Seaborn FacetGrid PointPlot 标签数据点 [英] Seaborn FacetGrid PointPlot Label Data Points

问题描述

鉴于以下内容:

导入 seaborn 为 sns参加 = sns.load_dataset("注意")sns.set_style("whitegrid", {'axes.grid': False,'axes.edgecolor':'none'})g = sns.FacetGrid(出席, col="subject", col_wrap=5,大小=1.5，ylim=(0, 10))ax = g.map(sns.pointplot, "solutions", "score", scale=.7)

我想在每一行上标记单个数据点(用值标签代替点).在我仅通过 MatPlotLib 创建的另一个图中，这是这样完成的:

对于 i，enumerate(ind) 中的文本:a.annotate(str(y[i])[:-2], xy=(ind[i], y[i]),fontsize=6, color=c,bbox=dict(pad=.9,alpha=1, fc='white',color='none'),va='center', ha='center',weight='bold')

但是，由于没有定义 ind，我不确定这将如何工作.

解决方案

我也不知道 ind 是什么.但如果目的是用坐标注释点，您可以在映射到 FacetGrid 的函数中使用 ax.annotate ，如下所示:

将 matplotlib.pyplot 导入为 plt将 seaborn 作为 sns 导入参加 = sns.load_dataset("注意")sns.set_style("whitegrid", {'axes.grid': False,'axes.edgecolor':'none'})g = sns.FacetGrid(出席, col="subject", col_wrap=5,大小=1.5，ylim=(0, 10))def f(x,y, **kwargs):ax = sns.pointplot(x,y,**kwargs)ax.axhline(5, alpha=0.5, color='grey')对于范围内的 i(len(x)):ax.annotate(str(y.values[i]), xy=(x.values[i]-1, y.values[i]),fontsize=8,xytext = (0,10), textcoords="offset points",color=kwargs.get("color","k"),bbox=dict(pad=.9,alpha=0.2, fc='limegreen',color='none'),va='center', ha='center',weight='bold')g.map(f, "solutions", "score", scale=.7)plt.show()

可能，您需要在注释中使用 xy=(i, y.values[i])，具体取决于数据的样子.

请注意，这也回答了

Given the following:

import seaborn as sns
attend = sns.load_dataset("attention")
sns.set_style("whitegrid", {'axes.grid' : False,'axes.edgecolor':'none'})
g = sns.FacetGrid(attend, col="subject", col_wrap=5,
size=1.5, ylim=(0, 10))
ax = g.map(sns.pointplot, "solutions", "score", scale=.7)

I would like to label individual data points (put value labels in place of dots) on each line. In another plot that I created via MatPlotLib only, this was accomplished like this:

for i, text in enumerate(ind):
    a.annotate(str(y[i])[:-2], xy=(ind[i], y[i]),fontsize=6, color=c, 
                bbox=dict(pad=.9,alpha=1, fc='white',color='none'),va='center', ha='center',weight='bold')

However, since there is no ind defined, I'm not sure how this would work.

解决方案

I wouldn't know what ind is either. But if the aim is to annotate the points with their coordinates, you may use ax.annotate inside a function that is mapped to the FacetGrid as follows:

import matplotlib.pyplot as plt
import seaborn as sns

attend = sns.load_dataset("attention")
sns.set_style("whitegrid", {'axes.grid' : False,'axes.edgecolor':'none'})
g = sns.FacetGrid(attend, col="subject", col_wrap=5,
                  size=1.5, ylim=(0, 10))

def f(x,y, **kwargs):
    ax = sns.pointplot(x,y,**kwargs)
    ax.axhline(5, alpha=0.5, color='grey')
    for i in range(len(x)):
        ax.annotate(str(y.values[i]), xy=(x.values[i]-1, y.values[i]),fontsize=8,
                    xytext = (0,10), textcoords="offset points",
                color=kwargs.get("color","k"), 
                bbox=dict(pad=.9,alpha=0.2, fc='limegreen',color='none'),
                va='center', ha='center',weight='bold')

g.map(f, "solutions", "score", scale=.7)

plt.show()

Possibly, you need to use xy=(i, y.values[i]) in the annotation, depending on what the data looks like.

Note that this also answers your previous question by putting the axhline in that function as well.

If the aim is to replace the points by the annotations, use xytext = (0,0) or leave that argument out completely; then also keep bbox=dict(pad=.9,alpha=1, fc='w',color='none') and use markers="" in the function call:

import matplotlib.pyplot as plt
import seaborn as sns

attend = sns.load_dataset("attention")
sns.set_style("whitegrid", {'axes.grid' : False,'axes.edgecolor':'none'})
g = sns.FacetGrid(attend, col="subject", col_wrap=5,
                  size=1.5, ylim=(0, 10))

def f(x,y, **kwargs):
    ax = sns.pointplot(x,y,**kwargs)
    ax.axhline(5, alpha=0.5, color='grey')
    for i in range(len(x)):
        ax.annotate(str(y.values[i]), xy=(i, y.values[i]),fontsize=8,
                color=kwargs.get("color","k"), 
                bbox=dict(pad=.9,alpha=1, fc='w',color='none'),
                va='center', ha='center',weight='bold')

g.map(f, "solutions", "score", scale=.7, markers="")

plt.show()

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