本文介绍了如何从matplotlib / seaborn图中删除或隐藏y轴刻度标签?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我制作了一个看起来像这样的情节
我想转身沿y轴剔除刻度标签。为此,我正在使用
plt.tick_params(labelleft = False,left = False)
现在情节看起来像这样。即使标签已关闭,刻度 1e67
仍然保留。
关闭比例尺 1e67
即可绘制看上去好些。我该怎么办?
解决方案
-
seaborn
用于绘制图,但这只是matplotlib
的高级API。
- 用来删除y轴标签和刻度的函数是
matplotlib
方法。
- 用来删除y轴标签和刻度的函数是
- 创建绘图后,使用
.set()
-
.set(yticklabels = [])
应该删除刻度标签。
- 如果使用
.set_title()
,则此方法不起作用,但可以使用.set(title ='')
- 如果使用
-
.set (ylabel = None)
应该删除轴标签。 -
.tick_params(left = False)
将 - 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])$ b
$ b g2.set(yticklabels = [])
g2.set(title ='企鹅:按性别划分的体重')
g2.set( ylabel = None)#删除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
import matplotlib .pyplot as plt
进口熊猫as pd
#正弦采样数据
sample_length = range(1,1 + 1)#频率列数
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'),column = [f'freq:{i} x'for i in sample_length])
df.reset_index(inplace = True)
#图
图,ax = plt.subplots(figsize =(8,8))
ax.plot('radians','freq:1x',data = df)
删除标签
#图
图,ax = plt.subplots(figsize =(8,8))
ax.plot('radians','freq:1x',data = 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 formatplotlib
.- The functions called to remove the y-axis labels and ticks are
matplotlib
methods.
- The functions called to remove the y-axis labels and ticks are
- 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='')
- This doesn't work if you use
.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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