如何在 seaborn relplot 中更改标题中的标记大小

Question

以下是工作代码。 我想对以下代码进行一些更改，但我不知道该怎么做。

1) 标题中的标记尺寸太小。 我希望图例中的标记大小增加（我尝试了 legend.markersize 没有显示任何效果）。 2）其次，我想画一条回归线。 我尝试了最后给出的代码，但缩小了图形，所以我想要带有回归线的原始图形，并用回归线的参数标记。

from matplotlib import pyplot as plt
import pandas as pd
import seaborn as sns
import numpy as np

d = {'x-axis':[71,35,61,253,145,157,218,241,291,277,159,167,171,188,240,254,258,269,277,288,298,347,349,353,360,380,441,443,506,528,530,537,538,566,600,762,815,889],
        'y-axis': [5,5,15,79,75,641,172,867,289,67,75,112,46,150,70,70,897,391,671,54,353,275,191,189,432,526,591,516,507,838,874,934,934,1086,698,913,1717,1482],
        'text':['p1','p2','p3','p4','p5','p6','p7','p8','p9','p10','p11','p12','p13','p14','p15','p16','p17','p18','p19','p20','p21','p22','p23','p24','p25','p26','p27','p28','p29','p30','p31','p32','p33','p34','p35','p36','p37','p38'],
        'size':[4,4,3,54,22,162,3,44,9,0,22,4,12,67,32,32,46,6,159,17,13,3,4,3,11,79,15,12,5,19,22,20,20,34,18,27,50,35],'hue':['good','bad','average','poor','good','bad','average','poor','good','bad','average','poor','poor','poor','poor','poor','poor','poor','poor','good','bad','good','bad','good','bad','good','bad','good','bad','good','bad','average','average','average','average','average','average','average']}
df = pd.DataFrame(d)
with sns.plotting_context(rc={"legend.fontsize":25,"legend.markersize":18,"axes.titlesize":20,"font.weight":'heavy',"legend.labelspacing":20}):
  p1 = sns.relplot(x='x-axis', y='y-axis',hue='hue',size='size',sizes=(300,1450),data=df,height=10, aspect=2 )
ax = p1.axes[0,0]
for idx,row in df.iterrows():
    x = row[0]
    y = row[1]
    text = row[2]
    ax.text(x+.05,y,text, horizontalalignment='left')
p1.set(xticks=[i for i in range(0, max(df['x-axis']) + 50, 50)],
       yticks=[i for i in range(0, max(df['y-axis']) + 500, 500)])

plt.show()

我用来绘制回归线的这段代码。

b, a = np.polyfit(df['x-axis'], df['y-axis'], 1)
xtest = np.linspace(df['x-axis'].min(),df['x-axis'].max(),10)
ax.plot(xtest, a + b* xtest, '--')

Answer 1

from matplotlib import pyplot as plt
import pandas as pd
import seaborn as sns
import numpy as np
import scipy.stats as st


d = {'x-axis':[71,35,61,253,145,157,218,241,291,277,159,167,171,188,240,254,258,269,277,288,298,347,349,353,360,380,441,443,506,528,530,537,538,566,600,762,815,889],
    'y-axis': [5,5,15,79,75,641,172,867,289,67,75,112,46,150,70,70,897,391,671,54,353,275,191,189,432,526,591,516,507,838,874,934,934,1086,698,913,1717,1482],
    'text':['p1','p2','p3','p4','p5','p6','p7','p8','p9','p10','p11','p12','p13','p14','p15','p16','p17','p18','p19','p20','p21','p22','p23','p24','p25','p26','p27','p28','p29','p30','p31','p32','p33','p34','p35','p36','p37','p38'],
    'size':[4,4,3,54,22,162,3,44,9,0,22,4,12,67,32,32,46,6,159,17,13,3,4,3,11,79,15,12,5,19,22,20,20,34,18,27,50,35],'hue':['good','bad','average','poor','good','bad','average','poor','good','bad','average','poor','poor','poor','poor','poor','poor','poor','poor','good','bad','good','bad','good','bad','good','bad','good','bad','good','bad','average','average','average','average','average','average','average']}

df = pd.DataFrame(d)

p1 = sns.relplot(x='x-axis', y='y-axis',hue='hue',size='size',sizes=(300,1450),data=df,height=10, aspect=2 )
p1._legend.remove()
ax = p1.axes[0,0]
for idx,row in df.iterrows():
    x = row[0]
    y = row[1]
    text = row[2]
    ax.text(x+.05,y,text, horizontalalignment='left')
p1.set(xticks=[i for i in range(0, max(df['x-axis']) + 50, 50)],
       yticks=[i for i in range(0, max(df['y-axis']) + 500, 500)])

#Regression part

slope, intercept, r_value, p_value, std_err = st.linregress(df['x-axis'],df['y-axis'])
line_df = pd.DataFrame()
line_df['line'] = slope*df['x-axis']+intercept
p,= plt.plot(df['x-axis'], line_df['line'],label='({:.2f})x+({:.2f})'.format(slope,intercept))

# adding legends for seaborn relplot
lgnd = plt.legend(loc="lower right", numpoints=1, fontsize=20)
for i in range(2,6):
    lgnd.legendHandles[i]._sizes = [300]  # you can change this for suitable size

plt.show()

我只是稍微修改了您的代码，我希望这应该可以完成工作。