Settings_And_Stylesheets

Customizing Matplotlib: Configurations and Stylesheets

Plot Customization by Hand

import matplotlib.pyplot as plt

plt.style.use('classic')
import numpy as np

%matplotlib
inline

x = np.random.randn(1000)
plt.hist(x);

# use a gray background
ax = plt.axes()
ax.set_facecolor('#E6E6E6')
ax.set_axisbelow(True)

# draw solid white grid lines
plt.grid(color='w', linestyle='solid')

# hide axis spines
for spine in ax.spines.values():
    spine.set_visible(False)

# hide top and right ticks
ax.xaxis.tick_bottom()
ax.yaxis.tick_left()

# lighten ticks and labels
ax.tick_params(colors='gray', direction='out')
for tick in ax.get_xticklabels():
    tick.set_color('gray')
for tick in ax.get_yticklabels():
    tick.set_color('gray')

# control face and edge color of histogram
ax.hist(x, edgecolor='#E6E6E6', color='#EE6666');

Changing the Defaults: rcParams

IPython_default = plt.rcParams.copy()

from matplotlib import cycler

colors = cycler('color',
                ['#EE6666', '#3388BB', '#9988DD',
                 '#EECC55', '#88BB44', '#FFBBBB'])
plt.rc('axes', facecolor='#E6E6E6', edgecolor='none',
       axisbelow=True, grid=True, prop_cycle=colors)
plt.rc('grid', color='w', linestyle='solid')
plt.rc('xtick', direction='out', color='gray')
plt.rc('ytick', direction='out', color='gray')
plt.rc('patch', edgecolor='#E6E6E6')
plt.rc('lines', linewidth=2)

plt.hist(x);

# rc 매개변수를 활용했을 때 간단한 라인 플롯
for i in range(4):
    plt.plot(np.random.rand(10))

Stylesheets

plt.style.available[:5]

['Solarize_Light2',
 '_classic_test_patch',
 '_mpl-gallery',
 '_mpl-gallery-nogrid',
 'bmh']

def hist_and_lines():
    np.random.seed(0)
    fig, ax = plt.subplots(1, 2, figsize=(11, 4))
    ax[0].hist(np.random.randn(1000))
    for i in range(3):
        ax[1].plot(np.random.rand(10))
    ax[1].legend(['a', 'b', 'c'], loc='lower left')

Default style

# reset rcParams
plt.rcParams.update(IPython_default);

hist_and_lines()

FiveThiryEight style

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

ggplot

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

Bayesian Methods for Hackers style

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

Dark background

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

Grayscale

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

Seaborn style

import seaborn

hist_and_lines()