def test_two_column_index(self, params, dataframe, caplog):
gdf = dataframe[columns[:2] + ['firing_rate']].groupby(
columns[:2]).sum()
if 'hue' in params:
plot_grouped_dataframe(gdf, metrics='firing_rate', **params)
assert hue_ignored_warning in caplog.text
else:
plot_grouped_dataframe(gdf, metrics='firing_rate', **params)
import matplotlib.pyplot as plt
import seaborn as sns
from gdfplot.core import plot_grouped_dataframe
dots = sns.load_dataset('dots')
dots = dots.loc[(dots['time'] >= 0) & (dots['time'] <= 50)]
g2 = dots[['align', 'choice', 'firing_rate']].groupby(['align',
'choice']).sum()
plot_grouped_dataframe(g2,
metrics='firing_rate',
hue='align',
h_subplots='choice')
plt.show()
def test_one_column_index(self, params, dataframe):
gdf = dataframe[columns[:1] + ['firing_rate']].groupby(
columns[:1]).sum()
plot_grouped_dataframe(gdf, metrics='firing_rate', **params)
def test_two_column_index(self, params, dataframe):
gdf = dataframe[columns[:2] + ['firing_rate']].groupby(
columns[:2]).sum()
with pytest.raises(ColumnNameNotInIndex):
plot_grouped_dataframe(gdf, metrics='firing_rate', **params)
def test_three_column_index(self, params, dataframe, caplog):
gdf = dataframe[columns + ['firing_rate']].groupby(columns).sum()
plot_grouped_dataframe(gdf, metrics='firing_rate', **params)
assert hue_ignored_warning in caplog.text