如何从matplotlib/seaborn图中删除或隐藏y轴刻度标签

问题描述

我做了一个看起来像这样的情节

我想关闭沿y轴的刻度标签.为此，我正在使用

  plt.tick_params(labelleft = False，left = False) 

现在情节看起来像这样.即使关闭了标签，刻度尺 1e67 仍然保留.

关闭比例尺 1e67 将使绘图看起来更好.我该怎么办?

解决方案

• seaborn 用于绘制图，但这只是 matplotlib 的高级API.
  • 为删除y轴标签和刻度线而调用的函数是 matplotlib 方法.
• 创建绘图后，使用 .set().
• .set(yticklabels = [])应该删除刻度标签.
  • 如果您使用 .set_title()，则此方法无效，但是您可以使用 .set(title ='')
• .set(ylabel = None)应该删除轴标签.
• .tick_params(left = False)将删除刻度线.
• 类似地，对于x轴:

  删除标签

    fig，ax = plt.subplots(2，1，figsize =(8，8))g1 = sns.boxplot(x ='time'，y ='pulse'，hue ='kind'，data = exercise，ax = ax [0])g1.set(yticklabels = [])#删除刻度线标签g1.set(title ='锻炼:按锻炼类型的时间脉动')#添加标题g1.set(ylabel = None)#删除轴标签g2 = sns.boxplot(x ='species'，y ='body_mass_g'，hue ='sex'，data = pen，ax = ax [1])g2.set(yticklabels = [])g2.set(title ='企鹅:按性别分类的体重')g2.set(ylabel = None)#移除y轴标签g2.tick_params(left = False)#删除刻度线plt.tight_layout()plt.show() 

  示例2

   将numpy导入为np导入matplotlib.pyplot作为plt将熊猫作为pd导入#正弦采样数据sample_length = range(1，1 + 1)#频率的列数rads = np.arange(0，2 * np.pi，0.01)数据= np.array([(sample_length中的t为((np.cos(t * rads)* 10 ** 67)+ 3 * 10 ** 67])df = pd.DataFrame(data.T，index = pd.Series(rads.tolist()，name ='radians')，column = [f'freq:{i} x'for sample_length中的i])df.reset_index(inplace = True)# 阴谋无花果，ax = plt.subplots(figsize =(8，8))ax.plot('弧度'，'频率:1x'，数据= df) 

  删除标签

   #图无花果，ax = plt.subplots(figsize =(8，8))ax.plot('弧度'，'频率:1x'，数据= df)ax.set(yticklabels = [])#删除刻度线标签ax.tick_params(left = False)#删除刻度线 

  I made a plot that looks like this

  I want to turn off the ticklabels along the y axis. And to do that I am using

  plt.tick_params(labelleft=False, left=False)
  

  And now the plot looks like this. Even though the labels are turned off the scale 1e67 still remains.

  Turning off the scale 1e67 would make the plot look better. How do I do that?

  解决方案
  • seaborn is used to draw the plot, but it's just a high-level API for matplotlib.
    • The functions called to remove the y-axis labels and ticks are matplotlib methods.
  • After creating the plot, use .set().
  • .set(yticklabels=[]) should remove tick labels.
    • This doesn't work if you use .set_title(), but you can use .set(title='')
  • .set(ylabel=None) should remove the axis label.
  • .tick_params(left=False) will remove the ticks.
  • Similarly, for the x-axis: How to remove or hide x-axis labels from a seaborn / matplotlib plot?

  Example 1

  import seaborn as sns
  import matplotlib.pyplot as plt
  
  # load data
  exercise = sns.load_dataset('exercise')
  pen = sns.load_dataset('penguins')
  
  # create figures
  fig, ax = plt.subplots(2, 1, figsize=(8, 8))
  
  # plot data
  g1 = sns.boxplot(x='time', y='pulse', hue='kind', data=exercise, ax=ax[0])
  
  g2 = sns.boxplot(x='species', y='body_mass_g', hue='sex', data=pen, ax=ax[1])
  
  plt.show()
  

  Remove Labels

  fig, ax = plt.subplots(2, 1, figsize=(8, 8))
  
  g1 = sns.boxplot(x='time', y='pulse', hue='kind', data=exercise, ax=ax[0])
  
  g1.set(yticklabels=[])  # remove the tick labels
  g1.set(title='Exercise: Pulse by Time for Exercise Type')  # add a title
  g1.set(ylabel=None)  # remove the axis label
  
  g2 = sns.boxplot(x='species', y='body_mass_g', hue='sex', data=pen, ax=ax[1])
  
  g2.set(yticklabels=[])
  g2.set(title='Penguins: Body Mass by Species for Gender')
  g2.set(ylabel=None)  # remove the y-axis label
  g2.tick_params(left=False)  # remove the ticks
  
  plt.tight_layout()
  plt.show()
  

  Example 2

  import numpy as np
  import matplotlib.pyplot as plt
  import pandas as pd
  
  # sinusoidal sample data
  sample_length = range(1, 1+1) # number of columns of frequencies
  rads = np.arange(0, 2*np.pi, 0.01)
  data = np.array([(np.cos(t*rads)*10**67) + 3*10**67 for t in sample_length])
  df = pd.DataFrame(data.T, index=pd.Series(rads.tolist(), name='radians'), columns=[f'freq: {i}x' for i in sample_length])
  df.reset_index(inplace=True)
  
  # plot
  fig, ax = plt.subplots(figsize=(8, 8))
  ax.plot('radians', 'freq: 1x', data=df)
  

  Remove Labels

  # plot
  fig, ax = plt.subplots(figsize=(8, 8))
  ax.plot('radians', 'freq: 1x', data=df)
  ax.set(yticklabels=[])  # remove the tick labels
  ax.tick_params(left=False)  # remove the ticks
  

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