diff --git a/.flake8 b/.flake8
@@ -240,6 +240,7 @@ per-file-ignores =
     examples/text_labels_and_annotations/tex_demo.py: E402
     examples/text_labels_and_annotations/watermark_text.py: E402
     examples/ticks_and_spines/auto_ticks.py: E501
+    examples/ticks_and_spines/date_concise_formatter.py: E402 
     examples/user_interfaces/canvasagg.py: E402
     examples/user_interfaces/embedding_in_gtk3_panzoom_sgskip.py: E402
     examples/user_interfaces/embedding_in_gtk3_sgskip.py: E402

diff --git a/doc/users/next_whats_new/concise_date_formatter.rst b/doc/users/next_whats_new/concise_date_formatter.rst
@@ -0,0 +1,40 @@
+:orphan:
+
+New date formatter: `~.dates.ConciseDateFormatter`
+--------------------------------------------------
+
+The automatic date formatter used by default can be quite verbose.  A new
+formatter can be accessed that tries to make the tick labels appropriately
+concise.
+
+  .. plot::
+
+    import datetime
+    import matplotlib.pyplot as plt
+    import matplotlib.dates as mdates
+    import numpy as np
+
+    # make a timeseries...
+    base = datetime.datetime(2005, 2, 1)
+    dates = np.array([base + datetime.timedelta(hours= 2 * i)
+                      for i in range(732)])
+    N = len(dates)
+    np.random.seed(19680801)
+    y = np.cumsum(np.random.randn(N))
+
+    lims = [(np.datetime64('2005-02'), np.datetime64('2005-04')),
+            (np.datetime64('2005-02-03'), np.datetime64('2005-02-15')),
+            (np.datetime64('2005-02-03 11:00'), np.datetime64('2005-02-04 13:20'))]
+    fig, axs = plt.subplots(3, 1, constrained_layout=True)
+    for nn, ax in enumerate(axs):
+        # activate the formatter here.
+        locator = mdates.AutoDateLocator()
+        formatter = mdates.ConciseDateFormatter(locator)
+        ax.xaxis.set_major_locator(locator)
+        ax.xaxis.set_major_formatter(formatter)
+
+        ax.plot(dates, y)
+        ax.set_xlim(lims[nn])
+    axs[0].set_title('Concise Date Formatter')
+
+    plt.show()
diff --git a/examples/ticks_and_spines/date_concise_formatter.py b/examples/ticks_and_spines/date_concise_formatter.py
@@ -0,0 +1,183 @@
+"""
+================================================
+Formatting date ticks using ConciseDateFormatter
+================================================
+
+Finding good tick values and formatting the ticks for an axis that
+has date data is often a challenge.  `~.dates.ConciseDateFormatter` is
+meant to improve the strings chosen for the ticklabels, and to minimize
+the strings used in those tick labels as much as possible.
+
+.. note::
+
+    This formatter is a candidate to become the default date tick formatter
+    in future versions of Matplotlib.  Please report any issues or
+    suggestions for improvement to the github repository or mailing list.
+
+"""
+import datetime
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+import numpy as np
+
+#############################################################################
+# First, the default formatter.
+
+base = datetime.datetime(2005, 2, 1)
+dates = np.array([base + datetime.timedelta(hours=(2 * i))
+                  for i in range(732)])
+N = len(dates)
+np.random.seed(19680801)
+y = np.cumsum(np.random.randn(N))
+
+fig, axs = plt.subplots(3, 1, constrained_layout=True, figsize=(6, 6))
+lims = [(np.datetime64('2005-02'), np.datetime64('2005-04')),
+        (np.datetime64('2005-02-03'), np.datetime64('2005-02-15')),
+        (np.datetime64('2005-02-03 11:00'), np.datetime64('2005-02-04 13:20'))]
+for nn, ax in enumerate(axs):
+    ax.plot(dates, y)
+    ax.set_xlim(lims[nn])
+    # rotate_labels...
+    for label in ax.get_xticklabels():
+        label.set_rotation(40)
+        label.set_horizontalalignment('right')
+axs[0].set_title('Default Date Formatter')
+plt.show()
+
+#############################################################################
+# The default date formater is quite verbose, so we have the option of
+# using `~.dates.ConciseDateFormatter`, as shown below.  Note that
+# for this example the labels do not need to be rotated as they do for the
+# default formatter because the labels are as small as possible.
+
+fig, axs = plt.subplots(3, 1, constrained_layout=True, figsize=(6, 6))
+for nn, ax in enumerate(axs):
+    locator = mdates.AutoDateLocator(minticks=3, maxticks=7)
+    formatter = mdates.ConciseDateFormatter(locator)
+    ax.xaxis.set_major_locator(locator)
+    ax.xaxis.set_major_formatter(formatter)
+
+    ax.plot(dates, y)
+    ax.set_xlim(lims[nn])
+axs[0].set_title('Concise Date Formatter')
+
+plt.show()
+
+#############################################################################
+# If all calls to axes that have dates are to be made using this converter,
+# it is probably most convenient to use the units registry where you do
+# imports:
+
+import matplotlib.units as munits
+converter = mdates.ConciseDateConverter()
+munits.registry[np.datetime64] = converter
+munits.registry[datetime.date] = converter
+munits.registry[datetime.datetime] = converter
+
+fig, axs = plt.subplots(3, 1, figsize=(6, 6), constrained_layout=True)
+for nn, ax in enumerate(axs):
+    ax.plot(dates, y)
+    ax.set_xlim(lims[nn])
+axs[0].set_title('Concise Date Formatter')
+
+plt.show()
+
+#############################################################################
+# Localization of date formats
+# ============================
+#
+# Dates formats can be localized if the default formats are not desirable by
+# manipulating one of three lists of strings.
+#
+# The ``formatter.formats`` list of formats is for the normal tick labels,
+# There are six levels: years, months, days, hours, minutes, seconds.
+# The ``formatter.offset_formats`` is how the "offset" string on the right
+# of the axis is formatted.  This is usually much more verbose than the tick
+# labels. Finally, the ``formatter.zero_formats`` are the formats of the
+# ticks that are "zeros".  These are tick values that are either the first of
+# the year, month, or day of month, or the zeroth hour, minute, or second.
+# These are usually the same as the format of
+# the ticks a level above.  For example if the axis limts mean the ticks are
+# mostly days, then we label 1 Mar 2005 simply with a "Mar".  If the axis
+# limits are mostly hours, we label Feb 4 00:00 as simply "Feb-4".
+#
+# Note that these format lists can also be passed to `.ConciseDateFormatter`
+# as optional kwargs.
+#
+# Here we modify the labels to be "day month year", instead of the ISO
+# "year month day":
+
+fig, axs = plt.subplots(3, 1, constrained_layout=True, figsize=(6, 6))
+
+for nn, ax in enumerate(axs):
+    locator = mdates.AutoDateLocator()
+    formatter = mdates.ConciseDateFormatter(locator)
+    formatter.formats = ['%y',  # ticks are mostly years
+                         '%b',       # ticks are mostly months
+                         '%d',       # ticks are mostly days
+                         '%H:%M',    # hrs
+                         '%H:%M',    # min
+                         '%S.%f', ]  # secs
+    # these are mostly just the level above...
+    formatter.zero_formats = [''] + formatter.formats[:-1]
+    # ...except for ticks that are mostly hours, then it is nice to have
+    # month-day:
+    formatter.zero_formats[3] = '%d-%b'
+
+    formatter.offset_formats = ['',
+                                '%Y',
+                                '%b %Y',
+                                '%d %b %Y',
+                                '%d %b %Y',
+                                '%d %b %Y %H:%M', ]
+    ax.xaxis.set_major_locator(locator)
+    ax.xaxis.set_major_formatter(formatter)
+
+    ax.plot(dates, y)
+    ax.set_xlim(lims[nn])
+axs[0].set_title('Concise Date Formatter')
+
+plt.show()
+
+#############################################################################
+# Registering a converter with localization
+# =========================================
+#
+# `.ConciseDateFormatter` doesn't have rcParams entries, but localization
+# can be accomplished by passing kwargs to `~.ConciseDateConverter` and
+# registering the datatypes you will use with the units registry:
+
+import datetime
+
+formats = ['%y',          # ticks are mostly years
+           '%b',     # ticks are mostly months
+           '%d',     # ticks are mostly days
+           '%H:%M',  # hrs
+           '%H:%M',  # min
+           '%S.%f', ]  # secs
+# these can be the same, except offset by one level....
+zero_formats = [''] + formats[:-1]
+# ...except for ticks that are mostly hours, then its nice to have month-day
+zero_formats[3] = '%d-%b'
+offset_formats = ['',
+                  '%Y',
+                  '%b %Y',
+                  '%d %b %Y',
+                  '%d %b %Y',
+                  '%d %b %Y %H:%M', ]
+
+converter = mdates.ConciseDateConverter(formats=formats,
+                                 zero_formats=zero_formats,
+                                 offset_formats=offset_formats)
+
+munits.registry[np.datetime64] = converter
+munits.registry[datetime.date] = converter
+munits.registry[datetime.datetime] = converter
+
+fig, axs = plt.subplots(3, 1, constrained_layout=True, figsize=(6, 6))
+for nn, ax in enumerate(axs):
+    ax.plot(dates, y)
+    ax.set_xlim(lims[nn])
+axs[0].set_title('Concise Date Formatter registered non-default')
+
+plt.show()