Adds custom plot formatting for TimedeltaIndex.

doc/source/visualization.rst

@@ -1245,6 +1245,16 @@ in ``pandas.plot_params`` can be used in a `with statement`:
 
    plt.close('all')
 
+Automatic Date Tick Adjustment
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Especially for the ``TimedeltaIndex`` that uses native matplotlib
+tick locator methods, it is useful to call the automatic
+date tick adjustment from matplotlib for figures whose ticklabels overlap.
+
+See the :meth:`autofmt_xdate <matplotlib.figure.autofmt_xdate>` method and the
+`matplotlib documentation <http://matplotlib.org/users/recipes.html#fixing-common-date-annoyances>`__ for more.
+
 Subplots
 ~~~~~~~~
 

doc/source/whatsnew/v0.20.0.txt

@@ -117,6 +117,7 @@ Other enhancements
 
 - ``.select_dtypes()`` now allows the string 'datetimetz' to generically select datetimes with tz (:issue:`14910`)
 
+- ``pd.TimedeltaIndex`` now has a custom datetick formatter specifically designed for nanosecond level precision (:issue:`8711`)
 
 .. _whatsnew_0200.api_breaking:
 

pandas/tests/plotting/test_datetimelike.py

@@ -7,6 +7,7 @@
 from pandas import Index, Series, DataFrame
 
 from pandas.tseries.index import date_range, bdate_range
+from pandas.tseries.tdi import timedelta_range
 from pandas.tseries.offsets import DateOffset
 from pandas.tseries.period import period_range, Period, PeriodIndex
 from pandas.tseries.resample import DatetimeIndex
@@ -1271,6 +1272,63 @@ def test_plot_outofbounds_datetime(self):
         values = [datetime(1677, 1, 1, 12), datetime(1677, 1, 2, 12)]
         self.plt.plot(values)
 
+    def test_format_timedelta_ticks_narrow(self):
+
+        expected_labels = [
+            '00:00:00.00000000{:d}'.format(i)
+            for i in range(10)]
+
+        rng = timedelta_range('0', periods=10, freq='ns')
+        df = DataFrame(np.random.randn(len(rng), 3), rng)
+        ax = df.plot(fontsize=2)
+        fig = ax.get_figure()
+        fig.canvas.draw()
+        labels = ax.get_xticklabels()
+        self.assertEqual(len(labels), len(expected_labels))
+        for l, l_expected in zip(labels, expected_labels):
+            self.assertEqual(l.get_text(), l_expected)
+
+    def test_format_timedelta_ticks_wide(self):
+
+        expected_labels = [
+            '00:00:00',
+            '1 days 03:46:40',
+            '2 days 07:33:20',
+            '3 days 11:20:00',
+            '4 days 15:06:40',
+            '5 days 18:53:20',
+            '6 days 22:40:00',
+            '8 days 02:26:40',
+            ''
+        ]
+
+        rng = timedelta_range('0', periods=10, freq='1 d')
+        df = DataFrame(np.random.randn(len(rng), 3), rng)
+        ax = df.plot(fontsize=2)
+        fig = ax.get_figure()
+        fig.canvas.draw()
+        labels = ax.get_xticklabels()
+        self.assertEqual(len(labels), len(expected_labels))
+        for l, l_expected in zip(labels, expected_labels):
+            self.assertEqual(l.get_text(), l_expected)
+
+    def test_timedelta_plot(self):
+        # test issue #8711
+        s = Series(range(5), timedelta_range('1day', periods=5))
+        _check_plot_works(s.plot)
+
+        # test long period
+        index = timedelta_range('1 day 2 hr 30 min 10 s',
+                                periods=10, freq='1 d')
+        s = Series(np.random.randn(len(index)), index)
+        _check_plot_works(s.plot)
+
+        # test short period
+        index = timedelta_range('1 day 2 hr 30 min 10 s',
+                                periods=10, freq='1 ns')
+        s = Series(np.random.randn(len(index)), index)
+        _check_plot_works(s.plot)
+
 
 def _check_plot_works(f, freq=None, series=None, *args, **kwargs):
     import matplotlib.pyplot as plt

pandas/tools/plotting.py

@@ -1780,7 +1780,7 @@ def _ts_plot(cls, ax, x, data, style=None, **kwds):
 
         lines = cls._plot(ax, data.index, data.values, style=style, **kwds)
         # set date formatter, locators and rescale limits
-        format_dateaxis(ax, ax.freq)
+        format_dateaxis(ax, ax.freq, data.index)
         return lines
 
     def _get_stacking_id(self):

pandas/tseries/plotting.py

@@ -12,6 +12,8 @@
 from pandas.tseries.offsets import DateOffset
 import pandas.tseries.frequencies as frequencies
 from pandas.tseries.index import DatetimeIndex
+from pandas.tseries.period import PeriodIndex
+from pandas.tseries.tdi import TimedeltaIndex
 from pandas.formats.printing import pprint_thing
 import pandas.compat as compat
 
@@ -49,7 +51,7 @@ def tsplot(series, plotf, ax=None, **kwargs):
     lines = plotf(ax, series.index._mpl_repr(), series.values, **kwargs)
 
     # set date formatter, locators and rescale limits
-    format_dateaxis(ax, ax.freq)
+    format_dateaxis(ax, ax.freq, series.index)
     return lines
 
 
@@ -278,8 +280,22 @@ def _maybe_convert_index(ax, data):
 # Patch methods for subplot. Only format_dateaxis is currently used.
 # Do we need the rest for convenience?
 
-
-def format_dateaxis(subplot, freq):
+def format_timedelta_ticks(x, pos, n_decimals):
+    ''' Convert seconds to 'D days HH:MM:SS.F' '''
+    s, ns = divmod(x, 1e9)
+    m, s = divmod(s, 60)
+    h, m = divmod(m, 60)
+    d, h = divmod(h, 24)
+    decimals = int(ns * 10**(n_decimals - 9))
+    s = r'{:02d}:{:02d}:{:02d}'.format(int(h), int(m), int(s))
+    if n_decimals > 0:
+        s += '.{{:0{:0d}d}}'.format(n_decimals).format(decimals)
+    if d != 0:
+        s = '{:d} days '.format(int(d)) + s
+    return s
+
+
+def format_dateaxis(subplot, freq, index):
     """
     Pretty-formats the date axis (x-axis).
 
@@ -288,26 +304,44 @@ def format_dateaxis(subplot, freq):
     default, changing the limits of the x axis will intelligently change
     the positions of the ticks.
     """
-    majlocator = TimeSeries_DateLocator(freq, dynamic_mode=True,
-                                        minor_locator=False,
-                                        plot_obj=subplot)
-    minlocator = TimeSeries_DateLocator(freq, dynamic_mode=True,
-                                        minor_locator=True,
-                                        plot_obj=subplot)
-    subplot.xaxis.set_major_locator(majlocator)
-    subplot.xaxis.set_minor_locator(minlocator)
-
-    majformatter = TimeSeries_DateFormatter(freq, dynamic_mode=True,
+
+    # handle index specific formatting
+    # Note: DatetimeIndex does not use this
+    # interface. DatetimeIndex uses matplotlib.date directly
+    if isinstance(index, PeriodIndex):
+
+        majlocator = TimeSeries_DateLocator(freq, dynamic_mode=True,
                                             minor_locator=False,
                                             plot_obj=subplot)
-    minformatter = TimeSeries_DateFormatter(freq, dynamic_mode=True,
+        minlocator = TimeSeries_DateLocator(freq, dynamic_mode=True,
                                             minor_locator=True,
                                             plot_obj=subplot)
-    subplot.xaxis.set_major_formatter(majformatter)
-    subplot.xaxis.set_minor_formatter(minformatter)
-
-    # x and y coord info
-    subplot.format_coord = lambda t, y: (
-        "t = {0}  y = {1:8f}".format(Period(ordinal=int(t), freq=freq), y))
+        subplot.xaxis.set_major_locator(majlocator)
+        subplot.xaxis.set_minor_locator(minlocator)
+
+        majformatter = TimeSeries_DateFormatter(freq, dynamic_mode=True,
+                                                minor_locator=False,
+                                                plot_obj=subplot)
+        minformatter = TimeSeries_DateFormatter(freq, dynamic_mode=True,
+                                                minor_locator=True,
+                                                plot_obj=subplot)
+        subplot.xaxis.set_major_formatter(majformatter)
+        subplot.xaxis.set_minor_formatter(minformatter)
+
+        # x and y coord info
+        subplot.format_coord = lambda t, y: (
+            "t = {0}  y = {1:8f}".format(Period(ordinal=int(t), freq=freq), y))
+
+    elif isinstance(index, TimedeltaIndex):
+        from matplotlib import ticker
+        (vmin, vmax) = tuple(subplot.xaxis.get_view_interval())
+        n_decimals = int(np.ceil(np.log10(100 * 1e9 / (vmax - vmin))))
+        if n_decimals > 9:
+            n_decimals = 9
+        formatter = ticker.FuncFormatter(
+            lambda x, pos: format_timedelta_ticks(x, pos, n_decimals))
+        subplot.xaxis.set_major_formatter(formatter)
+    else:
+        raise IOError('index type not supported')
 
     pylab.draw_if_interactive()