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- # coding: utf-8
- """ Test cases for GroupBy.plot """
- import numpy as np
- import pandas.util._test_decorators as td
- from pandas import DataFrame, Series
- from pandas.tests.plotting.common import TestPlotBase
- import pandas.util.testing as tm
- @td.skip_if_no_mpl
- class TestDataFrameGroupByPlots(TestPlotBase):
- def test_series_groupby_plotting_nominally_works(self):
- n = 10
- weight = Series(np.random.normal(166, 20, size=n))
- height = Series(np.random.normal(60, 10, size=n))
- with tm.RNGContext(42):
- gender = np.random.choice(['male', 'female'], size=n)
- weight.groupby(gender).plot()
- tm.close()
- height.groupby(gender).hist()
- tm.close()
- # Regression test for GH8733
- height.groupby(gender).plot(alpha=0.5)
- tm.close()
- def test_plotting_with_float_index_works(self):
- # GH 7025
- df = DataFrame({'def': [1, 1, 1, 2, 2, 2, 3, 3, 3],
- 'val': np.random.randn(9)},
- index=[1.0, 2.0, 3.0, 1.0, 2.0, 3.0, 1.0, 2.0, 3.0])
- df.groupby('def')['val'].plot()
- tm.close()
- df.groupby('def')['val'].apply(lambda x: x.plot())
- tm.close()
- def test_hist_single_row(self):
- # GH10214
- bins = np.arange(80, 100 + 2, 1)
- df = DataFrame({"Name": ["AAA", "BBB"],
- "ByCol": [1, 2],
- "Mark": [85, 89]})
- df["Mark"].hist(by=df["ByCol"], bins=bins)
- df = DataFrame({"Name": ["AAA"], "ByCol": [1], "Mark": [85]})
- df["Mark"].hist(by=df["ByCol"], bins=bins)
- def test_plot_submethod_works(self):
- df = DataFrame({'x': [1, 2, 3, 4, 5],
- 'y': [1, 2, 3, 2, 1],
- 'z': list('ababa')})
- df.groupby('z').plot.scatter('x', 'y')
- tm.close()
- df.groupby('z')['x'].plot.line()
- tm.close()
- def test_plot_kwargs(self):
- df = DataFrame({'x': [1, 2, 3, 4, 5],
- 'y': [1, 2, 3, 2, 1],
- 'z': list('ababa')})
- res = df.groupby('z').plot(kind='scatter', x='x', y='y')
- # check that a scatter plot is effectively plotted: the axes should
- # contain a PathCollection from the scatter plot (GH11805)
- assert len(res['a'].collections) == 1
- res = df.groupby('z').plot.scatter(x='x', y='y')
- assert len(res['a'].collections) == 1
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