adding labels to candlestick chart in matplotlib

I'm trying to add a series (composed of a list of [1,2,0,....]) to a candlestick chart I produced with matplotlib, but cannot work out how to include those labels for each specific candle in the graph. Basically I'd like to produce a chart like this one:

indicators http://www.linnsoft.com/charts/images/TD_Sequential.png

with the labels with the numbers (my signal series) just over or below each candles. Is there any way I can reach that?

Don't know if it helps, but my series are of the pandas DataFrame kind...

Here's an example derived from - http://matplotlib.org/examples/pylab_examples/finance_demo.html

Take special note of ax.annotate method call in the code below.

from pylab import *
from matplotlib.dates import  DateFormatter, WeekdayLocator, HourLocator, \
     DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo, candlestick,\
     plot_day_summary, candlestick2

# (Year, month, day) tuples suffice as args for quotes_historical_yahoo
date1 = ( 2004, 2, 1)
date2 = ( 2004, 4, 12 )


mondays = WeekdayLocator(MONDAY)        # major ticks on the mondays
alldays    = DayLocator()              # minor ticks on the days
weekFormatter = DateFormatter('%b %d')  # Eg, Jan 12
dayFormatter = DateFormatter('%d')      # Eg, 12

quotes = quotes_historical_yahoo('INTC', date1, date2)
if len(quotes) == 0:
    raise SystemExit

fig = figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#ax.xaxis.set_minor_formatter(dayFormatter)

#plot_day_summary(ax, quotes, ticksize=3)
candlestick(ax, quotes, width=0.6)

ax.xaxis_date()
ax.autoscale_view()
setp( gca().get_xticklabels(), rotation=45, horizontalalignment='right')

import datetime
dt = datetime.datetime(2004, 3, 8)

# Annotating a specific candle
ax.annotate('This is my special candle', xy=(dt, 24), xytext=(dt, 25),
            arrowprops=dict(facecolor='black', shrink=0.05),
           )

show()

The resulting plot if you run this file, should show you:-