"""
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.
"""

from __future__ import print_function
import numpy as np
from matplotlib.mlab import csv2rec
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
from matplotlib.ticker import Formatter

datafile = cbook.get_sample_data('msft.csv', asfileobj=False)
print('loading %s' % datafile)
r = csv2rec(datafile)[-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 self.dates[ind].strftime(self.fmt)

formatter = MyFormatter(r.date)

fig, ax = plt.subplots()
ax.xaxis.set_major_formatter(formatter)
ax.plot(np.arange(len(r)), r.close, 'o-')
fig.autofmt_xdate()
plt.show() 

　

Traceback (most recent call last):
  File "M:\______\date_index_formatter.py", line 12, in 
    from matplotlib.mlab import csv2rec
ImportError: cannot import name 'csv2rec' from 'matplotlib.mlab' 
(C:\Users\______\AppData\Local\Programs\Python\Python311\Lib\site-packages\matplotlib\mlab.py) 

Traceback (most recent call last):
  File "E:\______\date_index_formatter.py", line 12, in 
    from matplotlib.mlab import csv2rec
ImportError: cannot import name 'csv2rec' from 'matplotlib.mlab' 
(C:\Program Files\Python312\Lib\site-packages\matplotlib\mlab.py) 

"""
=====================================
Custom tick formatter for time series
=====================================

.. redirect-from:: /gallery/text_labels_and_annotations/date_index_formatter
.. redirect-from:: /gallery/ticks/date_index_formatter2

When plotting daily data, e.g., financial time series, one often wants
to leave out days on which there is no data, for instance weekends, so that
the data are plotted at regular intervals without extra spaces for the days
with no data.
The example shows how to use an 'index formatter' to achieve the desired plot.
"""

import matplotlib.pyplot as plt
import numpy as np

import matplotlib.cbook as cbook
from matplotlib.dates import DateFormatter, DayLocator
import matplotlib.lines as ml
from matplotlib.ticker import Formatter

# Load a structured numpy array from yahoo csv data with fields date, open, high,
# low, close, volume, adj_close from the mpl-data/sample_data directory. The
# record array stores the date as an np.datetime64 with a day unit ('D') in
# the date column (``r['date']``).
r = cbook.get_sample_data('goog.npz')['price_data']
r = r[:9]  # get the first 9 days

fig, (ax1, ax2) = plt.subplots(nrows=2, figsize=(6, 6), layout='constrained')
fig.get_layout_engine().set(hspace=0.15)

# First we'll do it the default way, with gaps on weekends
ax1.plot(r["date"], r["adj_close"], 'o-')

# Highlight gaps in daily data
gaps = np.flatnonzero(np.diff(r["date"]) > np.timedelta64(1, 'D'))
for gap in r[['date', 'adj_close']][np.stack((gaps, gaps + 1)).T]:
    ax1.plot(gap['date'], gap['adj_close'], 'w--', lw=2)
ax1.legend(handles=[ml.Line2D([], [], ls='--', label='Gaps in daily data')])

ax1.set_title("Plot y at x Coordinates")
ax1.xaxis.set_major_locator(DayLocator())
ax1.xaxis.set_major_formatter(DateFormatter('%a'))


# Next we'll write a custom index formatter. Below we will plot
# the data against an index that goes from 0, 1,  ... len(data).  Instead of
# formatting the tick marks as integers, we format as times.
def format_date(x, _):
    try:
        # convert datetime64 to datetime, and use datetime's strftime:
        return r["date"][round(x)].item().strftime('%a')
    except IndexError:
        pass

# Create an index plot (x defaults to range(len(y)) if omitted)
ax2.plot(r["adj_close"], 'o-')

ax2.set_title("Plot y at Index Coordinates Using Custom Formatter")
ax2.xaxis.set_major_formatter(format_date)  # internally creates FuncFormatter

# %%
# Instead of passing a function into `.Axis.set_major_formatter` you can use
# any other callable, e.g. an instance of a class that implements __call__:


class MyFormatter(Formatter):
    def __init__(self, dates, fmt='%a'):
        self.dates = dates
        self.fmt = fmt

    def __call__(self, x, pos=0):
        """Return the label for time x at position pos."""
        try:
            return self.dates[round(x)].item().strftime(self.fmt)
        except IndexError:
            pass


ax2.xaxis.set_major_formatter(MyFormatter(r["date"], '%a'))

plt.show() 

M:\______\date_index_formatter_2.py:28: MatplotlibDeprecationWarning: 
  In a future release, get_sample_data will automatically load numpy arrays.  
  Set np_load to True to get the array and suppress this warning.  
  Set asfileobj to False to get the path to the data file and suppress this warning.
  r = cbook.get_sample_data('goog.npz')['price_data']
Traceback (most recent call last):
  File "M:\______\date_index_formatter_2.py", line 28, in 
    r = cbook.get_sample_data('goog.npz')['price_data']
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^
TypeError: '_io.BufferedReader' object is not subscriptable 

　Python 3.12.0 (matplotlib 3.8.1) は、正常実行です。

　

• 2023/11/24 Ver=1.04 Python 3.12.0 (matplotlib 3.8.1)で確認
• 2023/11/24 Ver=1.04 Python 3.11.6 (matplotlib 3.7.1)で確認
• 2023/04/02 Ver=1.03 Python 3.11.2 で確認
• 2020/10/31 Ver=1.01 Python 3.7.8 で確認
• 2018/12/01 Ver=1.01 初版リリース

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