Boxplot：异常值标签Python [英] Boxplot : Outliers Labels Python

问题描述

我正在使用seaborn软件包制作时间序列箱线图，但无法在离群值上贴标签。

I'm making a time series boxplot using seaborn package but I can't put a label on my outliers.

我的数据是3列的dataFrame： [Month，Id，Value] ，我们可以像这样伪造：

My data is a dataFrame of 3 columns : [Month , Id , Value] that we can fake like that :

### Sample Data ###
Month = numpy.repeat(numpy.arange(1,11),10)
Id = numpy.arange(1,101)
Value = numpy.random.randn(100)

### As a pandas DataFrame ###
Ts = pandas.DataFrame({'Value' : Value,'Month':Month, 'Id': Id})

### Time series boxplot ###
ax = seaborn.boxplot(x="Month",y="Value",data=Ts)

我每个月都有一个箱线图，我试图将 Id 用作标签此处的三个异常值：

I have one boxplot for each month and I'm trying to put the Id as a label of the three outliers on the plot here:

推荐答案

首先，您需要检测数据框中哪些 Id 是异常值，可以使用

First of all, you need to detect which Id in your dataframe are outliers, you can use this:

outliers_df = pd.DataFrame(columns = ['Value', 'Month', 'Id'])
for month in Ts['Month'].unique():
        outliers = [y for stat in boxplot_stats(Ts[Ts['Month'] == month]['Value']) for y in stat['fliers']]
        if outliers != []:
                for outlier in outliers:
                        outliers_df = outliers_df.append(Ts[(Ts['Month'] == month) & (Ts['Value'] == outlier)])

创建一个类似于原始数据框的数据框，其中包含

然后您可以使用以下方法在情节上注释 Id ：

which creates a dataframe, similar to the original one, containing outliers only.
Then you can annotare Id on your plot with this:

for row in outliers_df.iterrows():
        ax.annotate(row[1]['Id'], xy=(row[1]['Month'] - 1, row[1]['Value']), xytext=(2,2), textcoords='offset points', fontsize=14)

完整代码：

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.cbook import boxplot_stats
sns.set_style('darkgrid')

Month = np.repeat(np.arange(1,11),10)
Id = np.arange(1,101)
Value = np.random.randn(100)

Ts = pd.DataFrame({'Value' : Value,'Month':Month, 'Id': Id})

fig, ax = plt.subplots()
sns.boxplot(ax=ax, x="Month",y="Value",data=Ts)

outliers_df = pd.DataFrame(columns = ['Value', 'Month', 'Id'])
for month in Ts['Month'].unique():
        outliers = [y for stat in boxplot_stats(Ts[Ts['Month'] == month]['Value']) for y in stat['fliers']]
        if outliers != []:
                for outlier in outliers:
                        outliers_df = outliers_df.append(Ts[(Ts['Month'] == month) & (Ts['Value'] == outlier)])

for row in outliers_df.iterrows():
        ax.annotate(row[1]['Id'], xy=(row[1]['Month'] - 1, row[1]['Value']), xytext=(2,2), textcoords='offset points', fontsize=14)

plt.show()

输出：

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