I have following candlestick plot. I want to make it scrollable so that I can see more details. The current plot is too long to see details. I have found examples for making a line plot scrollable at here: Matplotlib: scrolling plot
However, updating a candlestick seems way more complicated than updating a line chart. The candlestick plot returns lines and patches. Can you help?
from pandas.io.data import get_data_yahoo
import matplotlib.pyplot as plt
from matplotlib import dates as mdates
from matplotlib import ticker as mticker
from matplotlib.finance import candlestick_ohlc
import datetime as dt
symbol = "GOOG"
data = get_data_yahoo(symbol, start = '2011-9-01', end = '2015-10-23')
data.reset_index(inplace=True)
data['Date']=mdates.date2num(data['Date'].astype(dt.date))
fig = plt.figure()
ax1 = plt.subplot2grid((1,1),(0,0))
plt.title('How to make it scrollable')
plt.ylabel('Price')
ax1.xaxis.set_major_locator(mticker.MaxNLocator(6))
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
candlestick_ohlc(ax1,data.values,width=0.2)
You can plot the whole plot, and then use the slider widget to modify the axes area.
I couldn't reproduce your data because I don't have the pandas.io.data library, so I modified the candlestick example from here, and added the slider.
import matplotlib.pyplot as plt
import datetime
from matplotlib.widgets import Slider
from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlc
from matplotlib.dates import DateFormatter, WeekdayLocator,\
DayLocator, MONDAY
# (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') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
quotes = quotes_historical_yahoo_ohlc('INTC', date1, date2)
if len(quotes) == 0:
raise SystemExit
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
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_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.axis([datetime.date(*date1).toordinal(), datetime.date(*date1).toordinal()+10, 18.5, 22.5])
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
axcolor = 'lightgoldenrodyellow'
axpos = plt.axes([0.2, 0.05, 0.65, 0.03], axisbg=axcolor)
spos = Slider(axpos, 'Position', datetime.date(*date1).toordinal(), datetime.date(*date2).toordinal())
def update(val):
pos = spos.val
ax.axis([pos,pos+10, 18.5, 22.5])
fig.canvas.draw_idle()
spos.on_changed(update)
plt.show()
I hardcoded some values of the axes sizes and positions, please be careful when adapting to your code.
Also same idea can be implemented to add a vertical scroll if needed.