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"""
====================
Date Index Formatter
====================
When plotting daily data, a frequent request is to plot the data
ignoring skips, e.g., no extra spaces for weekends. This is particularly
common in financial time series, when you may have data for M-F and
not Sat, Sun and you don't want gaps in the x axis. The approach is
to simply use the integer index for the xdata and a custom tick
Formatter to get the appropriate date string for a given index.
"""
import dateutil.parser
from matplotlib import cbook, dates
import matplotlib.pyplot as plt
from matplotlib.ticker import Formatter
import numpy as np
datafile = cbook.get_sample_data('msft.csv', asfileobj=False)
print('loading %s' % datafile)
msft_data = np.genfromtxt(
datafile, delimiter=',', names=True,
converters={0: lambda s: dates.date2num(dateutil.parser.parse(s))})
class MyFormatter(Formatter):
def __init__(self, dates, fmt='%Y-%m-%d'):
self.dates = dates
self.fmt = fmt
def __call__(self, x, pos=0):
"""Return the label for time x at position pos."""
ind = int(round(x))
if ind >= len(self.dates) or ind < 0:
return ''
return dates.num2date(self.dates[ind]).strftime(self.fmt)
fig, ax = plt.subplots()
ax.xaxis.set_major_formatter(MyFormatter(msft_data['Date']))
ax.plot(msft_data['Close'], 'o-')
fig.autofmt_xdate()
plt.show()
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