import pandas as pd
import numpy as np
# Set some Pandas options
pd.set_option('display.notebook_repr_html', False)
pd.set_option('display.max_columns', 20)
pd.set_option('display.max_rows', 25)
import matplotlib.pyplot as plt
plt.plot(np.random.normal(size=100), np.random.normal(size=100), 'ro')
[<matplotlib.lines.Line2D at 0x11010da10>]
with mpl.rc_context(rc={'font.family': 'serif', 'font.weight': 'bold', 'font.size': 8}):
fig = plt.figure(figsize=(6,3))
ax1 = fig.add_subplot(121)
ax1.set_xlabel('some random numbers')
ax1.set_ylabel('more random numbers')
ax1.set_title("Random scatterplot")
plt.plot(np.random.normal(size=100), np.random.normal(size=100), 'r.')
ax2 = fig.add_subplot(122)
plt.hist(np.random.normal(size=100), bins=15)
ax2.set_xlabel('sample')
ax2.set_ylabel('cumulative sum')
ax2.set_title("Normal distrubution")
plt.tight_layout()
plt.savefig("normalvars.png", dpi=150)
normals = pd.Series(np.random.normal(size=10))
normals.plot()
<matplotlib.axes.AxesSubplot at 0x110119890>
variables = pd.DataFrame({'normal': np.random.normal(size=100),
'gamma': np.random.gamma(1, size=100),
'poisson': np.random.poisson(size=100)})
variables.cumsum(0).plot()
<matplotlib.axes.AxesSubplot at 0x1102ed990>