import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline
matplotlib.style.use("ggplot")
plt.style.available
['seaborn-dark',
'seaborn-talk',
'classic',
'seaborn-white',
'fivethirtyeight',
'seaborn-ticks',
'seaborn-colorblind',
'seaborn-muted',
'seaborn-notebook',
'seaborn-dark-palette',
'seaborn-paper',
'seaborn-bright',
'seaborn-darkgrid',
'seaborn-poster',
'seaborn-deep',
'ggplot',
'dark_background',
'seaborn-pastel',
'grayscale',
'bmh',
'seaborn-whitegrid']
# http://matplotlib.org/users/style_sheets.html#temporary-styling
with plt.style.context(('dark_background')):
plt.plot(np.sin(np.linspace(0, 2*np.pi)), 'r-o')
plt.plot(np.sin(np.linspace(0, 2*np.pi)), 'r-o')