import matplotlib.pyplot as plt
from w_helpers import load_data, aggregate_by_month
plt.ion()
temperature = load_data('mdw')
temperature_monthly = aggregate_by_month(temperature)
fig, ax = plt.subplots()
def plot_aggregated_errorbar(ax, gb, label, picker=None, **kwargs):
kwargs.setdefault('capsize', 3)
kwargs.setdefault('markersize', 5)
kwargs.setdefault('marker', 'o')
eb = ax.errorbar(gb.index,
'mean',
yerr='std',
data=gb,
label=label,
picker=picker,
**kwargs)
fill = ax.fill_between(gb.index,
'min',
'max',
alpha=.5,
data=gb,
color=eb[0].get_color())
ax.legend()
ax.figure.canvas.draw_idle()
return eb, fill
import matplotlib.pyplot as plt
from w_helpers import load_bwi_data, aggregate_by_month
plt.ion()
bwi = load_bwi_data()
bwi_monthly = aggregate_by_month(bwi)
fig, ax = plt.subplots()
def plot_aggregated_errorbar(ax, gb, label, picker=None, **kwargs):
kwargs.setdefault('capsize', 3)
kwargs.setdefault('markersize', 5)
kwargs.setdefault('marker', 'o')
eb = ax.errorbar(gb.index, 'mean',
yerr='std',
data=gb,
label=label,
picker=picker,
**kwargs)
fill = ax.fill_between(gb.index, 'min', 'max', alpha=.5,
data=gb, color=eb[0].get_color())
ax.legend()
ax.figure.canvas.draw_idle()
return eb, fill
arts = plot_aggregated_errorbar(ax, bwi_monthly, 'bwi')
# EXERCISE
# - make the shaded area configurable
def __init__(self,
hourly_data,
label,
yearly_ax,
monthly_ax,
daily_ax,
agg_by_day=None,
agg_by_month=None,
style_cycle=None):
'''Class to manage 3-levels of aggregated temperature
Parameters
----------
hourly_data : DataFrame
Tempreture measured hourly
label : str
The name of this data set_a
yearly_ax : Axes
The axes to plot 'year' scale data (aggregated by month) to
monthly_ax : Axes
The axes to plot 'month' scale data (aggregated by day) to
daily_ax : Axes
The axes to plot 'day' scale data (un-aggregated hourly) to
agg_by_day : DataFrame, optional
Data already aggregated by day. This is just to save
computation, will be computed if not provided.
agg_by_month : DataFrame, optional
Data already aggregated by month. This is just to save
computation, will be computed if not provided.
style_cycle : Cycler, optional
Style to use for plotting
'''
# data
self.data_by_hour = hourly_data
if agg_by_day is None:
agg_by_day = aggregate_by_day(hourly_data)
self.data_by_day = agg_by_day
if agg_by_month is None:
agg_by_month = aggregate_by_month(hourly_data)
self.data_by_month = agg_by_month
# style
if style_cycle is None:
style_cycle = (
(cycler('marker',
['o', 's', '^', '*', 'x', 'v', '8', 'D', 'H', '<']) +
cycler('color', [
'#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd',
'#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'
])))
self.style_cycle = style_cycle()
# axes
self.yearly_ax = yearly_ax
self.monthly_ax = monthly_ax
self.daily_ax = daily_ax
# name
self.label = label
# these will be used for book keeping
self.daily_artists = {}
self.daily_index = {}
self.hourly_artiists = {}
# artists
self.yearly_art = plot_aggregated_errorbar(self.yearly_ax,
self.data_by_month,
self.label,
picker=5,
**next(self.style_cycle))
# pick methods
self.y_cid = self.yearly_ax.figure.canvas.mpl_connect(
'pick_event', self._yearly_on_pick)
self.y_cid = self.yearly_ax.figure.canvas.mpl_connect(
'pick_event', self._monthly_on_pick)
self.y_cid = self.yearly_ax.figure.canvas.mpl_connect(
'pick_event', self._daily_on_pick)