import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pandas import Series, DataFrame
# local path for the https://github.com/pydata/pydata-book repo
PYDATA_BOOK_REPO_DIR = "/Users/raymondyee/D/Document/Working_with_Open_Data/pydata-book/"
import os
# relative to parent dir
DATA_FILES = {"datadict":"data/census/DataDict.txt",
"dataset":"data/census/DataSet.txt",
"fips": "data/census/FIPS_CountyName.txt"}
def file_path(key):
return os.path.join(os.pardir, DATA_FILES[key])
# run a basic test
plot(arange(10))
[<matplotlib.lines.Line2D at 0x4dffa70>]
ipython --help
yields
--pylab=<CaselessStrEnum> (InteractiveShellApp.pylab)
Default: None
Choices: ['tk', 'qt', 'wx', 'gtk', 'osx', 'inline', 'auto']
Pre-load matplotlib and numpy for interactive use, selecting a particular
matplotlib backend and loop integration.
qtconsole:
ipython qtconsole --pylab
osx:
ipython qtconsole --pylab=osx
fig = plt.figure()
ax1 = fig.add_subplot(2, 2, 1)
ax2 = fig.add_subplot(2, 2, 2)
ax3 = fig.add_subplot(2, 2, 3)
plt.plot([1.5, 3.5, -2, 1.6])
[<matplotlib.lines.Line2D at 0x506c030>]
from numpy.random import randn
plt.plot(randn(50).cumsum(), 'k--')
[<matplotlib.lines.Line2D at 0x50abd30>]
ax1.hist(randn(100), bins=20, color='k', alpha=0.3)
ax2.scatter(np.arange(30), np.arange(30) + 3 * randn(30))
ax3.plot(randn(50).cumsum(), 'k--')
fig
x = arange(-5, 5, 0.001)
y= np.tan(x)
plt.ylim((-10, 10))
tanplot = plot(x,y)