如何从 matplotlib/seaborn 图中删除或隐藏 y 轴刻度标签 [英] How to remove or hide y-axis ticklabels from a matplotlib / seaborn plot

问题描述

我画了一个像这样的情节

我想关闭沿 y 轴的刻度标签.要做到这一点，我正在使用

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

现在剧情是这样的.即使标签关闭，比例 1e67 仍然存在.

关闭比例1e67会使情节看起来更好.我该怎么做?

解决方案

• seaborn 用于绘制绘图，但它只是 matplotlib 的高级 API.
  • 用于移除 y 轴标签和刻度的函数是 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()，这将不起作用，但您可以使用 .set(title='')
• .set(ylabel=None) 应该删除轴标签.
• .tick_params(left=False) 将删除刻度.
• 同样，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=[]) # 删除刻度标签g1.set(title='Exercise: Pulse by Time for Exercise Type') # 添加标题g1.set(ylabel=None) # 移除轴标签g2 = sns.boxplot(x='物种'，y='body_mass_g'，hue='sex'，数据=笔，ax=ax[1])g2.set(yticklabels=[])g2.set(title='企鹅:按性别分类的体重')g2.set(ylabel=None) # 去除y轴标签g2.tick_params(left=False) # 删除刻度plt.tight_layout()plt.show()

  示例 2

  将 numpy 导入为 np导入 matplotlib.pyplot 作为 plt将熊猫导入为 pd# 正弦样本数据sample_length = range(1, 1+1) # 频率列数rads = np.arange(0, 2*np.pi, 0.01)数据 = 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(就地=真)# 阴谋图, ax = plt.subplots(figsize=(8, 8))ax.plot('弧度', '频率: 1x', 数据=df)

  删除标签

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

  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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