多个条形图的单个图例 matplotlib

Question

我有一个使用 pandas Dataframe 中的不同列创建的多个条形图。

fig1 = plt.figure()
ypos = np.arange(len(dframe))

colorscheme = seaborn.color_palette(n_colors=4)

accuracyFig = fig1.add_subplot(221)
accuracyFig.bar(ypos,dframe['accuracy'], align = 'center', color=colorscheme)
accuracyFig.set_xticks([0,1,2,3])
accuracyFig.set_ylim([0.5,1])

sensitivityFig = fig1.add_subplot(222)
sensitivityFig.bar(ypos, dframe['sensitivity'], align = 'center',color=colorscheme )
sensitivityFig.set_xticks([0,1,2,3])
sensitivityFig.set_ylim([0.5,1])

specificityFig = fig1.add_subplot(223)
specificityFig.bar(ypos, dframe['specificity'], align = 'center', color=colorscheme)
specificityFig.set_xticks([0,1,2,3])
specificityFig.set_ylim([0.5,1])

precisionFig = fig1.add_subplot(224)
precisionFig.bar(ypos, dframe['precision'], align = 'center', color=colorscheme)
precisionFig.set_xticks([0,1,2,3])
precisionFig.set_ylim([0.5,1])

其中dframe 是具有整数值的熊猫数据框。这给我输出了下图。

每种颜色对应一个分类器模型 - perceptron,C2,C3 and C4，它们存储在熊猫dframe['name']中

现在我想为整个图形绘制一个图例。我尝试了以下

leg = plt.legend(dframe['name'])

关于如何绘制单个图例并将其放在图下方 2 列中的任何帮助。

但它给了我以下。

这是我的数据框

                     name        accuracy     sensitivity     specificity       precision
0              perceptron  0.820182164169  0.852518881235  0.755172413793  0.875007098643
1  DecisionTreeClassifier             1.0             1.0             1.0             1.0
2    ExtraTreesClassifier             1.0             1.0             1.0             1.0
3  RandomForestClassifier  0.999796774253  0.999889340748  0.999610678532  0.999806362379

Answer 1

首先，您的表格格式不整齐（请参阅此处：http://vita.had.co.nz/papers/tidy-data.pdf）。

让你的表格整齐（或长）格式具有巨大的优势，即使用 seaborn 绘图变得非常容易（以及其他优势）：

df # yours
                     name        accuracy     sensitivity     specificity       precision
0              perceptron  0.820182164169  0.852518881235  0.755172413793  0.875007098643
1  DecisionTreeClassifier             1.0             1.0             1.0             1.0
2    ExtraTreesClassifier             1.0             1.0             1.0             1.0
3  RandomForestClassifier  0.999796774253  0.999889340748  0.999610678532  0.999806362379

将其转换为长格式（或整齐）：

df2 = pd.melt(df, value_vars=["accuracy", "sensitivity", "specificity", "precision"], id_vars="name")
df2
                      name     variable     value
0               perceptron     accuracy  0.820182
1   DecisionTreeClassifier     accuracy  1.000000
2     ExtraTreesClassifier     accuracy  1.000000
3   RandomForestClassifier     accuracy  0.999797
4               perceptron  sensitivity  0.852519
5   DecisionTreeClassifier  sensitivity  1.000000
6     ExtraTreesClassifier  sensitivity  1.000000
7   RandomForestClassifier  sensitivity  0.999889
8               perceptron  specificity  0.755172
9   DecisionTreeClassifier  specificity  1.000000
10    ExtraTreesClassifier  specificity  1.000000
11  RandomForestClassifier  specificity  0.999611
12              perceptron    precision  0.875007
13  DecisionTreeClassifier    precision  1.000000
14    ExtraTreesClassifier    precision  1.000000
15  RandomForestClassifier    precision  0.999806

然后，只需在一行 + 2 行中绘制您想要的内容以使其更清晰：

g = sns.factorplot(data=df2,
                   kind="bar",
                   col="variable", # you have 1 plot per variable, forming 1 line and 4 columns (4 different variables)
                   x="name", # in each plot the x-axis will be the name
                   y="value", # the height of the bar
                   col_wrap=2) # you actually want your line of plots to contain 2 plots maximum 
g.set_xticklabels(rotation=90) # rotate the labels so they don't overlap
plt.tight_layout() # fit everything into the figure

HTH

Answer 2

您可以使用以下方法将图例移动到图表中需要的位置。

在绘制条形图时添加标签是必要的。我已经更改了您绘制图例的主线。

我添加了一些虚拟标签，在您的代码中，您可以通过 labels = list(df) 为您提供数据框中的列名列表来获取标签。

import matplotlib.pyplot as plt

colorscheme = ['r','b','c','y']
fig1 = plt.figure()
accuracyFig = fig1.add_subplot(221)
A =[1,2,3,4]
B = [4,3,2,1]
labels = ['perceptron','C2','C3','C4']
for i in range(0,len(A)):
    accuracyFig.bar(A[i],B[i], align = 'center',label = labels[i], color = colorscheme[i])

accuracyFig1 = fig1.add_subplot(223)
A =[1,2,3,4]
B = [4,3,2,1]
labels = ['perceptron','C2','C3','C4']
for i in range(0,len(A)):
    accuracyFig1.bar(A[i],B[i], align = 'center',label = labels[i], color = colorscheme[i])

accuracyFig2 = fig1.add_subplot(222)
A =[1,2,3,4]
B = [4,3,2,1]
labels = ['perceptron','C2','C3','C4']
for i in range(0,len(A)):
    accuracyFig2.bar(A[i],B[i], align = 'center',label = labels[i], color = colorscheme[i])

accuracyFig3 = fig1.add_subplot(224)
A =[1,2,3,4]
B = [4,3,2,1]
labels = ['perceptron','C2','C3','C4']
for i in range(0,len(A)):
    accuracyFig3.bar(A[i],B[i], align = 'center',label = labels[i], color = colorscheme[i])

# Plot the legend:
# You don't want to plot to any particular axis, instead to a general plot.

plt.legend(loc = 'lower center',bbox_to_anchor = (0,-0.3,1,1),
        bbox_transform = plt.gcf().transFigure)
plt.show()

图例来源：

How to create custom legend in matplotlib based on the value of the barplot? how do I make a single legend for many subplots with matplotlib? How to put the legend out of the plot

更新：意外删除了我的 cmets：在 legend() 中添加 ncol = 2 将提供您想要的对称拆分行为。

Answer 3

我将代码修改如下

fig1 = plt.figure()

A = list(range(1,len(dframe)+1))
labels = dframe['name'].tolist()

colorscheme = sns.color_palette(n_colors=len(dframe))


accuracyFig = fig1.add_subplot(221)
for i in range(0,len(A)):
    accuracyFig.bar(A[i],dframe['accuracy'][i+1], align = 'center',label = labels[i], color = colorscheme[i])
accuracyFig.set_xticks([])
accuracyFig.set_ylim([0.5,1])
accuracyFig.set_title('Accuracy')

sensitivityFig = fig1.add_subplot(222)
for i in range(0,len(A)):
    sensitivityFig.bar(A[i],dframe['sensitivity'][i+1], align = 'center',label = labels[i], color = colorscheme[i])
sensitivityFig.set_xticks([])
sensitivityFig.set_ylim([0.5,1])
sensitivityFig.set_title('Sensitivity')

specificityFig = fig1.add_subplot(223)
for i in range(0,len(A)):
    specificityFig.bar(A[i],dframe['specificity'][i+1], align = 'center',label = labels[i], color = colorscheme[i])
specificityFig.set_xticks([])
specificityFig.set_ylim([0.5,1])
specificityFig.set_title('Specificity')

precisionFig = fig1.add_subplot(224)
for i in range(0,len(A)):
    precisionFig.bar(A[i],dframe['precision'][i+1], align = 'center',label = labels[i], color = colorscheme[i])
precisionFig.set_xticks([])
precisionFig.set_ylim([0.5,1])
precisionFig.set_title('Precision')

# Plot the legend:

plt.legend(loc = 'lower center',bbox_to_anchor = (0,-0.05,1,2), ncol=2,
        bbox_transform = plt.gcf().transFigure)

plt.show()

我没有使用固定长度的标签，而是直接从数据框中复制它们并且它可以工作。

我做了一些更新并将参数（n_cols = 2）添加到图例函数中，这样我的输出图看起来像这样

感谢@Charles Morris 的帮助