如何在 matplotlib 中绘制一个单词的两个或多个标签？

Question

我在用 1 到 5 的情绪绘制单词时遇到了问题

['dotcom', 13, 12, 17, 6, 13],

 ['graelam', 1, 2, 3, 2, 0],

 ['oprahin', 1, 0, 0, 0, 0],

 ['jeffi', 2, 2, 3, 7, 0],

 ['assuar', 1, 0, 0, 1, 0],

 ['ausio', 0, 0, 0, 1, 0],

 ['sweeeeet', 2, 1, 0, 5, 7],

 ['atual', 3, 5, 8, 4, 4],

 ['estraing', 0, 0, 0, 0, 1],

 ['affilait', 1, 0, 0, 0, 0],

 ['radioshark', 8, 4, 9, 4, 3],

 ['illuminati', 53, 45, 52, 37, 12],

 ['providedth', 0, 1, 1, 0, 0],

 ['recategor', 5, 0, 1, 0, 0],

 ['redondo', 2, 2, 0, 6, 2],

 ['dybl', 1, 0, 1, 2, 0],

 ['gebhardt', 0, 1, 1, 2, 2],

 ['isanyway', 0, 1, 0, 0, 0],

在每个列表中有单词并包含标签 [1,2,3,4,5] 的单词计数。我想绘制那些单词与不同标签的关系。我怎样才能做到这一点？谢谢你的主意

Answer 1

在我的解决方案中x-axis包含每个单词标签，并y-axis包含所属类别。代码如下所示：import numpy as npimport matplotlib.pyplot as pltpred = [['dotcom', 13, 12, 17, 6, 13], \       ['graelam', 1, 2, 3, 2, 0],\       ['oprahin', 1, 0, 0, 0, 0],\       ['jeffi', 2, 2, 3, 7, 0],\       ['assuar', 1, 0, 0, 1, 0],\       ['ausio', 0, 0, 0, 1, 0],\       ['sweeeeet', 2, 1, 0, 5, 7],\       ['atual', 3, 5, 8, 4, 4],\       ['estraing', 0, 0, 0, 0, 1],\       ['affilait', 1, 0, 0, 0, 0],\       ['radioshark', 8, 4, 9, 4, 3],\       ['illuminati', 53, 45, 52, 37, 12],\       ['providedth', 0, 1, 1, 0, 0],\       ['recategor', 5, 0, 1, 0, 0],\       ['redondo', 2, 2, 0, 6, 2],\       ['dybl', 1, 0, 1, 2, 0],\       ['gebhardt', 0, 1, 1, 2, 2],\       ['isanyway', 0, 1, 0, 0, 0]]pred = np.asarray(pred)predicted_val = pred[:,1:].astype(int)predicted_val = np.transpose(predicted_val)prediction_results = predword_list = pred[:,0].astype(str)word_list = word_list.tolist()classes = ['Class-0', 'Class-1', 'Class-2', 'Class-3', 'Class-4']fig, ax = plt.subplots()im = ax.imshow(predicted_val)# We want to show all ticks...ax.set_xticks(np.arange(len(word_list)))ax.set_yticks(np.arange(len(classes)))ax.set_xticklabels(word_list)ax.set_yticklabels(classes)# Rotate the tick labels and set their alignment.plt.setp(ax.get_xticklabels(), rotation=45, ha="right",         rotation_mode="anchor")# Loop over data dimensions and create text annotations.for i in range(len(classes)):    for j in range(len(word_list)):        text = ax.text(j, i, predicted_val[i, j],                       ha="center", va="center", color="w")#ax.set_title("")fig.tight_layout()cbar = ax.figure.colorbar(im, ax=ax)plt.show()绘制的图：