5
votes

I'm ploting a categorical data and value count by sns.countplot()

I'm trying to add legend for x-values to the figure as following: handles is set of x-value, labels is the descriptions of x-values.

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())

However, I got warning that

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

I've read the doc of proxy artist but I didn't find examples in my case.

enter image description here

Thanks for your help.

1

1 Answers

5
votes

Here is a possible solution, creating a text field as a legend handler. The following would create a TextHandler to be used to create the legend artist, which is a simple matplotlib.text.Text instance. The handles for the legend are given as tuples of (text, color) from which the TextHandler creates the desired 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()

enter image description here


TextAreaAnchoredOffsetbox
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()

Also see this more generic answer