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 我不知道该怎么做。

1) 标题中的标记太小。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()

这段代码我用来绘制回归线。

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()

我只是稍微修改了你的代码，我希望这应该可以工作。