# -*- coding: utf-8 -*-
"""

Created on Fri May 04 11:10:51 2012

Author: Ralf Gommers

"""

#Load the El Nino dataset.  Consists of 60 years worth of Pacific Ocean sea
#surface temperature data.

import matplotlib.pyplot as plt
import numpy as np

import statsmodels.api as sm

data = sm.datasets.elnino.load()

#Create a functional boxplot.  We see that the years 1982-83 and 1997-98 are
#outliers; these are the years where El Nino (a climate pattern
#characterized by warming up of the sea surface and higher air pressures)
#occurred with unusual intensity.

fig = plt.figure()
ax = fig.add_subplot(111)
res = sm.graphics.fboxplot(data.raw_data.iloc[:, 1:], wfactor=2.58,
                           labels=data.raw_data.iloc[:, 0].astype(int),
                           ax=ax)

ax.set_xlabel("Month of the year")
ax.set_ylabel("Sea surface temperature (C)")
ax.set_xticks(np.arange(13, step=3) - 1)
ax.set_xticklabels(["", "Mar", "Jun", "Sep", "Dec"])
ax.set_xlim([-0.2, 11.2])

#plt.show()

numpy.arange