if fontsize is not None:
ax.tick_params(axis="both", labelsize=fontsize)
if kwds.get("vert", 1):
+ ticks = ax.get_xticks()
+ if len(ticks) != len(keys):
+ i, remainder = divmod(len(ticks), len(keys))
+ assert remainder == 0, remainder
+ keys *= i
ax.set_xticklabels(keys, rotation=rot)
else:
ax.set_yticklabels(keys, rotation=rot)
_mpl_ge_2_2_3 = _mpl_version("2.2.3", operator.ge)
_mpl_ge_3_0_0 = _mpl_version("3.0.0", operator.ge)
_mpl_ge_3_1_0 = _mpl_version("3.1.0", operator.ge)
+_mpl_ge_3_3_0 = _mpl_version("3.3.0", operator.ge)
from pandas._libs.tslibs.frequencies import FreqGroup, get_freq
from pandas.core.dtypes.common import (
- is_datetime64_ns_dtype,
is_float,
is_float_dtype,
is_integer,
raise ValueError("Unrecognizable date '{date}'".format(date=date))
-def _dt_to_float_ordinal(dt):
- """
- Convert :mod:`datetime` to the Gregorian date as UTC float days,
- preserving hours, minutes, seconds and microseconds. Return value
- is a :func:`float`.
- """
- if isinstance(dt, (np.ndarray, Index, ABCSeries)) and is_datetime64_ns_dtype(dt):
- base = dates.epoch2num(dt.asi8 / 1.0e9)
- else:
- base = dates.date2num(dt)
- return base
-
-
# Datetime Conversion
class DatetimeConverter(dates.DateConverter):
@staticmethod
def _convert_1d(values, unit, axis):
def try_parse(values):
try:
- return _dt_to_float_ordinal(tools.to_datetime(values))
+ return dates.date2num(tools.to_datetime(values))
except Exception:
return values
- if isinstance(values, (datetime, pydt.date)):
- return _dt_to_float_ordinal(values)
- elif isinstance(values, np.datetime64):
- return _dt_to_float_ordinal(tslibs.Timestamp(values))
- elif isinstance(values, pydt.time):
+ if isinstance(values, (datetime, pydt.date, np.datetime64, pydt.time)):
return dates.date2num(values)
elif is_integer(values) or is_float(values):
return values
try:
values = tools.to_datetime(values)
- if isinstance(values, Index):
- values = _dt_to_float_ordinal(values)
- else:
- values = [_dt_to_float_ordinal(x) for x in values]
except Exception:
- values = _dt_to_float_ordinal(values)
+ pass
+
+ values = dates.date2num(values)
return values
freq = "%dL" % self._get_interval()
tz = self.tz.tzname(None)
- st = _from_ordinal(dates.date2num(dmin)) # strip tz
- ed = _from_ordinal(dates.date2num(dmax))
+ st = dmin.replace(tzinfo=None)
+ ed = dmin.replace(tzinfo=None)
all_dates = date_range(start=st, end=ed, freq=freq, tz=tz).astype(object)
try:
pass
pytest.importorskip("matplotlib.pyplot")
+dates = pytest.importorskip("matplotlib.dates")
def test_initial_warning():
def test_conversion(self):
rs = self.dtc.convert(["2012-1-1"], None, None)[0]
- xp = datetime(2012, 1, 1).toordinal()
+ xp = dates.date2num(datetime(2012, 1, 1))
assert rs == xp
rs = self.dtc.convert("2012-1-1", None, None)
rs = self.dtc.convert(date(2012, 1, 1), None, None)
assert rs == xp
- rs = self.dtc.convert(datetime(2012, 1, 1).toordinal(), None, None)
- assert rs == xp
-
rs = self.dtc.convert("2012-1-1", None, None)
assert rs == xp
bts = tm.makePeriodSeries()
_, ax = self.plt.subplots()
bts.plot(ax=ax)
- assert ax.get_lines()[0].get_xydata()[0, 0] == bts.index[0].ordinal
+
idx = ax.get_lines()[0].get_xdata()
assert PeriodIndex(data=idx).freqstr == "B"
@pytest.mark.slow
def test_irregular_ts_shared_ax_xlim(self):
# GH 2960
+ from pandas.plotting._matplotlib.converter import DatetimeConverter
+
ts = tm.makeTimeSeries()[:20]
ts_irregular = ts[[1, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 17, 18]]
# check that axis limits are correct
left, right = ax.get_xlim()
- assert left <= ts_irregular.index.min().toordinal()
- assert right >= ts_irregular.index.max().toordinal()
+ assert left <= DatetimeConverter.convert(ts_irregular.index.min(), "", ax)
+ assert right >= DatetimeConverter.convert(ts_irregular.index.max(), "", ax)
@pytest.mark.slow
def test_secondary_y_non_ts_xlim(self):
@pytest.mark.slow
def test_secondary_y_irregular_ts_xlim(self):
# GH 3490 - irregular-timeseries with secondary y
+ from pandas.plotting._matplotlib.converter import DatetimeConverter
+
ts = tm.makeTimeSeries()[:20]
ts_irregular = ts[[1, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 17, 18]]
ts_irregular[:5].plot(ax=ax)
left, right = ax.get_xlim()
- assert left <= ts_irregular.index.min().toordinal()
- assert right >= ts_irregular.index.max().toordinal()
+ assert left <= DatetimeConverter.convert(ts_irregular.index.min(), "", ax)
+ assert right >= DatetimeConverter.convert(ts_irregular.index.max(), "", ax)
def test_plot_outofbounds_datetime(self):
# 2579 - checking this does not raise
s2.plot(ax=ax)
s1.plot(ax=ax)
- @pytest.mark.xfail(reason="GH9053 matplotlib does not use ax.xaxis.converter")
+ @pytest.mark.xfail(reason="GH9053 matplotlib does not use ax.xaxis.converter", strict=False)
def test_add_matplotlib_datetime64(self):
# GH9053 - ensure that a plot with PeriodConverter still understands
# datetime64 data. This still fails because matplotlib overrides the
ax.xaxis.get_ticklocs(), np.arange(1, len(numeric_cols) + 1)
)
assert len(ax.lines) == self.bp_n_objects * len(numeric_cols)
+ tm.close()
axes = series.plot.box(rot=40)
self._check_ticks_props(axes, xrot=40, yrot=0)
self._check_ticks_props(axes, xrot=30)
def test_irregular_datetime(self):
+ from pandas.plotting._matplotlib.converter import DatetimeConverter
+
rng = date_range("1/1/2000", "3/1/2000")
rng = rng[[0, 1, 2, 3, 5, 9, 10, 11, 12]]
ser = Series(randn(len(rng)), rng)
_, ax = self.plt.subplots()
ax = ser.plot(ax=ax)
- xp = datetime(1999, 1, 1).toordinal()
+ xp = DatetimeConverter.convert(datetime(1999, 1, 1), "", ax)
ax.set_xlim("1/1/1999", "1/1/2001")
assert xp == ax.get_xlim()[0]
kinds = (
plotting.PlotAccessor._common_kinds + plotting.PlotAccessor._series_kinds
)
- _, ax = self.plt.subplots()
for kind in kinds:
-
+ _, ax = self.plt.subplots()
s.plot(kind=kind, ax=ax)
+ self.plt.close()
+ _, ax = self.plt.subplots()
getattr(s.plot, kind)()
+ self.plt.close()
@pytest.mark.slow
def test_invalid_plot_data(self):
def _skip_if_no_mpl():
mod = safe_import("matplotlib")
if mod:
- mod.use("Agg", warn=True)
+ mod.use("Agg")
else:
return True
projects / pandas.git / commitdiff