matplotlib: boîtes à moustaches de groupe

Question

Est-il possible de grouper des boîtes à moustaches dans matplotlib?

Supposons que nous ayons trois groupes "A", "B" et "C" et que pour chacun d'entre eux, nous souhaitons créer une boîte à moustaches pour les "pommes" et les "oranges". Si un regroupement n'est pas possible directement, nous pouvons créer les six combinaisons et les placer linéairement côte à côte. Quel serait le moyen le plus simple de visualiser les regroupements? J'essaie d'éviter de définir les étiquettes de graduation sur quelque chose comme "pommes A +" car mon scénario implique des noms beaucoup plus longs que "A".

Molly · Accepted Answer

Pourquoi ne pas utiliser des couleurs pour différencier "pommes" et "oranges" et un espacement pour séparer "A", "B" et "C"?

Quelque chose comme ça:

from pylab import plot, show, savefig, xlim, figure, \ hold, ylim, legend, boxplot, setp, axes # function for setting the colors of the box plots pairs def setBoxColors(bp): setp(bp['boxes'][0], color='blue') setp(bp['caps'][0], color='blue') setp(bp['caps'][1], color='blue') setp(bp['whiskers'][0], color='blue') setp(bp['whiskers'][1], color='blue') setp(bp['fliers'][0], color='blue') setp(bp['fliers'][1], color='blue') setp(bp['medians'][0], color='blue') setp(bp['boxes'][1], color='red') setp(bp['caps'][2], color='red') setp(bp['caps'][3], color='red') setp(bp['whiskers'][2], color='red') setp(bp['whiskers'][3], color='red') setp(bp['fliers'][2], color='red') setp(bp['fliers'][3], color='red') setp(bp['medians'][1], color='red') # Some fake data to plot A= [[1, 2, 5,], [7, 2]] B = [[5, 7, 2, 2, 5], [7, 2, 5]] C = [[3,2,5,7], [6, 7, 3]] fig = figure() ax = axes() hold(True) # first boxplot pair bp = boxplot(A, positions = [1, 2], widths = 0.6) setBoxColors(bp) # second boxplot pair bp = boxplot(B, positions = [4, 5], widths = 0.6) setBoxColors(bp) # thrid boxplot pair bp = boxplot(C, positions = [7, 8], widths = 0.6) setBoxColors(bp) # set axes limits and labels xlim(0,9) ylim(0,9) ax.set_xticklabels(['A', 'B', 'C']) ax.set_xticks([1.5, 4.5, 7.5]) # draw temporary red and blue lines and use them to create a legend hB, = plot([1,1],'b-') hR, = plot([1,1],'r-') legend((hB, hR),('Apples', 'Oranges')) hB.set_visible(False) hR.set_visible(False) savefig('boxcompare.png') show()

grouped box plot

jason · Answer

Voici ma version. Il stocke les données en fonction des catégories.

import matplotlib.pyplot as plt import numpy as np data_a = [[1,2,5], [5,7,2,2,5], [7,2,5]] data_b = [[6,4,2], [1,2,5,3,2], [2,3,5,1]] ticks = ['A', 'B', 'C'] def set_box_color(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['medians'], color=color) plt.figure() bpl = plt.boxplot(data_a, positions=np.array(xrange(len(data_a)))*2.0-0.4, sym='', widths=0.6) bpr = plt.boxplot(data_b, positions=np.array(xrange(len(data_b)))*2.0+0.4, sym='', widths=0.6) set_box_color(bpl, '#D7191C') # colors are from http://colorbrewer2.org/ set_box_color(bpr, '#2C7BB6') # draw temporary red and blue lines and use them to create a legend plt.plot([], c='#D7191C', label='Apples') plt.plot([], c='#2C7BB6', label='Oranges') plt.legend() plt.xticks(xrange(0, len(ticks) * 2, 2), ticks) plt.xlim(-2, len(ticks)*2) plt.ylim(0, 8) plt.tight_layout() plt.savefig('boxcompare.png')

Je manque de réputation alors je ne peux pas poster une image ici. Vous pouvez l'exécuter et voir le résultat. En gros, cela ressemble beaucoup à ce que Molly a fait.

Notez que, selon la version de python que vous utilisez, vous devrez peut-être remplacer xrange par range.

bmu · Answer

Un moyen simple serait d'utiliser pandas . J'ai adapté un exemple de la documentation de tracé :

In [1]: import pandas as pd, numpy as np In [2]: df = pd.DataFrame(np.random.Rand(12,2), columns=['Apples', 'Oranges'] ) In [3]: df['Categories'] = pd.Series(list('AAAABBBBCCCC')) In [4]: pd.options.display.mpl_style = 'default' In [5]: df.boxplot(by='Categories') Out[5]: array([<matplotlib.axes.AxesSubplot object at 0x51a5190>, <matplotlib.axes.AxesSubplot object at 0x53fddd0>], dtype=object)

pandas boxplot

jarry jafery · Answer

Données factices:

df = pd.DataFrame({'Group':['A','A','A','B','C','B','B','C','A','C'],\ 'Apple':np.random.Rand(10),'Orange':np.random.Rand(10)}) df = df[['Group','Apple','Orange']] Group Apple Orange 0 A 0.465636 0.537723 1 A 0.560537 0.727238 2 A 0.268154 0.648927 3 B 0.722644 0.115550 4 C 0.586346 0.042896 5 B 0.562881 0.369686 6 B 0.395236 0.672477 7 C 0.577949 0.358801 8 A 0.764069 0.642724 9 C 0.731076 0.302369

Vous pouvez utiliser la bibliothèque Seaborn pour ces parcelles. Tout d’abord, melt le cadre de données pour formater les données, puis créez la boîte à moustaches de votre choix.

import pandas as pd import matplotlib.pyplot as plt import seaborn as sns dd=pd.melt(df,id_vars=['Group'],value_vars=['Apple','Orange'],var_name='fruits') sns.boxplot(x='Group',y='value',data=dd,hue='fruits')

Juan Chacon · Answer

Juste pour ajouter à la conversation, j'ai trouvé un moyen plus élégant de changer la couleur du tracé de la boîte en itérant sur le dictionnaire de l'objet lui-même.

import numpy as np import matplotlib.pyplot as plt def color_box(bp, color): # Define the elements to color. You can also add medians, fliers and means elements = ['boxes','caps','whiskers'] # Iterate over each of the elements changing the color for elem in elements: [plt.setp(bp[elem][idx], color=color) for idx in xrange(len(bp[elem]))] return a = np.random.uniform(0,10,[100,5]) bp = plt.boxplot(a) color_box(bp, 'red')

À votre santé!

goats · Answer

Voici une fonction que j'ai écrite et qui prend le code de Molly et un autre code trouvé sur Internet pour créer des boîtes à moustaches groupées légèrement plus sophistiquées:

import numpy as np import matplotlib.pyplot as plt def custom_legend(colors, labels, linestyles=None): """ Creates a list of matplotlib Patch objects that can be passed to the legend(...) function to create a custom legend. :param colors: A list of colors, one for each entry in the legend. You can also include a linestyle, for example: 'k--' :param labels: A list of labels, one for each entry in the legend. """ if linestyles is not None: assert len(linestyles) == len(colors), "Length of linestyles must match length of colors." h = list() for k,(c,l) in enumerate(Zip(colors, labels)): clr = c ls = 'solid' if linestyles is not None: ls = linestyles[k] patch = patches.Patch(color=clr, label=l, linestyle=ls) h.append(patch) return h def grouped_boxplot(data, group_names=None, subgroup_names=None, ax=None, subgroup_colors=None, box_width=0.6, box_spacing=1.0): """ Draws a grouped boxplot. The data should be organized in a hierarchy, where there are multiple subgroups for each main group. :param data: A dictionary of length equal to the number of the groups. The key should be the group name, the value should be a list of arrays. The length of the list should be equal to the number of subgroups. :param group_names: (Optional) The group names, should be the same as data.keys(), but can be ordered. :param subgroup_names: (Optional) Names of the subgroups. :param subgroup_colors: A list specifying the plot color for each subgroup. :param ax: (Optional) The axis to plot on. """ if group_names is None: group_names = data.keys() if ax is None: ax = plt.gca() plt.sca(ax) nsubgroups = np.array([len(v) for v in data.values()]) assert len(np.unique(nsubgroups)) == 1, "Number of subgroups for each property differ!" nsubgroups = nsubgroups[0] if subgroup_colors is None: subgroup_colors = list() for k in range(nsubgroups): subgroup_colors.append(np.random.Rand(3)) else: assert len(subgroup_colors) == nsubgroups, "subgroup_colors length must match number of subgroups (%d)" % nsubgroups def _decorate_box(_bp, _d): plt.setp(_bp['boxes'], lw=0, color='k') plt.setp(_bp['whiskers'], lw=3.0, color='k') # fill in each box with a color assert len(_bp['boxes']) == nsubgroups for _k,_box in enumerate(_bp['boxes']): _boxX = list() _boxY = list() for _j in range(5): _boxX.append(_box.get_xdata()[_j]) _boxY.append(_box.get_ydata()[_j]) _boxCoords = Zip(_boxX, _boxY) _boxPolygon = plt.Polygon(_boxCoords, facecolor=subgroup_colors[_k]) ax.add_patch(_boxPolygon) # draw a black line for the median for _k,_med in enumerate(_bp['medians']): _medianX = list() _medianY = list() for _j in range(2): _medianX.append(_med.get_xdata()[_j]) _medianY.append(_med.get_ydata()[_j]) plt.plot(_medianX, _medianY, 'k', linewidth=3.0) # draw a black asterisk for the mean plt.plot([np.mean(_med.get_xdata())], [np.mean(_d[_k])], color='w', marker='*', markeredgecolor='k', markersize=12) cpos = 1 label_pos = list() for k in group_names: d = data[k] nsubgroups = len(d) pos = np.arange(nsubgroups) + cpos label_pos.append(pos.mean()) bp = plt.boxplot(d, positions=pos, widths=box_width) _decorate_box(bp, d) cpos += nsubgroups + box_spacing plt.xlim(0, cpos-1) plt.xticks(label_pos, group_names) if subgroup_names is not None: leg = custom_legend(subgroup_colors, subgroup_names) plt.legend(handles=leg)

Vous pouvez utiliser la ou les fonctions comme ceci:

data = { 'A':[np.random.randn(100), np.random.randn(100) + 5], 'B':[np.random.randn(100)+1, np.random.randn(100) + 9], 'C':[np.random.randn(100)-3, np.random.randn(100) -5] } grouped_boxplot(data, group_names=['A', 'B', 'C'], subgroup_names=['Apples', 'Oranges'], subgroup_colors=['#D02D2E', '#D67700']) plt.show()