In [1]:

    

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

%matplotlib inline


    

In [9]:

    

# %load snippets/simple_setup.py
"""
Simple notebook set up
"""


import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import sklearn

%matplotlib inline

# some basic plotting directives

plt.rcParams["figure.figsize"] = (16, 12)
# we check this in a second
# %config InlineBackend.figure_format = "retina"


    

In [10]:

    

from sklearn.datasets import make_classification


    

In [15]:

    

X, y = make_classification(200, n_features=2, n_informative=2, n_redundant=0, n_repeated=0, random_state=42)

X_0 = X[y == 0]
X_1 = X[y == 1]

plt.scatter(X[:, 0], X[:, 1], c=y)


    

    
Out[15]:





<matplotlib.collections.PathCollection at 0x121b564e0>






    

In [18]:

    

import seaborn as sns
sns.set_style("whitegrid")
plt.scatter(X[:, 0], X[:, 1], c=y)


    

    
Out[18]:





<matplotlib.collections.PathCollection at 0x124435b38>






    

In [19]:

    

current_palette = sns.color_palette()
sns.palplot(current_palette)