英文:
Second axis for Pandas boxplots
问题
我有一个类似这样的并列箱线图
second_axis = {0: 'a', 1: 'b', 2: 'c'}
import pandas as pd
import numpy as np
group = np.array([np.random.binomial(2, 0.4) for _ in range(100)])
data = [np.random.uniform(0, 5) for _ in range(len(group))]
df = pd.DataFrame({'data': data, 'group': group})
df.boxplot(by='group', vert=False)
我尝试在图上添加第二个垂直轴，我的期望输出是这样的：
[![在这里输入图片描述][1]][1]
我想知道是否有办法在pandas/matplotlib中实现这个效果。
[1]: https://i.stack.imgur.com/XEpbX.png
英文:
I have a side-by-side boxplot like this
second_axis = {0:'a',1: 'b', 2: 'c'}
import pandas as pd
import numpy as np
group = np.array([ np.random.binomial(2,0.4) for _ in range(100)])
data = [ np.random.uniform(0,5) for _ in range(len(group))]
df = pd.DataFrame({'data': data, 'group': group} )
df.boxplot(by='group', vert=False)
I am trying to add the 2nd vertical axis to the plot, my desired output is something like this:
I wonder whether there is a way to do this with pandas/matplotlib
答案1
得分: 2
你可以使用恒等变换创建一个 secondary_yaxis（不要与创建新的独立 y 轴的 twinx() 混淆，后者要复杂得多）。请注意，内部的箱线图是从 1 开始编号的。
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
group = np.array([np.random.binomial(2, 0.4) for _ in range(100)])
data = [np.random.uniform(0, 5) for _ in range(len(group))]
df = pd.DataFrame({'data': data, 'group': group})
ax = df.boxplot(by='group', vert=False)
sec_ax = ax.secondary_yaxis('right')
second_axis = {0: 'a', 1: 'b', 2: 'c'}
sec_ax.set_yticks(range(1, 1 + len(second_axis)), second_axis.values())
plt.tight_layout()
plt.show()
PS: 如果组是非连续的数字，你可以使用：
sec_ax.set_yticks(ax.get_yticks(), [second_axis[int(label.get_text())] for label in ax.get_yticklabels()])
或者当它们是字符串时：
sec_ax.set_yticks(ax.get_yticks(), [second_axis[label.get_text()] for label in ax.get_yticklabels()])
英文:
You can create a secondary_yaxis with the identity transformation (not to be confused with twinx() which creates a new independent y-axis and is much trickier). Note that internally, the boxplots are numbered starting from 1.
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
group = np.array([np.random.binomial(2, 0.4) for _ in range(100)])
data = [np.random.uniform(0, 5) for _ in range(len(group))]
df = pd.DataFrame({'data': data, 'group': group})
ax = df.boxplot(by='group', vert=False)
sec_ax = ax.secondary_yaxis('right')
second_axis = {0: 'a', 1: 'b', 2: 'c'}
sec_ax.set_yticks(range(1, 1 + len(second_axis)), second_axis.values())
plt.tight_layout()
plt.show()
PS: If the groups are non-successive numbers, you can use:
sec_ax.set_yticks(ax.get_yticks(), [second_axis[int(label.get_text())] for label in ax.get_yticklabels()])
or when they are strings:
sec_ax.set_yticks(ax.get_yticks(), [second_axis[label.get_text()] for label in ax.get_yticklabels()])
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