def violin_plot_pandas(bin_vec,
real_vec,
ann='p',
order=None,
ax=None,
filename=None):
"""
http://pyinsci.blogspot.com/2009/09/violin-plot-with-matplotlib.html
Wrapper around matplotlib's boxplot function to add violin profile.
Inputs
bin_vec: Series of labels
real_vec: Series of measurements to be grouped according to bin_vec
"""
fig, ax = init_ax(ax)
ax.set_ylabel(real_vec.name)
ax.set_xlabel(bin_vec.name)
bin_vec, real_vec = match_series(bin_vec, real_vec)
try:
if order is None:
categories = bin_vec.value_counts().index
else:
categories = order
_violin_plot(ax, [real_vec[bin_vec == num] for num in categories],
pos=categories,
bp=True)
ax.set_xticklabels(
[str(c) + '\n(n=%i)' % sum(bin_vec == c) for c in categories])
except:
box_plot_pandas(bin_vec, real_vec, ax=ax)
#if type(bin_vec.name) == str:
# ax.set_title(str(bin_vec.name) + ' x ' + str(real_vec.name))
p_value = Stats.kruskal_pandas(bin_vec, real_vec)['p']
if ann == 'p_fancy':
ax.annotate('$p = {}$'.format(latex_float(p_value)), (.95, -.02),
xycoords='axes fraction',
ha='right',
va='bottom',
size=14)
if ann == 'p':
ax.annotate('p = {0:.1e}'.format(p_value), (.95, .02),
xycoords='axes fraction',
ha='right',
va='bottom',
size=12)
elif ann is not None:
ax.annotate(ann, (.95, .02),
xycoords='axes fraction',
ha='right',
va='bottom',
size=12)
if filename is not None:
fig.savefig(filename)
return
def violin_plot_pandas(bin_vec, real_vec, ann='p', order=None, ax=None,
filename=None):
"""
http://pyinsci.blogspot.com/2009/09/violin-plot-with-matplotlib.html
Wrapper around matplotlib's boxplot function to add violin profile.
Inputs
bin_vec: Series of labels
real_vec: Series of measurements to be grouped according to bin_vec
"""
fig, ax = init_ax(ax)
ax.set_ylabel(real_vec.name)
ax.set_xlabel(bin_vec.name)
bin_vec, real_vec = match_series(bin_vec, real_vec)
try:
if order is None:
categories = bin_vec.value_counts().index
else:
categories = order
_violin_plot(ax, [real_vec[bin_vec == num] for num in categories],
pos=categories, bp=True)
ax.set_xticklabels([str(c) + '\n(n=%i)' % sum(bin_vec == c)
for c in categories])
except:
box_plot_pandas(bin_vec, real_vec, ax=ax)
#if type(bin_vec.name) == str:
# ax.set_title(str(bin_vec.name) + ' x ' + str(real_vec.name))
p_value = Stats.kruskal_pandas(bin_vec, real_vec)['p']
if ann == 'p_fancy':
ax.annotate('$p = {}$'.format(latex_float(p_value)), (.95, -.02),
xycoords='axes fraction', ha='right', va='bottom', size=14)
if ann == 'p':
ax.annotate('p = {0:.1e}'.format(p_value), (.95, .02),
xycoords='axes fraction', ha='right', va='bottom', size=12)
elif ann is not None:
ax.annotate(ann, (.95, .02), xycoords='axes fraction', ha='right',
va='bottom', size=12)
if filename is not None:
fig.savefig(filename)
return
