如何在 seaborn relplot 中更改標題中的標記大小

Question

以下是工作代碼。 我想對以下代碼進行一些更改，但我不知道該怎么做。

1) 標題中的標記尺寸太小。 我希望圖例中的標記大小增加（我嘗試了 legend.markersize 沒有顯示任何效果）。 2）其次，我想畫一條回歸線。 我嘗試了最后給出的代碼，但縮小了圖形，所以我想要帶有回歸線的原始圖形，並用回歸線的參數標記。

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()

我用來繪制回歸線的這段代碼。

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碼，我希望這應該可以完成工作。