我有以下数据：

d_data = {"Name":["Jean","Luis",   "Ana", "Ana",  "Jean",  "Luis","Ana",    "Ana",  "Luis","Ana","Luis" ],
          "Money":[100,   2220,       333,   3342,  4423,  43,   5454,     4455,    421,   996,3102],
          "Type":["Cash","Cash","Cash","Cash","Digital","Cash","Digital","Cash","Cash","Digital","Digital"]}

为此我想为每个人的钱类型制作一个条形图。为此，我正在使用此代码：

df= pd.DataFrame(d_data)
df.groupby(["Name","Type"]).sum().unstack().plot(kind='bar', stacked=True) 

产生以下：

从这个图中我想删除图例中的双重标签：“无”和只保留资金类型：“数字”和“现金”

这是解决问题的一种方法。ax.get_legend_handles_labels()返回轴对象的图例句柄和标签。如果打印labels，将看到None, Type未打印。

解决办法：

现在，可以剥离标签以仅获取“现金”和“数字”，并使用列表理解来存储它们labels_new。

因此，当再次使用时设置图例时plt.legend(handles, labels_new)，只能获得所需的图例。可能还有其他直接方式，但以下解决方案也有效。

fig, ax = plt.subplots()

d_data = {"Name":["Jean","Luis",   "Ana", "Ana",  "Jean",  "Luis","Ana",    "Ana",  "Luis","Ana","Luis" ],
          "Money":[100,   2220,       333,   3342,  4423,  43,   5454,     4455,    421,   996,3102],
          "Type":["Cash","Cash","Cash","Cash","Digital","Cash","Digital","Cash","Cash","Digital","Digital"]}

df= pd.DataFrame(d_data)
df.groupby(["Name","Type"]).sum().unstack().plot(kind='bar', stacked=True, ax=ax) 

handles, labels = ax.get_legend_handles_labels()
labels_new = [label.strip('()').split(',')[1] for label in labels]
plt.legend(handles, labels_new)