python - 如何插入统计注释(星号或 p 值)

Question

这似乎是一个微不足道的问题，但我已经搜索了一段时间，似乎找不到答案。它似乎也应该成为这些软件包的标准部分。有谁知道是否有一种标准方法可以在seaborn中的分布图之间包含统计注释？

例如，在两个方框图或群图之间？

Answer 1

大括号/括号可以直接用 matplotlib.pyplot.plot 绘制或matplotlib.axes.Axes.plot ，并且可以使用 matplotlib.pyplot.text 添加注释或matplotlib.axes.Axes.text .

seaborn 分类图的索引为 0，而默认情况下，matplotlib 和 pandas 的箱线图从 range( 1, N+1)，可以通过positions参数进行调整。

seaborn 是 matplotlib 的高级 API，pandas.DataFrame.plot 使用 matplotlib 作为默认后端。

导入和 DataFrame

import seaborn as sns
import matplotlib.pyplot as plt

# dataframe in long form for seaborn
tips = sns.load_dataset("tips")

# dataframe in wide form for plotting with pandas.DataFrame.plot
df = tips.pivot(columns='day', values='total_bill')

# data as a list of lists for plotting directly with matplotlib (no nan values allowed)
data = [df[c].dropna().tolist() for c in df.columns]

seaborn

sns.boxplot(x="day", y="total_bill", data=tips, palette="PRGn")

# statistical annotation
x1, x2 = 2, 3   # columns 'Sat' and 'Sun' (first column: 0, see plt.xticks())
y, h, col = tips['total_bill'].max() + 2, 2, 'k'

plt.plot([x1, x1, x2, x2], [y, y+h, y+h, y], lw=1.5, c=col)
plt.text((x1+x2)*.5, y+h, "ns", ha='center', va='bottom', color=col)

plt.show()

pandas.DataFrame.plot

ax = df.plot(kind='box', positions=range(len(df.columns)))

x1, x2 = 2, 3
y, h, col = df.max().max() + 2, 2, 'k'

ax.plot([x1, x1, x2, x2], [y, y+h, y+h, y], lw=1.5, c=col)
ax.text((x1+x2)*.5, y+h, "ns", ha='center', va='bottom', color=col)

matplotlib

plt.boxplot(data, positions=range(len(data)))

x1, x2 = 2, 3

y, h, col = max(map(max, data)) + 2, 2, 'k'

plt.plot([x1, x1, x2, x2], [y, y+h, y+h, y], lw=1.5, c=col)
plt.text((x1+x2)*.5, y+h, "ns", ha='center', va='bottom', color=col)

<小时/>

tips.head()

   total_bill   tip     sex smoker  day    time  size
0       16.99  1.01  Female     No  Sun  Dinner     2
1       10.34  1.66    Male     No  Sun  Dinner     3
2       21.01  3.50    Male     No  Sun  Dinner     3
3       23.68  3.31    Male     No  Sun  Dinner     2
4       24.59  3.61  Female     No  Sun  Dinner     4

df.head()

day  Thur  Fri  Sat    Sun
0     NaN  NaN  NaN  16.99
1     NaN  NaN  NaN  10.34
2     NaN  NaN  NaN  21.01
3     NaN  NaN  NaN  23.68
4     NaN  NaN  NaN  24.59

数据

[[27.2, 22.76, 17.29, ..., 20.53, 16.47, 18.78],
 [28.97, 22.49, 5.75, ..., 13.42, 16.27, 10.09],
 [20.65, 17.92, 20.29, ..., 29.03, 27.18, 22.67, 17.82],
 [16.99, 10.34, 21.01, ..., 18.15, 23.1, 15.69]]