def test_pairplot(self):
df = self.iris
pg = df.sns.pairplot()
self._check_axes_shape(pg.axes, axes_num=25, layout=(5, 5), figsize=None)
for i in range(5):
self.assertEqual(pg.axes[i][0].get_ylabel(), df.columns[i])
self.assertEqual(pg.axes[-1][i].get_xlabel(), df.columns[i])
tm.close()
def test_pairplot(self):
df = self.iris
pg = df.sns.pairplot()
self._check_axes_shape(pg.axes, axes_num=25,
layout=(5, 5), figsize=None)
for i in range(5):
self.assertEqual(pg.axes[i][0].get_ylabel(), df.columns[i])
self.assertEqual(pg.axes[-1][i].get_xlabel(), df.columns[i])
tm.close()
def test_lmplot(self):
df = self.diabetes
fg = df.sns.lmplot("col2")
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), "col2")
self.assertEqual(fg.ax.get_ylabel(), ".target")
tm.close()
fg = df.sns.lmplot("col2", "col3")
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), "col2")
self.assertEqual(fg.ax.get_ylabel(), "col3")
def test_jointplot(self):
df = self.iris
jg = df.sns.jointplot(df.columns[1])
self.assertIsInstance(jg, sns.JointGrid)
self.assertEqual(jg.ax_joint.get_xlabel(), df.columns[1])
self.assertEqual(jg.ax_joint.get_ylabel(), '.target')
tm.close()
jg = df.sns.jointplot(df.columns[2], df.columns[3])
self.assertIsInstance(jg, sns.JointGrid)
self.assertEqual(jg.ax_joint.get_xlabel(), df.columns[2])
self.assertEqual(jg.ax_joint.get_ylabel(), df.columns[3])
def test_lmplot(self):
df = self.diabetes
fg = df.sns.lmplot(df.columns[1])
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), df.columns[1])
self.assertEqual(fg.ax.get_ylabel(), '.target')
tm.close()
fg = df.sns.lmplot(df.columns[1], df.columns[2])
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), df.columns[1])
self.assertEqual(fg.ax.get_ylabel(), df.columns[2])
def test_lmplot(self):
df = self.diabetes
fg = df.sns.lmplot(df.columns[1])
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), df.columns[1])
self.assertEqual(fg.ax.get_ylabel(), '.target')
tm.close()
fg = df.sns.lmplot(df.columns[1], df.columns[2])
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), df.columns[1])
self.assertEqual(fg.ax.get_ylabel(), df.columns[2])
def test_jointplot(self):
df = self.iris
jg = df.sns.jointplot(df.columns[1])
self.assertIsInstance(jg, sns.JointGrid)
self.assertEqual(jg.ax_joint.get_xlabel(), df.columns[1])
self.assertEqual(jg.ax_joint.get_ylabel(), '.target')
tm.close()
jg = df.sns.jointplot(df.columns[2], df.columns[3])
self.assertIsInstance(jg, sns.JointGrid)
self.assertEqual(jg.ax_joint.get_xlabel(), df.columns[2])
self.assertEqual(jg.ax_joint.get_ylabel(), df.columns[3])
def test_lmplot(self):
df = self.diabetes
fg = df.sns.lmplot('col2')
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), 'col2')
self.assertEqual(fg.ax.get_ylabel(), '.target')
tm.close()
fg = df.sns.lmplot('col2', 'col3')
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), 'col2')
self.assertEqual(fg.ax.get_ylabel(), 'col3')
def test_categorical_mean_plots(self):
df = self.iris
plots = ['pointplot', 'barplot']
for plot in plots:
func = getattr(df.sns, plot)
ax = func(df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
self.assertEqual(ax.get_ylabel(), '{0}'.format(df.columns[1]))
tm.close()
ax = func(y=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
self.assertEqual(ax.get_ylabel(), '{0}'.format(df.columns[1]))
tm.close()
ax = func(x=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), '{0}'.format('.target'))
tm.close()
ax = func(x=df.columns[1], y=df.columns[2])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), '{0}'.format(df.columns[2]))
tm.close()
def test_categoricalplots(self):
df = self.iris
plots = ['boxplot', 'violinplot', 'stripplot']
for plot in plots:
func = getattr(df.sns, plot)
ax = func(df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
self.assertEqual(ax.get_ylabel(), df.columns[1])
tm.close()
ax = func(y=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
self.assertEqual(ax.get_ylabel(), df.columns[1])
tm.close()
ax = func(x=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), '.target')
tm.close()
ax = func(x=df.columns[1], y=df.columns[2])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), df.columns[2])
tm.close()
def test_categorical_mean_plots(self):
df = self.iris
plots = ["pointplot", "barplot"]
for plot in plots:
func = getattr(df.sns, plot)
ax = func(df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), ".target")
self.assertEqual(ax.get_ylabel(), "mean({0})".format(df.columns[1]))
tm.close()
ax = func(y=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), ".target")
self.assertEqual(ax.get_ylabel(), "mean({0})".format(df.columns[1]))
tm.close()
ax = func(x=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), "mean({0})".format(".target"))
tm.close()
ax = func(x=df.columns[1], y=df.columns[2])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), "mean({0})".format(df.columns[2]))
tm.close()
def test_count_plots(self):
df = self.iris
ax = df.sns.countplot()
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
self.assertEqual(ax.get_ylabel(), 'count')
tm.close()
return # ToDo: only fails on Travis
ax = df.sns.countplot(df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), 'count')
tm.close()
ax = df.sns.countplot(x=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), 'count')
tm.close()
ax = df.sns.countplot(y=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), 'count')
self.assertEqual(ax.get_ylabel(), df.columns[1])
tm.close()
with tm.assertRaises(TypeError):
# can't pass both x and y
df.sns.countplot(x=df.columns[1], y=df.columns[2])
def test_categorical_mean_plots(self):
df = self.iris
plots = ['pointplot', 'barplot']
for plot in plots:
func = getattr(df.sns, plot)
ax = func(df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
self.assertEqual(ax.get_ylabel(), 'mean({0})'.format(df.columns[1]))
tm.close()
ax = func(y=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
self.assertEqual(ax.get_ylabel(), 'mean({0})'.format(df.columns[1]))
tm.close()
ax = func(x=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), 'mean({0})'.format('.target'))
tm.close()
ax = func(x=df.columns[1], y=df.columns[2])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), 'mean({0})'.format(df.columns[2]))
tm.close()
def test_categoricalplots(self):
df = self.iris
plots = ['boxplot', 'violinplot', 'stripplot']
for plot in plots:
func = getattr(df.sns, plot)
ax = func(df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
self.assertEqual(ax.get_ylabel(), df.columns[1])
tm.close()
ax = func(y=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
self.assertEqual(ax.get_ylabel(), df.columns[1])
tm.close()
ax = func(x=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), '.target')
tm.close()
ax = func(x=df.columns[1], y=df.columns[2])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), df.columns[2])
tm.close()
def test_count_plots(self):
df = self.iris
ax = df.sns.countplot()
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
self.assertEqual(ax.get_ylabel(), 'count')
tm.close()
return # ToDo: only fails on Travis
ax = df.sns.countplot(df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), 'count')
tm.close()
ax = df.sns.countplot(x=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), 'count')
tm.close()
ax = df.sns.countplot(y=df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), 'count')
self.assertEqual(ax.get_ylabel(), df.columns[1])
tm.close()
with tm.assertRaises(TypeError):
# can't pass both x and y
df.sns.countplot(x=df.columns[1], y=df.columns[2])
def test_regression_plot(self):
df = self.diabetes
plots = ['regplot', 'residplot']
for plot in plots:
func = getattr(df.sns, plot)
ax = func('col2')
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), 'col2')
self.assertEqual(ax.get_ylabel(), '.target')
tm.close()
ax = func('col2', 'col3')
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), 'col2')
self.assertEqual(ax.get_ylabel(), 'col3')
tm.close()
def test_factorplots(self):
df = self.iris
fg = df.sns.factorplot(df.columns[1])
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), '.target')
self.assertEqual(fg.ax.get_ylabel(), df.columns[1])
tm.close()
fg = df.sns.factorplot(x=df.columns[1])
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), df.columns[1])
self.assertEqual(fg.ax.get_ylabel(), '.target')
tm.close()
fg = df.sns.factorplot(x=df.columns[1], y=df.columns[2])
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), df.columns[1])
self.assertEqual(fg.ax.get_ylabel(), df.columns[2])
def test_regression_plot(self):
df = self.diabetes
plots = ['regplot', 'residplot']
for plot in plots:
func = getattr(df.sns, plot)
ax = func(df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), '.target')
tm.close()
ax = func(df.columns[1], df.columns[2])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
self.assertEqual(ax.get_ylabel(), df.columns[2])
tm.close()
def test_regression_plot(self):
df = self.diabetes
plots = ["regplot", "residplot"]
for plot in plots:
func = getattr(df.sns, plot)
ax = func("col2")
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), "col2")
self.assertEqual(ax.get_ylabel(), ".target")
tm.close()
ax = func("col2", "col3")
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), "col2")
self.assertEqual(ax.get_ylabel(), "col3")
tm.close()
def test_factorplots(self):
df = self.iris
fg = df.sns.factorplot(df.columns[1])
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), '.target')
self.assertEqual(fg.ax.get_ylabel(), df.columns[1])
tm.close()
fg = df.sns.factorplot(x=df.columns[1])
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), df.columns[1])
self.assertEqual(fg.ax.get_ylabel(), '.target')
tm.close()
fg = df.sns.factorplot(x=df.columns[1], y=df.columns[2])
self.assertIsInstance(fg, sns.FacetGrid)
self.assertEqual(fg.ax.get_xlabel(), df.columns[1])
self.assertEqual(fg.ax.get_ylabel(), df.columns[2])
def test_kdeplot(self):
df = pdml.ModelFrame(np.random.randn(100, 5), columns=list('abcde'))
df.target = df['a']
ax = df.sns.kdeplot()
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '')
self.assertEqual(ax.get_ylabel(), '')
tm.close()
ax = df.sns.kdeplot(data='b', data2='c')
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), 'b')
self.assertEqual(ax.get_ylabel(), 'c')
tm.close()
ax = df.sns.kdeplot(data=df['b'], data2=df['c'])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), 'b')
self.assertEqual(ax.get_ylabel(), 'c')
def test_distplot(self):
return # ToDo: only fails on Travis
df = self.iris
ax = df.sns.distplot()
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
tm.close()
# pass scalar (str)
ax = df.sns.distplot(df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
tm.close()
# pass Series
ax = df.sns.distplot(df[df.columns[2]])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[2])
def test_distplot(self):
return # ToDo: only fails on Travis
df = self.iris
ax = df.sns.distplot()
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '.target')
tm.close()
# pass scalar (str)
ax = df.sns.distplot(df.columns[1])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[1])
tm.close()
# pass Series
ax = df.sns.distplot(df[df.columns[2]])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), df.columns[2])
def test_kdeplot(self):
df = pdml.ModelFrame(np.random.randn(100, 5), columns=list('abcde'))
df.target = df['a']
ax = df.sns.kdeplot()
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), '')
self.assertEqual(ax.get_ylabel(), '')
tm.close()
ax = df.sns.kdeplot(data='b', data2='c')
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), 'b')
self.assertEqual(ax.get_ylabel(), 'c')
tm.close()
ax = df.sns.kdeplot(data=df['b'], data2=df['c'])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), 'b')
self.assertEqual(ax.get_ylabel(), 'c')
def test_kdeplot(self):
df = pdml.ModelFrame(np.random.randn(100, 5), columns=list("abcde"))
df.target = df["a"]
ax = df.sns.kdeplot()
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), "")
self.assertEqual(ax.get_ylabel(), "")
tm.close()
ax = df.sns.kdeplot(data="b", data2="c")
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), "b")
self.assertEqual(ax.get_ylabel(), "c")
tm.close()
ax = df.sns.kdeplot(data=df["b"], data2=df["c"])
self.assertIsInstance(ax, matplotlib.axes.Axes)
self.assertEqual(ax.get_xlabel(), "b")
self.assertEqual(ax.get_ylabel(), "c")
def test_facetgrid(self):
df = self.iris
fg = df.sns.FacetGrid(df.columns[0])
self.assertIsInstance(fg, sns.FacetGrid)
self._check_axes_shape(fg.axes,
axes_num=3,
layout=(3, 1),
figsize=None)
tm.close()
fg = df.sns.FacetGrid(row=df.columns[0])
self.assertIsInstance(fg, sns.FacetGrid)
self._check_axes_shape(fg.axes,
axes_num=3,
layout=(3, 1),
figsize=None)
tm.close()
fg = df.sns.FacetGrid(col=df.columns[0])
self.assertIsInstance(fg, sns.FacetGrid)
self._check_axes_shape(fg.axes,
axes_num=3,
layout=(1, 3),
figsize=None)
tm.close()
def test_facetgrid(self):
df = self.iris
fg = df.sns.FacetGrid(df.columns[0])
self.assertIsInstance(fg, sns.FacetGrid)
self._check_axes_shape(fg.axes, axes_num=3, layout=(3, 1), figsize=None)
tm.close()
fg = df.sns.FacetGrid(row=df.columns[0])
self.assertIsInstance(fg, sns.FacetGrid)
self._check_axes_shape(fg.axes, axes_num=3, layout=(3, 1), figsize=None)
tm.close()
fg = df.sns.FacetGrid(col=df.columns[0])
self.assertIsInstance(fg, sns.FacetGrid)
self._check_axes_shape(fg.axes, axes_num=3, layout=(1, 3), figsize=None)
tm.close()
