# coding: utf-8

""" Test cases for GroupBy.plot """


import numpy as np

import pandas.util._test_decorators as td

from pandas import DataFrame, Series
import pandas._testing as tm
from pandas.tests.plotting.common import TestPlotBase


@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
