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