def _most_recent_convictions(recent_convictions) -> Optional[Charge]:
recent_convictions.sort(key=lambda charge: charge.disposition.date, reverse=True)
newer, older = take(2, padnone(recent_convictions))
if newer and "violation" in newer.level.lower():
return older
else:
return newer
def _most_recent_convictions(recent_convictions):
recent_convictions.sort(key=lambda charge: charge.disposition.date,
reverse=True)
first, second, third = take(3, padnone(recent_convictions))
if first and "violation" in first.level.lower():
return second, third
elif second and "violation" in second.level.lower():
return first, third
else:
return first, second
def plot_dataframe(axs,
df: pd.DataFrame,
x: Optional = None,
y: Optional[Iterable] = None,
style: Optional[Iterable] = None,
stacked=False,
kind="line"):
# for some reason df.plot() completely ruins datetime xaxis so no other formatter works
# reinvent the wheel...
if x is None:
xvals = df.index.values
elif isinstance(x, str):
xvals = df[x].values
else:
xvals = x
if y is None:
yvals = df
else:
yvals = df.loc[:, y]
if style is None:
style = []
if stacked:
yvals_original = yvals.copy()
yvals = yvals.cumsum(axis=1)
if kind == "bar":
styler = iter(
cycler.cycler(hatch=[None, "///", "..."]) *
mpl.rcParams["axes.prop_cycle"])
cols = yvals.columns
styletup = [(st, ) if st else ()
for st in islice(padnone(iter(style)), len(cols))]
for st, ci in zip(styletup, cols):
if kind == "line":
axs.plot(xvals, yvals[ci], *st, label=ci)
elif kind == "bar":
if stacked:
bot = (yvals[ci] - yvals_original[ci]).to_numpy()
bot[np.isnan(bot)] = 0.0
what = dict(height=yvals_original[ci], bottom=bot)
else:
what = dict(height=yvals[ci])
axs.bar(xvals,
**what,
linewidth=0,
width=-1.0,
align="edge",
**next(styler),
label=ci)
axs.legend()
def test_happy_path(self):
"""wrapper iterator should return None indefinitely"""
r = range(2)
p = mi.padnone(r)
self.assertEqual([0, 1, None, None], [next(p) for _ in range(4)])
def test_happy_path(self):
"""wrapper iterator should return None indefinitely"""
r = range(2)
p = mi.padnone(r)
self.assertEqual([0, 1, None, None], [next(p) for _ in range(4)])
