python/pyspark/pandas/tests/plot/test_series_plot_plotly.py - spark - Git at Google

 #
 # Licensed to the Apache Software Foundation (ASF) under one or more
 # contributor license agreements.  See the NOTICE file distributed with
 # this work for additional information regarding copyright ownership.
 # The ASF licenses this file to You under the Apache License, Version 2.0
 # (the "License"); you may not use this file except in compliance with
 # the License.  You may obtain a copy of the License at
 #
 #    http://www.apache.org/licenses/LICENSE-2.0
 #
 # Unless required by applicable law or agreed to in writing, software
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #

 import unittest
 import pprint

 import pandas as pd
 import numpy as np

 from pyspark import pandas as ps
 from pyspark.pandas.config import set_option, reset_option
 from pyspark.pandas.utils import name_like_string
 from pyspark.testing.pandasutils import (
     have_plotly,
     plotly_requirement_message,
     PandasOnSparkTestCase,
     TestUtils,
 )

 if have_plotly:
     from plotly import express
     import plotly.graph_objs as go


 @unittest.skipIf(not have_plotly, plotly_requirement_message)
 class SeriesPlotPlotlyTest(PandasOnSparkTestCase, TestUtils):
     @classmethod
     def setUpClass(cls):
         super().setUpClass()
         pd.set_option("plotting.backend", "plotly")
         set_option("plotting.backend", "plotly")
         set_option("plotting.max_rows", 1000)
         set_option("plotting.sample_ratio", None)

     @classmethod
     def tearDownClass(cls):
         pd.reset_option("plotting.backend")
         reset_option("plotting.backend")
         reset_option("plotting.max_rows")
         reset_option("plotting.sample_ratio")
         super().tearDownClass()

     @property
     def pdf1(self):
         return pd.DataFrame(
             {"a": [1, 2, 3, 4, 5, 6, 7, 8, 9, 15, 50]}, index=[0, 1, 3, 5, 6, 8, 9, 9, 9, 10, 10]
         )

     @property
     def psdf1(self):
         return ps.from_pandas(self.pdf1)

     @property
     def psdf2(self):
         return ps.range(1002)

     @property
     def pdf2(self):
         return self.psdf2._to_pandas()

     def test_bar_plot(self):
         pdf = self.pdf1
         psdf = self.psdf1

         self.assertEqual(pdf["a"].plot(kind="bar"), psdf["a"].plot(kind="bar"))
         self.assertEqual(pdf["a"].plot.bar(), psdf["a"].plot.bar())

     def test_line_plot(self):
         pdf = self.pdf1
         psdf = self.psdf1

         self.assertEqual(pdf["a"].plot(kind="line"), psdf["a"].plot(kind="line"))
         self.assertEqual(pdf["a"].plot.line(), psdf["a"].plot.line())

     def test_barh_plot(self):
         pdf = self.pdf1
         psdf = self.psdf1

         self.assertEqual(pdf["a"].plot(kind="barh"), psdf["a"].plot(kind="barh"))

     def test_area_plot(self):
         pdf = pd.DataFrame(
             {
                 "sales": [3, 2, 3, 9, 10, 6],
                 "signups": [5, 5, 6, 12, 14, 13],
                 "visits": [20, 42, 28, 62, 81, 50],
             },
             index=pd.date_range(start="2018/01/01", end="2018/07/01", freq="M"),
         )
         psdf = ps.from_pandas(pdf)

         self.assertEqual(pdf["sales"].plot(kind="area"), psdf["sales"].plot(kind="area"))
         self.assertEqual(pdf["sales"].plot.area(), psdf["sales"].plot.area())

         # just a sanity check for df.col type
         self.assertEqual(pdf.sales.plot(kind="area"), psdf.sales.plot(kind="area"))

     def test_pie_plot(self):
         psdf = self.psdf1
         pdf = psdf._to_pandas()
         self.assertEqual(
             psdf["a"].plot(kind="pie"),
             express.pie(pdf, values=pdf.columns[0], names=pdf.index),
         )

         # TODO: support multi-index columns
         # columns = pd.MultiIndex.from_tuples([("x", "y")])
         # psdf.columns = columns
         # pdf.columns = columns
         # self.assertEqual(
         #     psdf[("x", "y")].plot(kind="pie"),
         #     express.pie(pdf, values=pdf.iloc[:, 0].to_numpy(), names=pdf.index.to_numpy()),
         # )

         # TODO: support multi-index
         # psdf = ps.DataFrame(
         #     {
         #         "a": [1, 2, 3, 4, 5, 6, 7, 8, 9, 15, 50],
         #         "b": [2, 3, 4, 5, 7, 9, 10, 15, 34, 45, 49]
         #     },
         #     index=pd.MultiIndex.from_tuples([("x", "y")] * 11),
         # )
         # pdf = psdf._to_pandas()
         # self.assertEqual(
         #     psdf["a"].plot(kind="pie"), express.pie(pdf, values=pdf.columns[0], names=pdf.index),
         # )

     def test_hist_plot(self):
         def check_hist_plot(psser):
             bins = np.array([1.0, 5.9, 10.8, 15.7, 20.6, 25.5, 30.4, 35.3, 40.2, 45.1, 50.0])
             data = np.array([5.0, 4.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0])
             prev = bins[0]
             text_bins = []
             for b in bins[1:]:
                 text_bins.append("[%s, %s)" % (prev, b))
                 prev = b
             text_bins[-1] = text_bins[-1][:-1] + "]"
             bins = 0.5 * (bins[:-1] + bins[1:])
             name_a = name_like_string(psser.name)
             bars = [
                 go.Bar(
                     x=bins,
                     y=data,
                     name=name_a,
                     text=text_bins,
                     hovertemplate=("variable=" + name_a + "<br>value=%{text}<br>count=%{y}"),
                 ),
             ]
             fig = go.Figure(data=bars, layout=go.Layout(barmode="stack"))
             fig["layout"]["xaxis"]["title"] = "value"
             fig["layout"]["yaxis"]["title"] = "count"

             self.assertEqual(
                 pprint.pformat(psser.plot(kind="hist").to_dict()), pprint.pformat(fig.to_dict())
             )

         psdf1 = self.psdf1
         check_hist_plot(psdf1["a"])

         columns = pd.MultiIndex.from_tuples([("x", "y")])
         psdf1.columns = columns
         check_hist_plot(psdf1[("x", "y")])

     def test_pox_plot(self):
         def check_pox_plot(psser):
             fig = go.Figure()
             fig.add_trace(
                 go.Box(
                     name=name_like_string(psser.name),
                     q1=[3],
                     median=[6],
                     q3=[9],
                     mean=[10.0],
                     lowerfence=[1],
                     upperfence=[15],
                     y=[[50]],
                     boxpoints="suspectedoutliers",
                     notched=False,
                 )
             )
             fig["layout"]["xaxis"]["title"] = name_like_string(psser.name)
             fig["layout"]["yaxis"]["title"] = "value"

             self.assertEqual(
                 pprint.pformat(psser.plot(kind="box").to_dict()), pprint.pformat(fig.to_dict())
             )

         psdf1 = self.psdf1
         check_pox_plot(psdf1["a"])

         columns = pd.MultiIndex.from_tuples([("x", "y")])
         psdf1.columns = columns
         check_pox_plot(psdf1[("x", "y")])

     def test_pox_plot_arguments(self):
         with self.assertRaisesRegex(ValueError, "does not support"):
             self.psdf1.a.plot.box(boxpoints="all")
         with self.assertRaisesRegex(ValueError, "does not support"):
             self.psdf1.a.plot.box(notched=True)
         self.psdf1.a.plot.box(hovertext="abc")  # other arguments should not throw an exception

     def test_kde_plot(self):
         psdf = ps.DataFrame({"a": [1, 2, 3, 4, 5]})
         pdf = pd.DataFrame(
             {
                 "Density": [0.05709372, 0.07670272, 0.05709372],
                 "names": ["a", "a", "a"],
                 "index": [-1.0, 3.0, 7.0],
             }
         )

         actual = psdf.a.plot.kde(bw_method=5, ind=3)

         expected = express.line(pdf, x="index", y="Density")
         expected["layout"]["xaxis"]["title"] = None

         self.assertEqual(pprint.pformat(actual.to_dict()), pprint.pformat(expected.to_dict()))


 if __name__ == "__main__":
     from pyspark.pandas.tests.plot.test_series_plot_plotly import *  # noqa: F401

     try:
         import xmlrunner

         testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2)
     except ImportError:
         testRunner = None
     unittest.main(testRunner=testRunner, verbosity=2)
	#
	# Licensed to the Apache Software Foundation (ASF) under one or more
	# contributor license agreements. See the NOTICE file distributed with
	# this work for additional information regarding copyright ownership.
	# The ASF licenses this file to You under the Apache License, Version 2.0
	# (the "License"); you may not use this file except in compliance with
	# the License. You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.
	#

	import unittest
	import pprint

	import pandas as pd
	import numpy as np

	from pyspark import pandas as ps
	from pyspark.pandas.config import set_option, reset_option
	from pyspark.pandas.utils import name_like_string
	from pyspark.testing.pandasutils import (
	have_plotly,
	plotly_requirement_message,
	PandasOnSparkTestCase,
	TestUtils,
	)

	if have_plotly:
	from plotly import express
	import plotly.graph_objs as go


	@unittest.skipIf(not have_plotly, plotly_requirement_message)
	class SeriesPlotPlotlyTest(PandasOnSparkTestCase, TestUtils):
	@classmethod
	def setUpClass(cls):
	super().setUpClass()
	pd.set_option("plotting.backend", "plotly")
	set_option("plotting.backend", "plotly")
	set_option("plotting.max_rows", 1000)
	set_option("plotting.sample_ratio", None)

	@classmethod
	def tearDownClass(cls):
	pd.reset_option("plotting.backend")
	reset_option("plotting.backend")
	reset_option("plotting.max_rows")
	reset_option("plotting.sample_ratio")
	super().tearDownClass()

	@property
	def pdf1(self):
	return pd.DataFrame(
	{"a": [1, 2, 3, 4, 5, 6, 7, 8, 9, 15, 50]}, index=[0, 1, 3, 5, 6, 8, 9, 9, 9, 10, 10]
	)

	@property
	def psdf1(self):
	return ps.from_pandas(self.pdf1)

	@property
	def psdf2(self):
	return ps.range(1002)

	@property
	def pdf2(self):
	return self.psdf2._to_pandas()

	def test_bar_plot(self):
	pdf = self.pdf1
	psdf = self.psdf1

	self.assertEqual(pdf["a"].plot(kind="bar"), psdf["a"].plot(kind="bar"))
	self.assertEqual(pdf["a"].plot.bar(), psdf["a"].plot.bar())

	def test_line_plot(self):
	pdf = self.pdf1
	psdf = self.psdf1

	self.assertEqual(pdf["a"].plot(kind="line"), psdf["a"].plot(kind="line"))
	self.assertEqual(pdf["a"].plot.line(), psdf["a"].plot.line())

	def test_barh_plot(self):
	pdf = self.pdf1
	psdf = self.psdf1

	self.assertEqual(pdf["a"].plot(kind="barh"), psdf["a"].plot(kind="barh"))

	def test_area_plot(self):
	pdf = pd.DataFrame(
	{
	"sales": [3, 2, 3, 9, 10, 6],
	"signups": [5, 5, 6, 12, 14, 13],
	"visits": [20, 42, 28, 62, 81, 50],
	},
	index=pd.date_range(start="2018/01/01", end="2018/07/01", freq="M"),
	)
	psdf = ps.from_pandas(pdf)

	self.assertEqual(pdf["sales"].plot(kind="area"), psdf["sales"].plot(kind="area"))
	self.assertEqual(pdf["sales"].plot.area(), psdf["sales"].plot.area())

	# just a sanity check for df.col type
	self.assertEqual(pdf.sales.plot(kind="area"), psdf.sales.plot(kind="area"))

	def test_pie_plot(self):
	psdf = self.psdf1
	pdf = psdf._to_pandas()
	self.assertEqual(
	psdf["a"].plot(kind="pie"),
	express.pie(pdf, values=pdf.columns[0], names=pdf.index),
	)

	# TODO: support multi-index columns
	# columns = pd.MultiIndex.from_tuples([("x", "y")])
	# psdf.columns = columns
	# pdf.columns = columns
	# self.assertEqual(
	# psdf[("x", "y")].plot(kind="pie"),
	# express.pie(pdf, values=pdf.iloc[:, 0].to_numpy(), names=pdf.index.to_numpy()),
	# )

	# TODO: support multi-index
	# psdf = ps.DataFrame(
	# {
	# "a": [1, 2, 3, 4, 5, 6, 7, 8, 9, 15, 50],
	# "b": [2, 3, 4, 5, 7, 9, 10, 15, 34, 45, 49]
	# },
	# index=pd.MultiIndex.from_tuples([("x", "y")] * 11),
	# )
	# pdf = psdf._to_pandas()
	# self.assertEqual(
	# psdf["a"].plot(kind="pie"), express.pie(pdf, values=pdf.columns[0], names=pdf.index),
	# )

	def test_hist_plot(self):
	def check_hist_plot(psser):
	bins = np.array([1.0, 5.9, 10.8, 15.7, 20.6, 25.5, 30.4, 35.3, 40.2, 45.1, 50.0])
	data = np.array([5.0, 4.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0])
	prev = bins[0]
	text_bins = []
	for b in bins[1:]:
	text_bins.append("[%s, %s)" % (prev, b))
	prev = b
	text_bins[-1] = text_bins[-1][:-1] + "]"
	bins = 0.5 * (bins[:-1] + bins[1:])
	name_a = name_like_string(psser.name)
	bars = [
	go.Bar(
	x=bins,
	y=data,
	name=name_a,
	text=text_bins,
	hovertemplate=("variable=" + name_a + "<br>value=%{text}<br>count=%{y}"),
	),
	]
	fig = go.Figure(data=bars, layout=go.Layout(barmode="stack"))
	fig["layout"]["xaxis"]["title"] = "value"
	fig["layout"]["yaxis"]["title"] = "count"

	self.assertEqual(
	pprint.pformat(psser.plot(kind="hist").to_dict()), pprint.pformat(fig.to_dict())
	)

	psdf1 = self.psdf1
	check_hist_plot(psdf1["a"])

	columns = pd.MultiIndex.from_tuples([("x", "y")])
	psdf1.columns = columns
	check_hist_plot(psdf1[("x", "y")])

	def test_pox_plot(self):
	def check_pox_plot(psser):
	fig = go.Figure()
	fig.add_trace(
	go.Box(
	name=name_like_string(psser.name),
	q1=[3],
	median=[6],
	q3=[9],
	mean=[10.0],
	lowerfence=[1],
	upperfence=[15],
	y=[[50]],
	boxpoints="suspectedoutliers",
	notched=False,
	)
	)
	fig["layout"]["xaxis"]["title"] = name_like_string(psser.name)
	fig["layout"]["yaxis"]["title"] = "value"

	self.assertEqual(
	pprint.pformat(psser.plot(kind="box").to_dict()), pprint.pformat(fig.to_dict())
	)

	psdf1 = self.psdf1
	check_pox_plot(psdf1["a"])

	columns = pd.MultiIndex.from_tuples([("x", "y")])
	psdf1.columns = columns
	check_pox_plot(psdf1[("x", "y")])

	def test_pox_plot_arguments(self):
	with self.assertRaisesRegex(ValueError, "does not support"):
	self.psdf1.a.plot.box(boxpoints="all")
	with self.assertRaisesRegex(ValueError, "does not support"):
	self.psdf1.a.plot.box(notched=True)
	self.psdf1.a.plot.box(hovertext="abc") # other arguments should not throw an exception

	def test_kde_plot(self):
	psdf = ps.DataFrame({"a": [1, 2, 3, 4, 5]})
	pdf = pd.DataFrame(
	{
	"Density": [0.05709372, 0.07670272, 0.05709372],
	"names": ["a", "a", "a"],
	"index": [-1.0, 3.0, 7.0],
	}
	)

	actual = psdf.a.plot.kde(bw_method=5, ind=3)

	expected = express.line(pdf, x="index", y="Density")
	expected["layout"]["xaxis"]["title"] = None

	self.assertEqual(pprint.pformat(actual.to_dict()), pprint.pformat(expected.to_dict()))


	if __name__ == "__main__":
	from pyspark.pandas.tests.plot.test_series_plot_plotly import * # noqa: F401

	try:
	import xmlrunner

	testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2)
	except ImportError:
	testRunner = None
	unittest.main(testRunner=testRunner, verbosity=2)