Matplotlib Boxplot Doesn't Align With Overlaid Scatterplot
I have a plot where I'm trying to overlay a scatter series on a boxplot series... here is a simple example of the problem so that you can re-create it. import pandas as pd import n
Solution 1:
- Tested in
python 3.8.11
,pandas 1.3.2
,matplotlib 3.4.3
,seaborn 0.11.2
- Notice the
xticklabel
locations are misaligned. - As per
matplotlib.pyplot.boxplot
,position
defaults torange(1, N+1)
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(6, 8))
ax1.boxplot(df, labels=names)
print(ax1.get_xticks())
ax2.scatter(names, df.head(1))
print(ax2.get_xticks())
ax3.boxplot(df, labels=names)
ax3.scatter(names, df.head(1))
[out]:
[1 2 3 4 5 6]
[0, 1, 2, 3, 4, 5]
- A correct solution, given the existing code, is to set the
positions
parameter - This also requires converting the dataframe to long form with
pandas.DataFrame.melt
, for the scatterplot.
plt.boxplot(df, labels=names, positions=range(len(df.columns)))
plt.scatter(data=df.melt(), x='variable', y='value')
- Alternatively, plot directly with
pandas.DataFrame.plot
ax = df.plot(kind='box', positions=range(len(df.columns)))
df.melt().plot(kind='scatter', x='variable', y='value', ax=ax)
- The simplest solution is to use
seaborn
, which is a high-level API formatplotlib
. This plots the given dataframe directly, without any transformations- How can box plot be overlaid on top of swarm plot in Seaborn?
seaborn.boxplot
andseaborn.swarmplot
, which is a better option thanseaborn.scatterplot
.boxplot
positions begin at 0
import seaborn as sns
sns.boxplot(data=df, boxprops={'facecolor':'None'})
print(plt.xticks())
sns.swarmplot(data=df)
print(plt.xticks())
[out]:
(array([0, 1, 2, 3, 4, 5]), [Text(0, 0, 'a'), Text(1, 0, 'b'), Text(2, 0, 'c'), Text(3, 0, 'd'), Text(4, 0, 'e'), Text(5, 0, 'f')])
(array([0, 1, 2, 3, 4, 5]), [Text(0, 0, 'a'), Text(1, 0, 'b'), Text(2, 0, 'c'), Text(3, 0, 'd'), Text(4, 0, 'e'), Text(5, 0, 'f')])
Solution 2:
The shape of your data passed to scatter is incorrect, and the index needs to be shifted as boxplot indices start from 1.
Here is a working solution:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
names = ['a','b','c','d','e','f']
df = pd.DataFrame(np.random.rand(6,6), columns=names)
display(df)
plt.boxplot(df, labels=names)
plt.show()
df2 = df.copy()
df2.columns = range(1, len(df2.columns)+1)
df2 = df2.unstack().reset_index(level=0)
plt.scatter(*df2.values.T)
plt.show()
plt.boxplot(df, labels=names)
plt.scatter(*df2.values.T)
plt.show()
What needs to be fed to scatter
:
[1., 1., 1., 1., 1., 1., 2., 2., 2., 2., 2., 2., 3., 3., 3., 3., 3.,
3., 4., 4., 4., 4., 4., 4., 5., 5., 5., 5., 5., 5., 6., 6., 6., 6.,
6., 6.]
and
[0.40196123, 0.24802927, 0.3152357 , 0.76739054, 0.06847434,
0.30173798, 0.30350823, 0.36324843, 0.35928768, 0.69194326,
0.61586685, 0.74039024, 0.56971769, 0.37970524, 0.67049866,
0.82031296, 0.15917911, 0.58760412, 0.02660848, 0.67014213,
0.46027398, 0.39161172, 0.01191327, 0.48197714, 0.79882359,
0.84189102, 0.10873758, 0.56858526, 0.48169526, 0.08860958,
0.43500853, 0.26380151, 0.14911615, 0.47846386, 0.25583401,
0.04949216]
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