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= )
- Do not use
sns.boxplot(...).set(xticklabels=[]) because, while this works, the object type is changed from matplotlib.axes._axes.Axes for sns.boxplot(...), to list.
.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?
- Tested in
python 3.11, pandas 1.5.2, matplotlib 3.6.2, seaborn 0.12.1
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)
# or skip the previous two lines and plot df directly
# ax = df.plot(x= radians , y= freq: 1x , figsize=(8, 8), legend=False)
Remove Labels
# plot
fig, ax = plt.subplots(figsize=(8, 8))
ax.plot( radians , freq: 1x , data=df)
# or skip the previous two lines and plot df directly
# ax = df.plot(x= radians , y= freq: 1x , figsize=(8, 8), legend=False)
ax.set(yticklabels=[]) # remove the tick labels
ax.tick_params(left=False) # remove the ticks
