我可以根据“简单”字典在 matplotlib 中创建一个简单的柱状图：
import matplotlib.pyplot as plt
D = {u'Label1':26, u'Label2': 17, u'Label3':30}
plt.bar(range(len(D)), D.values(), align='center')
plt.xticks(range(len(D)), D.keys())
plt.show()
But, how do I create curved line on the text and numeric data of this dictionarie, I do not know?
Т_OLD = {'10': 'need1', '11': 'need2', '12': 'need1', '13': 'need2', '14': 'need1'}
Like the picture below
您可以使用 numpy 将字典转换为具有两列的数组，并且可以绘制该数组。
import matplotlib.pyplot as plt
import numpy as np
T_OLD = {'10' : 'need1', '11':'need2', '12':'need1', '13':'need2','14':'need1'}
x = list(zip(*T_OLD.items()))
# sort array, since dictionary is unsorted
x = np.array(x)[:,np.argsort(x[0])].T
# let second column be "True" if "need2", else be "False
x[:,1] = (x[:,1] == "need2").astype(int)
# plot the two columns of the array
plt.plot(x[:,0], x[:,1])
#set the labels accordinly
plt.gca().set_yticks([0,1])
plt.gca().set_yticklabels(['need1', 'need2'])
plt.show()
以下是一个版本，与词典的实际内容无关；唯一的假设是键可以转换为浮点数。
import matplotlib.pyplot as plt
import numpy as np
T_OLD = {'10': 'run', '11': 'tea', '12': 'mathematics', '13': 'run', '14' :'chemistry'}
x = np.array(list(zip(*T_OLD.items())))
u, ind = np.unique(x[1,:], return_inverse=True)
x[1,:] = ind
x = x.astype(float)[:,np.argsort(x[0])].T
# plot the two columns of the array
plt.plot(x[:,0], x[:,1])
#set the labels accordinly
plt.gca().set_yticks(range(len(u)))
plt.gca().set_yticklabels(u)
plt.show()