def quarter_plot(x, dates=None, ylabel=None, ax=None):
"""
Seasonal plot of quarterly data
Parameters
----------
x : array-like
Seasonal data to plot. If dates is None, x must be a pandas object
with a PeriodIndex or DatetimeIndex with a monthly frequency.
dates : array-like, optional
If `x` is not a pandas object, then dates must be supplied.
ylabel : str, optional
The label for the y-axis. Will attempt to use the `name` attribute
of the Series.
ax : matplotlib.axes, optional
Existing axes instance.
Returns
-------
matplotlib.Figure
"""
from pandas import DataFrame
if dates is None:
from statsmodels.tools.data import _check_period_index
_check_period_index(x, freq="Q")
else:
from pandas import Series, PeriodIndex
x = Series(x, index=PeriodIndex(dates, freq="Q"))
xticklabels = ['q1', 'q2', 'q3', 'q4']
return seasonal_plot(x.groupby(lambda y: y.quarter),
xticklabels,
ylabel=ylabel,
ax=ax)
def quarter_plot(x, dates=None, ylabel=None, ax=None):
"""
Seasonal plot of quarterly data
Parameters
----------
x : array-like
Seasonal data to plot. If dates is None, x must be a pandas object
with a PeriodIndex or DatetimeIndex with a monthly frequency.
dates : array-like, optional
If `x` is not a pandas object, then dates must be supplied.
ylabel : str, optional
The label for the y-axis. Will attempt to use the `name` attribute
of the Series.
ax : matplotlib.axes, optional
Existing axes instance.
Returns
-------
matplotlib.Figure
"""
from pandas import DataFrame
if dates is None:
from statsmodels.tools.data import _check_period_index
_check_period_index(x, freq="Q")
else:
from pandas import Series, PeriodIndex
x = Series(x, index=PeriodIndex(dates, freq="Q"))
xticklabels = ['q1', 'q2', 'q3', 'q4']
return seasonal_plot(x.groupby(lambda y : y.quarter), xticklabels,
ylabel=ylabel, ax=ax)
def month_plot(x, dates=None, ylabel=None, ax=None):
"""
Seasonal plot of monthly data.
Parameters
----------
x : array_like
Seasonal data to plot. If dates is None, x must be a pandas object
with a PeriodIndex or DatetimeIndex with a monthly frequency.
dates : array_like, optional
If `x` is not a pandas object, then dates must be supplied.
ylabel : str, optional
The label for the y-axis. Will attempt to use the `name` attribute
of the Series.
ax : Axes, optional
Existing axes instance.
Returns
-------
Figure
If `ax` is provided, the Figure instance attached to `ax`. Otherwise
a new Figure instance.
Examples
--------
>>> import statsmodels.api as sm
>>> import pandas as pd
>>> dta = sm.datasets.elnino.load_pandas().data
>>> dta['YEAR'] = dta.YEAR.astype(int).astype(str)
>>> dta = dta.set_index('YEAR').T.unstack()
>>> dates = pd.to_datetime(list(map(lambda x: '-'.join(x) + '-1',
... dta.index.values)))
>>> dta.index = pd.DatetimeIndex(dates, freq='MS')
>>> fig = sm.graphics.tsa.month_plot(dta)
.. plot:: plots/graphics_tsa_month_plot.py
"""
if dates is None:
from statsmodels.tools.data import _check_period_index
_check_period_index(x, freq="M")
else:
x = pd.Series(x, index=pd.PeriodIndex(dates, freq="M"))
# there's no zero month
xticklabels = list(calendar.month_abbr)[1:]
return seasonal_plot(x.groupby(lambda y: y.month),
xticklabels,
ylabel=ylabel,
ax=ax)
def month_plot(x, dates=None, ylabel=None, ax=None):
"""
Seasonal plot of monthly data
Parameters
----------
x : array-like
Seasonal data to plot. If dates is None, x must be a pandas object
with a PeriodIndex or DatetimeIndex with a monthly frequency.
dates : array-like, optional
If `x` is not a pandas object, then dates must be supplied.
ylabel : str, optional
The label for the y-axis. Will attempt to use the `name` attribute
of the Series.
ax : matplotlib.axes, optional
Existing axes instance.
Returns
-------
matplotlib.Figure
Examples
--------
>>> import statsmodels.api as sm
>>> import pandas as pd
>>> dta = sm.datasets.elnino.load_pandas().data
>>> dta['YEAR'] = dta.YEAR.astype(int).astype(str)
>>> dta = dta.set_index('YEAR').T.unstack()
>>> dates = pd.to_datetime(list(map(lambda x : '-'.join(x) + '-1',
... dta.index.values)))
>>> dta.index = pd.DatetimeIndex(dates, freq='M')
>>> fig = sm.graphics.tsa.month_plot(dta)
.. plot:: plots/graphics_month_plot.py
"""
from pandas import DataFrame
if dates is None:
from statsmodels.tools.data import _check_period_index
_check_period_index(x, freq="M")
else:
from pandas import Series, PeriodIndex
x = Series(x, index=PeriodIndex(dates, freq="M"))
xticklabels = ['j', 'f', 'm', 'a', 'm', 'j', 'j', 'a', 's', 'o', 'n', 'd']
return seasonal_plot(x.groupby(lambda y: y.month),
xticklabels,
ylabel=ylabel,
ax=ax)
def month_plot(x, dates=None, ylabel=None, ax=None):
"""
Seasonal plot of monthly data
Parameters
----------
x : array-like
Seasonal data to plot. If dates is None, x must be a pandas object
with a PeriodIndex or DatetimeIndex with a monthly frequency.
dates : array-like, optional
If `x` is not a pandas object, then dates must be supplied.
ylabel : str, optional
The label for the y-axis. Will attempt to use the `name` attribute
of the Series.
ax : matplotlib.axes, optional
Existing axes instance.
Returns
-------
matplotlib.Figure
Examples
--------
>>> import statsmodels.api as sm
>>> import pandas as pd
>>> dta = sm.datasets.elnino.load_pandas().data
>>> dta['YEAR'] = dta.YEAR.astype(int).astype(str)
>>> dta = dta.set_index('YEAR').T.unstack()
>>> dates = map(lambda x : pd.datetools.parse_time_string('1 '+' '.join(x)),
... dta.index.values)
>>> dta.index = pd.DatetimeIndex(dates, freq='M')
>>> fig = sm.graphics.tsa.month_plot(dta)
.. plot:: plots/graphics_month_plot.py
"""
from pandas import DataFrame
if dates is None:
from statsmodels.tools.data import _check_period_index
_check_period_index(x, freq="M")
else:
from pandas import Series, PeriodIndex
x = Series(x, index=PeriodIndex(dates, freq="M"))
xticklabels = ["j", "f", "m", "a", "m", "j", "j", "a", "s", "o", "n", "d"]
return seasonal_plot(x.groupby(lambda y: y.month), xticklabels, ylabel=ylabel, ax=ax)
def quarter_plot(x, dates=None, ylabel=None, ax=None):
"""
Seasonal plot of quarterly data
Parameters
----------
x : array-like
Seasonal data to plot. If dates is None, x must be a pandas object
with a PeriodIndex or DatetimeIndex with a monthly frequency.
dates : array-like, optional
If `x` is not a pandas object, then dates must be supplied.
ylabel : str, optional
The label for the y-axis. Will attempt to use the `name` attribute
of the Series.
ax : matplotlib.axes, optional
Existing axes instance.
Returns
-------
matplotlib.Figure
Examples
--------
>>> import statsmodels.api as sm
>>> import pandas as pd
>>> dta = sm.datasets.elnino.load_pandas().data
>>> dta['YEAR'] = dta.YEAR.astype(int).astype(str)
>>> dta = dta.set_index('YEAR').T.unstack()
>>> dates = pd.to_datetime(list(map(lambda x: '-'.join(x) + '-1',
... dta.index.values)))
>>> dta.index = dates.to_period('Q')
>>> fig = sm.graphics.tsa.quarter_plot(dta)
.. plot:: plots/graphics_tsa_quarter_plot.py
"""
if dates is None:
from statsmodels.tools.data import _check_period_index
_check_period_index(x, freq="Q")
else:
from pandas import Series, PeriodIndex
x = Series(x, index=PeriodIndex(dates, freq="Q"))
xticklabels = ['q1', 'q2', 'q3', 'q4']
return seasonal_plot(x.groupby(lambda y: y.quarter), xticklabels,
ylabel=ylabel, ax=ax)