notebook.community

Edit and run

Matplotlib styles examples

The matplotlib documentation is pretty incomplete, and all you really want to know about its style sheets is what they look like - but they're not shown in an easily comparable way. So here they are!





In [49]:



    


%matplotlib inline

from matplotlib import pyplot as plt
import numpy as np

sorted(plt.style.available)



    


















    
Out[49]:








['bmh',
 'classic',
 'dark_background',
 'fivethirtyeight',
 'ggplot',
 'grayscale',
 'seaborn-bright',
 'seaborn-colorblind',
 'seaborn-dark',
 'seaborn-dark-palette',
 'seaborn-darkgrid',
 'seaborn-deep',
 'seaborn-muted',
 'seaborn-notebook',
 'seaborn-paper',
 'seaborn-pastel',
 'seaborn-poster',
 'seaborn-talk',
 'seaborn-ticks',
 'seaborn-white',
 'seaborn-whitegrid']

And what do they look like?

To globally change the style, use plt.style.use(<name>). Here, we're going to temporarily switch between them using the context manager form: with plt.style.context((<name>)). But first let's set up the plots we want to show.





In [50]:



    


def make_title(s):
    return s.replace('-', ' ').replace('_', ' ').title()


def make_plots(style_str=None):
    fig, axes_array = plt.subplots(2, 2)
    ((ax1, ax2), (ax3, ax4)) = axes_array
    
    # sine and cosine line plots
    x = np.arange(10)
    y_sin = np.sin(x)
    y_cos = np.cos(x)
    ax1.plot(x, y_sin)
    ax1.plot(x, y_cos)
    ax1.set_title('sine and cosine line plots')
    
    # a random scatter plot
    points1 = np.random.rand(20,2)
    points2 = np.random.rand(20,2)
    ax2.scatter(points1[:, 0], points1[:, 1])
    ax2.scatter(points2[:, 0], points1[:, 1])
    ax2.set_title('a random scatter plot')
    
    # a random bar graph
    width = 0.4
    middles = np.arange(1, 6)
    heights1 = np.random.rand(5)
    heights2 = np.random.rand(5)
    ax3.bar(middles - width, heights1, width)
    ax3.bar(middles, heights2, width)
    ax3.set_title('a random bar graph')
    
    # a random pie chart
    values = np.random.rand(5)
    frac_values = values/values.sum()
    labels = ['A', 'B', 'C', 'D', 'E']
    ax4.pie(frac_values, labels=labels)
    ax4.set_title('a random pie chart')
    
    # draw them!
    fig.suptitle('{} ({})'.format(make_title(style_str), style_str) if style_str else 'Default Settings', fontsize=20)
    fig.subplots_adjust(hspace=0.3)
    fig.set_size_inches(10, 10)
    plt.show()

Things you'll note

  • Pie charts don't play nice with style sheet colours
  • Seaborn styles are generally quite nice (note: your matplotlib starts using a seaborn style if you simply import seaborn!)
  • Matlab-like styles make horrible graphs for horrible people
  • None of these plots are really ready for presenting without more tinkering!

Default settings





In [51]:



    


make_plots()

Seaborn Darkgrid ('seaborn-darkgrid')





In [52]:



    


with plt.style.context(('seaborn-darkgrid')):
    make_plots('seaborn-darkgrid')

Seaborn Whitegrid ('seaborn-whitegrid')





In [53]:



    


with plt.style.context(('seaborn-whitegrid')):
    make_plots('seaborn-whitegrid')

Seaborn Dark Palette ('seaborn-dark-palette')





In [54]:



    


with plt.style.context(('seaborn-dark-palette')):
    make_plots('seaborn-dark-palette')

Seaborn Paper ('seaborn-paper')





In [55]:



    


with plt.style.context(('seaborn-paper')):
    make_plots('seaborn-paper')

Seaborn Talk ('seaborn-talk')





In [56]:



    


with plt.style.context(('seaborn-talk')):
    make_plots('seaborn-talk')

Seaborn Dark ('seaborn-dark')





In [57]:



    


with plt.style.context(('seaborn-dark')):
    make_plots('seaborn-dark')

Seaborn Bright ('seaborn-bright')





In [58]:



    


with plt.style.context(('seaborn-bright')):
    make_plots('seaborn-bright')

Ggplot ('ggplot')





In [59]:



    


with plt.style.context(('ggplot')):
    make_plots('ggplot')

Grayscale ('grayscale')





In [60]:



    


with plt.style.context(('grayscale')):
    make_plots('grayscale')

Seaborn Pastel ('seaborn-pastel')





In [61]:



    


with plt.style.context(('seaborn-pastel')):
    make_plots('seaborn-pastel')

Bmh ('bmh')





In [62]:



    


with plt.style.context(('bmh')):
    make_plots('bmh')

Seaborn Colorblind ('seaborn-colorblind')





In [63]:



    


with plt.style.context(('seaborn-colorblind')):
    make_plots('seaborn-colorblind')

Seaborn Ticks ('seaborn-ticks')





In [64]:



    


with plt.style.context(('seaborn-ticks')):
    make_plots('seaborn-ticks')

Fivethirtyeight ('fivethirtyeight')





In [65]:



    


with plt.style.context(('fivethirtyeight')):
    make_plots('fivethirtyeight')

Dark Background ('dark_background')





In [66]:



    


with plt.style.context(('dark_background')):
    make_plots('dark_background')

Seaborn White ('seaborn-white')





In [67]:



    


with plt.style.context(('seaborn-white')):
    make_plots('seaborn-white')

Classic ('classic')





In [68]:



    


with plt.style.context(('classic')):
    make_plots('classic')

Seaborn Notebook ('seaborn-notebook')





In [69]:



    


with plt.style.context(('seaborn-notebook')):
    make_plots('seaborn-notebook')

Seaborn Muted ('seaborn-muted')





In [70]:



    


with plt.style.context(('seaborn-muted')):
    make_plots('seaborn-muted')

Seaborn Deep ('seaborn-deep')





In [71]:



    


with plt.style.context(('seaborn-deep')):
    make_plots('seaborn-deep')

Seaborn Poster ('seaborn-poster')





In [72]:



    


with plt.style.context(('seaborn-poster')):
    make_plots('seaborn-poster')

Content source: clbarnes/plotstyles

Similar notebooks:

notebook.community | gallery | about