Date Index FormatterΒΆ

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.

date index formatter2


loading /usr/local/lib64/python3.8/site-packages/matplotlib/mpl-data/sample_data/msft.csv

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.plot(msft_data['Close'], 'o-')

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