可视化学习-箱形图

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import numpy as np
import matplotlib.pyplot as plt
np.random.seed(100)
data = np.random.normal(size=1000,loc=0,scale=1)
plt.boxplot(data)
plt.show()

改变异常点的形状   ,sym='>'

import numpy as np
import matplotlib.pyplot as plt
np.random.seed(100)
data = np.random.normal(size=1000,loc=0,scale=1)
plt.boxplot(data,sym='>')
plt.show()

调整异常值的范围 whis = 1.5

import numpy as np
import matplotlib.pyplot as plt
np.random.seed(100)
data = np.random.normal(size=1000,loc=0,scale=1)
plt.boxplot(data,sym='>',whis= 0.6)
plt.show()

同时画出多个箱形图

import numpy as np
import matplotlib.pyplot as plt
np.random.seed(100)
data = np.random.normal(size=(1000,4),loc=0,scale=1)
labels = ['A','B','C','D']
plt.boxplot(data,labels = labels)
plt.show()