Question

我正在尝试使用对数刻度作为我的seaborn jointplot的边距图。我正在使用set_xticks（）和set_yticks（），但我的更改没有出现。以下是我的代码和结果图：

import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
import seaborn as sns
import pandas as pd

tips = sns.load_dataset('tips')
female_waiters = tips[tips['sex']=='Female']

def graph_joint_histograms(df1):
    g=sns.jointplot(x = 'total_bill',y = 'tip', data = tips, space = 0.3,ratio = 3)
    g.ax_joint.cla()
    g.ax_marg_x.cla()
    g.ax_marg_y.cla()

    for xlabel_i in g.ax_marg_x.get_xticklabels():
        xlabel_i.set_visible(False)
    for ylabel_i in g.ax_marg_y.get_yticklabels():
        ylabel_i.set_visible(False)

    x_labels = g.ax_joint.get_xticklabels()
    x_labels[0].set_visible(False)
    x_labels[-1].set_visible(False)

    y_labels = g.ax_joint.get_yticklabels()
    y_labels[0].set_visible(False)
    y_labels[-1].set_visible(False)

    g.ax_joint.set_xlim(0,200)
    g.ax_marg_x.set_xlim(0,200)

    g.ax_joint.scatter(x = df1['total_bill'],y = df1['tip'],data = df1,c = 'y',edgecolors= '#080808',zorder = 2)
    g.ax_joint.scatter(x = tips['total_bill'],y = tips['tip'],data = tips, c= 'c',edgecolors= '#080808')

    ax1 =g.ax_marg_x.get_axes()
    ax2 = g.ax_marg_y.get_axes()
    ax1.set_yscale('log')
    ax2.set_xscale('log')

    ax1.set_yscale('log')
    ax2.set_xscale('log')

    ax2.set_xlim(1e0, 1e4)
    ax1.set_ylim(1e0, 1e3)
    ax2.xaxis.set_ticks([1e0,1e1,1e2,1e3])
    ax2.xaxis.set_ticklabels(("1","10","100","1000"), visible = True)


    plt.setp(ax2.get_xticklabels(), visible = True)
    colors = ['y','c']
    ax1.hist([df1['total_bill'],tips['total_bill']],bins = 10, stacked=True,log = True,color = colors, ec='black')

    ax2.hist([df1['tip'],tips['tip']],bins = 10,orientation = 'horizontal', stacked=True,log = True,color = colors, ec='black')
ax2.set_ylabel('')

非常感谢任何想法。

以下是结果图：

Answer 1

由于轴没有g.ax_marg_y.get_axes()方法，因此您应该从第get_axes()行获得错误。纠正

ax1 =g.ax_marg_x
ax2 = g.ax_marg_y

应该给你想要的情节。不幸的是，直方图的log=True参数覆盖了日志轴的勾选标签。因此，您可以将其保留（因为您已经将轴设置为记录比例）或者您需要在调用hist之后设置标签。

import matplotlib.pyplot as plt import seaborn as sns tips = sns.load_dataset('tips') def graph_joint_histograms(tips): g=sns.jointplot(x = 'total_bill',y = 'tip', data = tips, space = 0.3,ratio = 3) g.ax_joint.cla() g.ax_marg_x.cla() g.ax_marg_y.cla() for xlabel_i in g.ax_marg_x.get_xticklabels(): xlabel_i.set_visible(False) for ylabel_i in g.ax_marg_y.get_yticklabels(): ylabel_i.set_visible(False) x_labels = g.ax_joint.get_xticklabels() x_labels[0].set_visible(False) x_labels[-1].set_visible(False) y_labels = g.ax_joint.get_yticklabels() y_labels[0].set_visible(False) y_labels[-1].set_visible(False) g.ax_joint.set_xlim(0,200) g.ax_marg_x.set_xlim(0,200) g.ax_joint.scatter(x = tips['total_bill'],y = tips['tip'],data = tips, c = 'y',edgecolors= '#080808',zorder = 2) g.ax_joint.scatter(x = tips['total_bill'],y = tips['tip'],data = tips, c= 'c',edgecolors= '#080808') ax1 =g.ax_marg_x ax2 = g.ax_marg_y ax1.set_yscale('log') ax2.set_xscale('log') ax2.set_xlim(1e0, 1e4) ax1.set_ylim(1e0, 1e3) ax2.xaxis.set_ticks([1e0,1e1,1e2,1e3]) ax2.xaxis.set_ticklabels(("1","10","100","1000"), visible = True) plt.setp(ax2.get_xticklabels(), visible = True) colors = ['y','c'] ax1.hist([tips['total_bill'],tips['total_bill']],bins = 10, stacked=True, color = colors, ec='black') ax2.hist([tips['tip'],tips['tip']],bins = 10,orientation = 'horizontal', stacked=True, color = colors, ec='black') ax2.set_ylabel('') graph_joint_histograms(tips) plt.show()

如何手动更改Seaborn关节图上边距图的刻度标签

1 个答案: