Note
Click here to download the full example code
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.
Out:
loading /tmp/mpl_doc_build/lib/python3.7/site-packages/matplotlib/mpl-data/sample_data/msft.csv
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
from matplotlib.dates import bytespdate2num, num2date
from matplotlib.ticker import Formatter
datafile = cbook.get_sample_data('msft.csv', asfileobj=False)
print('loading %s' % datafile)
msft_data = np.genfromtxt(datafile, delimiter=',', names=True,
converters={0: bytespdate2num('%d-%b-%y')})[-40:]
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(np.round(x))
if ind >= len(self.dates) or ind < 0:
return ''
return num2date(self.dates[ind]).strftime(self.fmt)
formatter = MyFormatter(msft_data['Date'])
fig, ax = plt.subplots()
ax.xaxis.set_major_formatter(formatter)
ax.plot(np.arange(len(msft_data)), msft_data['Close'], 'o-')
fig.autofmt_xdate()
plt.show()
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