def test_groupby_categorical_unequal_len(self):
# GH3011
series = Series([np.nan, np.nan, 1, 1, 2, 2, 3, 3, 4, 4])
# The raises only happens with categorical, not with series of types
# category
bins = pd.cut(series.dropna().values, 4)
# len(bins) != len(series) here
self.assertRaises(ValueError, lambda: series.groupby(bins).mean())
def test_groupby_categorical_unequal_len(self):
# GH3011
series = Series([np.nan, np.nan, 1, 1, 2, 2, 3, 3, 4, 4])
# The raises only happens with categorical, not with series of types
# category
bins = pd.cut(series.dropna().values, 4)
# len(bins) != len(series) here
self.assertRaises(ValueError, lambda: series.groupby(bins).mean())
def tsplot(series, plotf, *args, **kwargs):
"""
Plots a Series on the given Matplotlib axes object
Parameters
----------
axes : Axes
series : Series
Notes
_____
Supports same args and kwargs as Axes.plot
"""
# Used inferred freq is possible, need a test case for inferred
freq = getattr(series.index, 'freq', None)
if freq is None and hasattr(series.index, 'inferred_freq'):
freq = series.index.inferred_freq
if isinstance(freq, DateOffset):
freq = freq.rule_code
freq = frequencies.to_calendar_freq(freq)
# Convert DatetimeIndex to PeriodIndex
if isinstance(series.index, DatetimeIndex):
idx = series.index.to_period(freq=freq)
series = Series(series.values, idx, name=series.name)
if not isinstance(series.index, PeriodIndex):
#try to get it to DatetimeIndex then to period
if series.index.inferred_type == 'datetime':
idx = DatetimeIndex(series.index).to_period(freq=freq)
series = Series(series.values, idx, name=series.name)
else:
raise TypeError('series argument to tsplot must have '
'DatetimeIndex or PeriodIndex')
if freq != series.index.freq:
series = series.asfreq(freq)
series = series.dropna()
if 'ax' in kwargs:
ax = kwargs.pop('ax')
else:
ax = plt.gca()
# Specialized ts plotting attributes for Axes
ax.freq = freq
xaxis = ax.get_xaxis()
xaxis.freq = freq
xaxis.converter = DateConverter
ax.legendlabels = [kwargs.get('label', None)]
ax.view_interval = None
ax.date_axis_info = None
# format args and lot
args = _check_plot_params(series, series.index, freq, *args)
plotted = plotf(ax, *args, **kwargs)
format_dateaxis(ax, ax.freq)
# when adding a right axis (using add_yaxis), for some reason the
# x axis limits don't get properly set. This gets around the problem
xlim = ax.get_xlim()
if xlim[0] == 0.0 and xlim[1] == 1.0:
# if xlim still at default values, autoscale the axis
ax.autoscale_view()
left = series.index[0] #get_datevalue(series.index[0], freq)
right = series.index[-1] #get_datevalue(series.index[-1], freq)
ax.set_xlim(left, right)
return plotted
def tsplot(series, plotf, *args, **kwargs):
"""
Plots a Series on the given Matplotlib axes object
Parameters
----------
axes : Axes
series : Series
Notes
_____
Supports same args and kwargs as Axes.plot
"""
# Used inferred freq is possible, need a test case for inferred
freq = getattr(series.index, 'freq', None)
if freq is None and hasattr(series.index, 'inferred_freq'):
freq = series.index.inferred_freq
if isinstance(freq, DateOffset):
freq = freq.rule_code
else:
freq = frequencies.get_base_alias(freq)
freq = frequencies.to_calendar_freq(freq)
# Convert DatetimeIndex to PeriodIndex
if isinstance(series.index, DatetimeIndex):
idx = series.index.to_period(freq=freq)
series = Series(series.values, idx, name=series.name)
if not isinstance(series.index, PeriodIndex):
#try to get it to DatetimeIndex then to period
if series.index.inferred_type == 'datetime':
idx = DatetimeIndex(series.index).to_period(freq=freq)
series = Series(series.values, idx, name=series.name)
else:
raise TypeError('series argument to tsplot must have '
'DatetimeIndex or PeriodIndex')
if freq != series.index.freq:
series = series.asfreq(freq)
series = series.dropna()
style = kwargs.pop('style', None)
if 'ax' in kwargs:
ax = kwargs.pop('ax')
else:
ax = plt.gca()
# Specialized ts plotting attributes for Axes
ax.freq = freq
xaxis = ax.get_xaxis()
xaxis.freq = freq
xaxis.converter = DateConverter
ax.legendlabels = [kwargs.get('label', None)]
ax.view_interval = None
ax.date_axis_info = None
# format args and lot
args = _check_plot_params(series, series.index, freq, style, *args)
plotted = plotf(ax, *args, **kwargs)
format_dateaxis(ax, ax.freq)
# when adding a right axis (using add_yaxis), for some reason the
# x axis limits don't get properly set. This gets around the problem
xlim = ax.get_xlim()
if xlim[0] == 0.0 and xlim[1] == 1.0:
# if xlim still at default values, autoscale the axis
ax.autoscale_view()
left = series.index[0] #get_datevalue(series.index[0], freq)
right = series.index[-1] #get_datevalue(series.index[-1], freq)
ax.set_xlim(left, right)
return plotted