Python 实用宝典

Question 1

I tried the following code (test_seaborn.py):

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot')
import seaborn as sns
sns.set()
df = sns.load_dataset('iris')
sns_plot = sns.pairplot(df, hue='species', size=2.5)
fig = sns_plot.get_figure()
fig.savefig("output.png")
#sns.plt.show()

But I get this error:

  Traceback (most recent call last):
  File "test_searborn.py", line 11, in <module>
    fig = sns_plot.get_figure()
AttributeError: 'PairGrid' object has no attribute 'get_figure'

I expect the final output.png will exist and look like this:

How can I resolve the problem?

Question 2

Remove the get_figure and just use sns_plot.savefig('output.png')

df = sns.load_dataset('iris')
sns_plot = sns.pairplot(df, hue='species', size=2.5)
sns_plot.savefig("output.png")

Question 3

The suggested solutions are incompatible with Seaborn 0.8.1

giving the following errors because the Seaborn interface has changed:

AttributeError: 'AxesSubplot' object has no attribute 'fig'
When trying to access the figure

AttributeError: 'AxesSubplot' object has no attribute 'savefig'
when trying to use the savefig directly as a function

The following calls allow you to access the figure (Seaborn 0.8.1 compatible):

swarm_plot = sns.swarmplot(...)
fig = swarm_plot.get_figure()
fig.savefig(...)

as seen previously in this answer.

UPDATE: I have recently used PairGrid object from seaborn to generate a plot similar to the one in this example. In this case, since GridPlot is not a plot object like, for example, sns.swarmplot, it has no get_figure() function. It is possible to directly access the matplotlib figure by

fig = myGridPlotObject.fig

Like previously suggested in other posts in this thread.

Question 4

Some of the above solutions did not work for me. The .fig attribute was not found when I tried that and I was unable to use .savefig() directly. However, what did work was:

sns_plot.figure.savefig("output.png")

I am a newer Python user, so I do not know if this is due to an update. I wanted to mention it in case anybody else runs into the same issues as I did.

Question 5

You should just be able to use the savefig method of sns_plot directly.

sns_plot.savefig("output.png")

For clarity with your code if you did want to access the matplotlib figure that sns_plot resides in then you can get it directly with

fig = sns_plot.fig

In this case there is no get_figure method as your code assumes.

Question 6

I use distplot and get_figure to save picture successfully.

sns_hist = sns.distplot(df_train['SalePrice'])
fig = sns_hist.get_figure()
fig.savefig('hist.png')

Question 7

Fewer lines for 2019 searchers:

import matplotlib.pyplot as plt
import seaborn as sns

df = sns.load_dataset('iris')
sns_plot = sns.pairplot(df, hue='species', height=2.5)
plt.savefig('output.png')

UPDATE NOTE: size was changed to height.

Question 8

This works for me

import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline

sns.factorplot(x='holiday',data=data,kind='count',size=5,aspect=1)
plt.savefig('holiday-vs-count.png')

Question 9

Its also possible to just create a matplotlib figure object and then use plt.savefig(...):

from matplotlib import pyplot as plt
import seaborn as sns
import pandas as pd

df = sns.load_dataset('iris')
plt.figure() # Push new figure on stack
sns_plot = sns.pairplot(df, hue='species', size=2.5)
plt.savefig('output.png') # Save that figure

Question 10

You would get an error for using sns.figure.savefig("output.png") in seaborn 0.8.1.

Instead use:

import seaborn as sns

df = sns.load_dataset('iris')
sns_plot = sns.pairplot(df, hue='species', size=2.5)
sns_plot.savefig("output.png")

Question 11

Just FYI, the below command worked in seaborn 0.8.1 so I guess the initial answer is still valid.

sns_plot = sns.pairplot(data, hue='species', size=3)
sns_plot.savefig("output.png")

Question 12

I’m trying to use my own labels for a Seaborn barplot with the following code:

import pandas as pd
import seaborn as sns

fake = pd.DataFrame({'cat': ['red', 'green', 'blue'], 'val': [1, 2, 3]})
fig = sns.barplot(x = 'val', y = 'cat', 
                  data = fake, 
                  color = 'black')
fig.set_axis_labels('Colors', 'Values')

However, I get an error that:

AttributeError: 'AxesSubplot' object has no attribute 'set_axis_labels'

What gives?

Question 13

Seaborn’s barplot returns an axis-object (not a figure). This means you can do the following:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

fake = pd.DataFrame({'cat': ['red', 'green', 'blue'], 'val': [1, 2, 3]})
ax = sns.barplot(x = 'val', y = 'cat', 
              data = fake, 
              color = 'black')
ax.set(xlabel='common xlabel', ylabel='common ylabel')
plt.show()

Question 14

One can avoid the AttributeError brought about by set_axis_labels() method by using the matplotlib.pyplot.xlabel and matplotlib.pyplot.ylabel.

matplotlib.pyplot.xlabel sets the x-axis label while the matplotlib.pyplot.ylabel sets the y-axis label of the current axis.

Solution code:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

fake = pd.DataFrame({'cat': ['red', 'green', 'blue'], 'val': [1, 2, 3]})
fig = sns.barplot(x = 'val', y = 'cat', data = fake, color = 'black')
plt.xlabel("Colors")
plt.ylabel("Values")
plt.title("Colors vs Values") # You can comment this line out if you don't need title
plt.show(fig)

Output figure:

Question 15

You can also set the title of your chart by adding the title parameter as follows

ax.set(xlabel='common xlabel', ylabel='common ylabel', title='some title')

Question 16

How do I add a title to this Seaborne plot? Let’s give it a title ‘I AM A TITLE’.

tips = sns.load_dataset("tips")
g = sns.FacetGrid(tips, col="sex", row="smoker", margin_titles=True)
g.map(sns.plt.scatter, "total_bill", "tip")

Question 17

After those lines:

plt.subplots_adjust(top=0.9)
g.fig.suptitle('THIS IS A TITLE, YOU BET') # can also get the figure from plt.gcf()

If you add a suptitle without adjusting the axis, the seaborn facet titles overlap it.

(With different data):

Question 18

In ipython notebook, this worked for me!

sns.plt.title('YOUR TITLE HERE')

Question 19

g.fig.subplots_adjust(top=0.9)
g.fig.suptitle('Title', fontsize=16)

More info here: http://matplotlib.org/api/figure_api.html

Question 20

What worked for me was:

sns.plt.suptitle('YOUR TITLE HERE')

Question 21

plt.suptitle("Title")

or

plt.title("Title")

This worked for me.

Question 22

The answers using sns.plt.title() and sns.plt.suptitle() don’t work anymore.

Instead, you need to use matplotlib’s title() function:

import matplotlib.pyplot as plt
sns.FacetGrid(<whatever>)
plt.title("A title")

Question 23

The title will not be center aligned with the subplot titles. To set the position of the title you can use plt.suptitle("Title", x=center)

In my case, my subplots were in a 2×1 grid, so I was able to use bbox = g.axes[0,0].get_position() to find the bounding box and then center=0.5*(bbox.x1+bbox.x2)

Question 24

When plotting heatmaps with seaborn (and correlation matrices with matplotlib) the first and the last row is cut in halve. This happens also when I run this minimal code example which I found online.

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

data = pd.read_csv('https://raw.githubusercontent.com/resbaz/r-novice-gapminder-files/master/data/gapminder-FiveYearData.csv')
plt.figure(figsize=(10,5))
sns.heatmap(data.corr())
plt.show()

The labels at the y axis are on the correct spot, but the rows aren’t completely there.

A few days ago, it work as intended. Since then, I installed texlive-xetex so I removed it again but it didn’t solve my problem.

Any ideas what I could be missing?

Question 25

Unfortunately matplotlib 3.1.1 broke seaborn heatmaps; and in general inverted axes with fixed ticks.
This is fixed in the current development version; you may hence

revert to matplotlib 3.1.0
use matplotlib 3.1.2 or higher
set the heatmap limits manually (ax.set_ylim(bottom, top) # set the ylim to bottom, top)

Question 26

Its a bug in the matplotlib regression between 3.1.0 and 3.1.1 You can correct this by:

import seaborn as sns
df_corr = someDataFrame.corr()
ax = sns.heatmap(df_corr, annot=True) #notation: "annot" not "annote"
bottom, top = ax.get_ylim()
ax.set_ylim(bottom + 0.5, top - 0.5)

Question 27

Fixed using the above and setting the heatmap limits manually.

First

ax = sns.heatmap(...

checked the current axes with

ax.get_ylim()
(5.5, 0.5)

Fixed with

ax.set_ylim(6.0, 0)

Question 28

I solved it by adding this line in my code, with matplotlib==3.1.1:

ax.set_ylim(sorted(ax.get_xlim(), reverse=True))

NB. The only reason this works is because the x-axis isn’t changed, so use at your own risk with future mpl versions

Question 29

matplotlib 3.1.2 is out – It is available in the Anaconda cloud via conda-forge but I was not able to install it via conda install. The manual alternative worked: Download matplotlib 3.1.2 from github and install via pip

 % curl https://codeload.github.com/matplotlib/matplotlib/tar.gz/v3.1.2 --output matplotlib-3.1.2.tar.gz
 % pip install matplotlib-3.1.2.tar.gz

Question 30

It happens with matplotlib version 3.1.1 as suggested by importanceofbeingernest

Following solved my problem

pip install matplotlib==3.1.0

Question 31

rustyDev is right about conda-forge, but I did not need to do a manual pip install from a github download. For me, on Windows, it worked directly. And the plots are all nice again.

https://anaconda.org/conda-forge/matplotlib

conda install -c conda-forge matplotlib

optional points, not needed for the answer:

Afterwards, I tried other steps, but they are not needed: In conda prompt: conda search matplotlib –info showed no new version info, the most recent info was for 3.1.1. Thus I tried pip using pip install matplotlib==3.1.2 But pip says “Requirement already satisfied”

Then getting the version according to medium.com/@rakshithvasudev/… python - import matplotlib - matplotlib.__version__ shows that 3.1.2 was successfully installed

Btw, I had this error directly after updating Spyder to v4.0.0. The error was in a plot of a confusion matrix. This was mentioned already some months ago. stackoverflow.com/questions/57225685/… which is already linked to this seaborn question.

Question 32

conda install matplotlib=3.1.0

This worked for me and downgraded matplotlib from 3.1.1 to 3.1.0 and the heatmaps started to behave correctly

Question 33

I solved this problem with the following code:

Question 34

I strongly prefer using matplotlib in OOP style:

f, axarr = plt.subplots(2, sharex=True)
axarr[0].plot(...)
axarr[1].plot(...)

This makes it easier to keep track of multiple figures and subplots.

Question: How to use seaborn this way? Or, how to change this example to OOP style? How to tell seaborn plotting functions like lmplot which Figure or Axes it plots to?

Question 35

It depends a bit on which seaborn function you are using.

The plotting functions in seaborn are broadly divided into two classes

“Axes-level” functions, including regplot, boxplot, kdeplot, and many others
“Figure-level” functions, including lmplot, factorplot, jointplot and one or two others

The first group is identified by taking an explicit ax argument and returning an Axes object. As this suggests, you can use them in an “object oriented” style by passing your Axes to them:

f, (ax1, ax2) = plt.subplots(2)
sns.regplot(x, y, ax=ax1)
sns.kdeplot(x, ax=ax2)

Axes-level functions will only draw onto an Axes and won’t otherwise mess with the figure, so they can coexist perfectly happily in an object-oriented matplotlib script.

The second group of functions (Figure-level) are distinguished by the fact that the resulting plot can potentially include several Axes which are always organized in a “meaningful” way. That means that the functions need to have total control over the figure, so it isn’t possible to plot, say, an lmplot onto one that already exists. Calling the function always initializes a figure and sets it up for the specific plot it’s drawing.

However, once you’ve called lmplot, it will return an object of the type FacetGrid. This object has some methods for operating on the resulting plot that know a bit about the structure of the plot. It also exposes the underlying figure and array of axes at the FacetGrid.fig and FacetGrid.axes arguments. The jointplot function is very similar, but it uses a JointGrid object. So you can still use these functions in an object-oriented context, but all of your customization has to come after you’ve called the function.

Question 36

How do I change the size of my image so it’s suitable for printing?

For example, I’d like to use to A4 paper, whose dimensions are 11.7 inches by 8.27 inches in landscape orientation.

Question 37

You need to create the matplotlib Figure and Axes objects ahead of time, specifying how big the figure is:

from matplotlib import pyplot
import seaborn

import mylib

a4_dims = (11.7, 8.27)
df = mylib.load_data()
fig, ax = pyplot.subplots(figsize=a4_dims)
seaborn.violinplot(ax=ax, data=df, **violin_options)

Question 38

You can also set figure size by passing dictionary to rc parameter with key 'figure.figsize' in seaborn set method:

import seaborn as sns

sns.set(rc={'figure.figsize':(11.7,8.27)})

Other alternative may be to use figure.figsize of rcParams to set figure size as below:

from matplotlib import rcParams

# figure size in inches
rcParams['figure.figsize'] = 11.7,8.27

More details can be found in matplotlib documentation

Question 39

You can set the context to be poster or manually set fig_size.

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

np.random.seed(0)
n, p = 40, 8
d = np.random.normal(0, 2, (n, p))
d += np.log(np.arange(1, p + 1)) * -5 + 10


# plot
sns.set_style('ticks')
fig, ax = plt.subplots()
# the size of A4 paper
fig.set_size_inches(11.7, 8.27)
sns.violinplot(data=d, inner="points", ax=ax)    
sns.despine()

fig.savefig('example.png')

Question 40

Note that if you are trying to pass to a “figure level” method in seaborn (for example lmplot, catplot / factorplot, jointplot) you can and should specify this within the arguments using height and aspect.

sns.catplot(data=df, x='xvar', y='yvar', 
    hue='hue_bar', height=8.27, aspect=11.7/8.27)

See https://github.com/mwaskom/seaborn/issues/488 and Plotting with seaborn using the matplotlib object-oriented interface for more details on the fact that figure level methods do not obey axes specifications.

Question 41

first import matplotlib and use it to set the size of the figure

from matplotlib import pyplot as plt
import seaborn as sns

plt.figure(figsize=(15,8))
ax = sns.barplot(x="Word", y="Frequency", data=boxdata)

Question 42

This shall also work.

from matplotlib import pyplot as plt
import seaborn as sns    

plt.figure(figsize=(15,16))
sns.countplot(data=yourdata, ...)

Question 43

This can be done using:

plt.figure(figsize=(15,8))
sns.kdeplot(data,shade=True)

Question 44

For my plot (a sns factorplot) the proposed answer didn’t works fine.

Thus I use

plt.gcf().set_size_inches(11.7, 8.27)

Just after the plot with seaborn (so no need to pass an ax to seaborn or to change the rc settings).

Question 45

In addition to elz answer regarding “figure level” methods that return multi-plot grid objects it is possible to set the figure height and width explicitly (that is without using aspect ratio) using the following approach:

import seaborn as sns 

g = sns.catplot(data=df, x='xvar', y='yvar', hue='hue_bar')
g.fig.set_figwidth(8.27)
g.fig.set_figheight(11.7)

Question 46

The top answers by Paul H and J. Li do not work for all types of seaborn figures. For the FacetGrid type (for instance sns.lmplot()), use the size and aspect parameter.

Size changes both the height and width, maintaining the aspect ratio.

Aspect only changes the width, keeping the height constant.

You can always get your desired size by playing with these two parameters.

Credit: https://stackoverflow.com/a/28765059/3901029

Question 47

I’m sure I’m forgetting something very simple, but I cannot get certain plots to work with Seaborn.

If I do:

import seaborn as sns

Then any plots that I create as usual with matplotlib get the Seaborn styling (with the grey grid in the background).

However, if I try to do one of the examples, such as:

In [1]: import seaborn as sns

In [2]: sns.set()

In [3]: df = sns.load_dataset('iris')

In [4]: sns.pairplot(df, hue='species', size=2.5)
Out[4]: <seaborn.axisgrid.PairGrid at 0x3e59150>

The pairplot function returns a PairGrid object, but the plot doesn’t show up.

I’m a little confused because matplotlib seems to be functioning properly, and the Seaborn styles are applied to other matplotlib plots, but the Seaborn functions don’t seem to do anything. Does anybody have any idea what might be the problem?

Question 48

Plots created using seaborn need to be displayed like ordinary matplotlib plots. This can be done using the

plt.show()

function from matplotlib.

Originally I posted the solution to use the already imported matplotlib object from seaborn (sns.plt.show()) however this is considered to be a bad practice. Therefore, simply directly import the matplotlib.pyplot module and show your plots with

import matplotlib.pyplot as plt
plt.show()

If the IPython notebook is used the inline backend can be invoked to remove the necessity of calling show after each plot. The respective magic is

%matplotlib inline

Question 49

I come to this question quite regularly and it always takes me a while to find what I search:

import seaborn as sns
import matplotlib.pyplot as plt

plt.show()  # <--- This is what you are looking for

Please note: In Python 2, you can also use sns.plt.show(), but not in Python 3.

Complete Example

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""Visualize C_0.99 for all languages except the 10 with most characters."""

import seaborn as sns
import matplotlib.pyplot as plt

l = [41, 44, 46, 46, 47, 47, 48, 48, 49, 51, 52, 53, 53, 53, 53, 55, 55, 55,
     55, 56, 56, 56, 56, 56, 56, 57, 57, 57, 57, 57, 57, 57, 57, 58, 58, 58,
     58, 59, 59, 59, 59, 59, 59, 59, 59, 60, 60, 60, 60, 60, 60, 60, 60, 61,
     61, 61, 61, 61, 61, 61, 61, 61, 61, 61, 62, 62, 62, 62, 62, 62, 62, 62,
     62, 63, 63, 63, 63, 63, 63, 63, 63, 63, 64, 64, 64, 64, 64, 64, 64, 65,
     65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 66, 66, 66, 66, 66, 66, 66,
     67, 67, 67, 67, 67, 67, 67, 67, 68, 68, 68, 68, 68, 69, 69, 69, 70, 70,
     70, 70, 71, 71, 71, 71, 71, 72, 72, 72, 72, 73, 73, 73, 73, 73, 73, 73,
     74, 74, 74, 74, 74, 75, 75, 75, 76, 77, 77, 78, 78, 79, 79, 79, 79, 80,
     80, 80, 80, 81, 81, 81, 81, 83, 84, 84, 85, 86, 86, 86, 86, 87, 87, 87,
     87, 87, 88, 90, 90, 90, 90, 90, 90, 91, 91, 91, 91, 91, 91, 91, 91, 92,
     92, 93, 93, 93, 94, 95, 95, 96, 98, 98, 99, 100, 102, 104, 105, 107, 108,
     109, 110, 110, 113, 113, 115, 116, 118, 119, 121]

sns.distplot(l, kde=True, rug=False)

plt.show()

Gives

Question 50

To avoid confusion (as there seems to be some in the comments). Assuming you are on Jupyter:

%matplotlib inline > displays the plots INSIDE the notebook

sns.plt.show() > displays the plots OUTSIDE of the notebook

%matplotlib inline will OVERRIDE sns.plt.show() in the sense that plots will be shown IN the notebook even when sns.plt.show() is called.

And yes, it is easy to include the line in to your config:

Automatically run %matplotlib inline in IPython Notebook

But it seems a better convention to keep it together with imports in the actual code.

Question 51

This worked for me

import matplotlib.pyplot as plt
import seaborn as sns
.
.
.
plt.show(sns)

Question 52

My advice is just to give a

plt.figure() and give some sns plot. For example

sns.distplot(data).

Though it will look it doesnt show any plot, When you maximise the figure, you will be able to see the plot.

Question 53

If you plot in IPython console (where you can’t use %matplotlib inline) instead of Jupyter notebook, and don’t want to run plt.show() repeatedly, you can start IPython console with ipython --pylab:

$ ipython --pylab     
Python 3.6.6 |Anaconda custom (64-bit)| (default, Jun 28 2018, 17:14:51) 
Type 'copyright', 'credits' or 'license' for more information
IPython 7.0.1 -- An enhanced Interactive Python. Type '?' for help.
Using matplotlib backend: Qt5Agg

In [1]: import seaborn as sns

In [2]: tips = sns.load_dataset("tips")

In [3]: sns.relplot(x="total_bill", y="tip", data=tips) # you can see the plot now

Question 54

To tell from the style of your code snippet, I suppose you were using IPython rather than Jupyter Notebook.

In this issue on GitHub, it was made clear by a member of IPython in 2016 that the display of charts would only work when “only work when it’s a Jupyter kernel”. Thus, the %matplotlib inline would not work.

I was just having the same issue and suggest you use Jupyter Notebook for the visualization.

问题：如何将Seaborn图保存到文件中

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问题：Seaborn Barplot上的标签轴

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问题：如何为Seaborn Facet Plot添加标题

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问题：matplotlib / seaborn：热图图的第一行和最后一行被切成两半

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问题：使用matplotlib面向对象的界面进行seaborn绘图

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问题：如何更改海图的图形大小？

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问题：Seaborn地块未显示

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