python - Seaborn countplot 为 x 值设置图例

Question

我正在通过 sns.countplot()

绘制分类数据和值计数

我正在尝试将 x 值的图例添加到图中，如下所示:handles 是 x 值的集合，labels 是 x 值的描述。

ax = sns.countplot(x = df.GARAGE_DOM)
handles, labels = ax.get_legend_handles_labels()

handles = ["VP", "BC", "GC", "GP", "JC", "PO"]
labels = ["Voie Publique", "box", "Garage couvert", "garage particulier clos", "Jardin clos", "parking ouvert"]
by_label = OrderedDict(zip(handles,labels))
ax.legend(by_label.keys(), by_label.values())

但是，我得到警告

UserWarning:

Legend does not support 'VP' instances.A proxy artist may be used instead.See: http://matplotlib.org/users/legend_guide.html#using-proxy-artist

我已经阅读了代理艺术家的文档，但我没有在我的案例中找到示例。

感谢您的帮助。

Answer 1

这是一个可能的解决方案，创建一个文本字段作为图例处理程序。下面将创建一个 TextHandler 用于创建图例艺术家，这是一个简单的 matplotlib.text.Text 实例。图例的句柄以 (text, color) 的元组形式给出，TextHandler 从中创建所需的 Text。

import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.legend_handler import HandlerBase
from matplotlib.text import Text
import numpy as np
import pandas as pd

class TextHandler(HandlerBase):
    def create_artists(self, legend, tup ,xdescent, ydescent,
                        width, height, fontsize,trans):
        tx = Text(width/2.,height/2,tup[0], fontsize=fontsize,
                  ha="center", va="center", color=tup[1], fontweight="bold")
        return [tx]


a = np.random.choice(["VP", "BC", "GC", "GP", "JC", "PO"], size=100, 
                     p=np.arange(1,7)/21. )
df = pd.DataFrame(a, columns=["GARAGE_DOM"])

ax = sns.countplot(x = df.GARAGE_DOM)


handltext = ["VP", "BC", "GC", "GP", "JC", "PO"]
labels = ["Voie Publique", "box", "Garage couvert", "garage particulier clos", "Jardin clos", "parking ouvert"]


t = ax.get_xticklabels()
labeldic = dict(zip(handltext, labels))
labels = [labeldic[h.get_text()]  for h in t]
handles = [(h.get_text(),c.get_fc()) for h,c in zip(t,ax.patches)]

ax.legend(handles, labels, handler_map={tuple : TextHandler()}) 

plt.show()

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上面的解决方案是下面原始版本的更新版本，看起来更复杂。以下是原始解决方案，它使用 TextArea 和 AnchoredOffsetbox 将文本放置在图例中。

import seaborn.apionly as sns
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from matplotlib.offsetbox import TextArea, AnchoredOffsetbox
from matplotlib.transforms import TransformedBbox, Bbox
from matplotlib.legend_handler import HandlerBase
import numpy as np
import pandas as pd

class TextHandler(HandlerBase):
    def __init__(self, text, color="k"):
        self.text = text 
        self.color = color
        super(TextHandler, self).__init__()

    def create_artists(self, legend, orig_handle,xdescent, ydescent,
                        width, height, fontsize,trans):
        bb = Bbox.from_bounds(xdescent,ydescent, width,height)
        tbb = TransformedBbox(bb, trans)
        textbox = TextArea(self.text, textprops={"weight":"bold","color":self.color})
        ab = AnchoredOffsetbox(loc=10,child=textbox, bbox_to_anchor=tbb, frameon=False)
        return [ab]


a = np.random.choice(["VP", "BC", "GC", "GP", "JC", "PO"], size=100, 
                     p=np.arange(1,7)/21. )
df = pd.DataFrame(a, columns=["GARAGE_DOM"])

ax = sns.countplot(x = df.GARAGE_DOM)


handltext = ["VP", "BC", "GC", "GP", "JC", "PO"]
labels = ["Voie Publique", "box", "Garage couvert", "garage particulier clos", "Jardin clos", "parking ouvert"]

handles = [ patches.Rectangle((0,0),1,1) for h in handltext]
t = ax.get_xticklabels()
labeldic = dict(zip(handltext, labels))
labels = [labeldic[h.get_text()]  for h in t]
handlers = [TextHandler(h.get_text(),c.get_fc()) for h,c in zip(t,ax.patches)]
handlermap = dict(zip(handles, handlers))
ax.legend(handles, labels, handler_map=handlermap,) 

plt.show()

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另见 this more generic answer