#
# 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
from distutils.version import LooseVersion
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.testing.pandasutils import (
have_plotly,
plotly_requirement_message,
PandasOnSparkTestCase,
TestUtils,
)
from pyspark.pandas.utils import name_like_string
if have_plotly:
from plotly import express
import plotly.graph_objs as go
@unittest.skipIf(not have_plotly, plotly_requirement_message)
@unittest.skipIf(
LooseVersion(pd.__version__) < "1.0.0",
"pandas<1.0; pandas<1.0 does not support latest plotly and/or 'plotting.backend' option.",
)
class DataFramePlotPlotlyTest(PandasOnSparkTestCase, TestUtils):
@classmethod
def setUpClass(cls):
super().setUpClass()
pd.set_option("plotting.backend", "plotly")
set_option("plotting.backend", "plotly")
set_option("plotting.max_rows", 2000)
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], "b": [2, 3, 4, 5, 7, 9, 10, 15, 34, 45, 49]},
index=[0, 1, 3, 5, 6, 8, 9, 9, 9, 10, 10],
)
@property
def psdf1(self):
return ps.from_pandas(self.pdf1)
def test_line_plot(self):
def check_line_plot(pdf, psdf):
self.assertEqual(pdf.plot(kind="line"), psdf.plot(kind="line"))
self.assertEqual(pdf.plot.line(), psdf.plot.line())
pdf1 = self.pdf1
psdf1 = self.psdf1
check_line_plot(pdf1, psdf1)
def test_area_plot(self):
def check_area_plot(pdf, psdf):
self.assertEqual(pdf.plot(kind="area"), psdf.plot(kind="area"))
self.assertEqual(pdf.plot.area(), psdf.plot.area())
pdf = self.pdf1
psdf = self.psdf1
check_area_plot(pdf, psdf)
def test_area_plot_y(self):
def check_area_plot_y(pdf, psdf, y):
self.assertEqual(pdf.plot.area(y=y), psdf.plot.area(y=y))
# test if frame area plot is correct when y is specified
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)
check_area_plot_y(pdf, psdf, y="sales")
def test_barh_plot_with_x_y(self):
def check_barh_plot_with_x_y(pdf, psdf, x, y):
self.assertEqual(pdf.plot(kind="barh", x=x, y=y), psdf.plot(kind="barh", x=x, y=y))
self.assertEqual(pdf.plot.barh(x=x, y=y), psdf.plot.barh(x=x, y=y))
# this is testing plot with specified x and y
pdf1 = pd.DataFrame({"lab": ["A", "B", "C"], "val": [10, 30, 20]})
psdf1 = ps.from_pandas(pdf1)
check_barh_plot_with_x_y(pdf1, psdf1, x="lab", y="val")
def test_barh_plot(self):
def check_barh_plot(pdf, psdf):
self.assertEqual(pdf.plot(kind="barh"), psdf.plot(kind="barh"))
self.assertEqual(pdf.plot.barh(), psdf.plot.barh())
# this is testing when x or y is not assigned
pdf1 = pd.DataFrame({"lab": [20.1, 40.5, 60.6], "val": [10, 30, 20]})
psdf1 = ps.from_pandas(pdf1)
check_barh_plot(pdf1, psdf1)
def test_bar_plot(self):
def check_bar_plot(pdf, psdf):
self.assertEqual(pdf.plot(kind="bar"), psdf.plot(kind="bar"))
self.assertEqual(pdf.plot.bar(), psdf.plot.bar())
pdf1 = self.pdf1
psdf1 = self.psdf1
check_bar_plot(pdf1, psdf1)
def test_bar_with_x_y(self):
# this is testing plot with specified x and y
pdf = pd.DataFrame({"lab": ["A", "B", "C"], "val": [10, 30, 20]})
psdf = ps.from_pandas(pdf)
self.assertEqual(
pdf.plot(kind="bar", x="lab", y="val"), psdf.plot(kind="bar", x="lab", y="val")
)
self.assertEqual(pdf.plot.bar(x="lab", y="val"), psdf.plot.bar(x="lab", y="val"))
def test_scatter_plot(self):
def check_scatter_plot(pdf, psdf, x, y, c):
self.assertEqual(pdf.plot.scatter(x=x, y=y), psdf.plot.scatter(x=x, y=y))
self.assertEqual(
pdf.plot(kind="scatter", x=x, y=y), psdf.plot(kind="scatter", x=x, y=y)
)
# check when keyword c is given as name of a column
self.assertEqual(
pdf.plot.scatter(x=x, y=y, c=c, s=50), psdf.plot.scatter(x=x, y=y, c=c, s=50)
)
# Use pandas scatter plot example
pdf1 = pd.DataFrame(np.random.rand(50, 4), columns=["a", "b", "c", "d"])
psdf1 = ps.from_pandas(pdf1)
check_scatter_plot(pdf1, psdf1, x="a", y="b", c="c")
def test_pie_plot(self):
def check_pie_plot(psdf):
pdf = psdf.to_pandas()
self.assertEqual(
psdf.plot(kind="pie", y=psdf.columns[0]),
express.pie(pdf, values="a", names=pdf.index),
)
self.assertEqual(
psdf.plot(kind="pie", values="a"),
express.pie(pdf, values="a"),
)
psdf1 = self.psdf1
check_pie_plot(psdf1)
# TODO: support multi-index columns
# columns = pd.MultiIndex.from_tuples([("x", "y"), ("y", "z")])
# psdf1.columns = columns
# check_pie_plot(psdf1)
# TODO: support multi-index
# psdf1 = 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),
# )
# check_pie_plot(psdf1)
def test_hist_plot(self):
def check_hist_plot(psdf):
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]),
np.array([4.0, 3.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 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(psdf.columns[0])
name_b = name_like_string(psdf.columns[1])
bars = [
go.Bar(
x=bins,
y=data[0],
name=name_a,
text=text_bins,
hovertemplate=("variable=" + name_a + "
value=%{text}
count=%{y}"),
),
go.Bar(
x=bins,
y=data[1],
name=name_b,
text=text_bins,
hovertemplate=("variable=" + name_b + "
value=%{text}
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(psdf.plot(kind="hist").to_dict()), pprint.pformat(fig.to_dict())
)
psdf1 = self.psdf1
check_hist_plot(psdf1)
columns = pd.MultiIndex.from_tuples([("x", "y"), ("y", "z")])
psdf1.columns = columns
check_hist_plot(psdf1)
def test_kde_plot(self):
psdf = ps.DataFrame({"a": [1, 2, 3, 4, 5], "b": [1, 3, 5, 7, 9], "c": [2, 4, 6, 8, 10]})
pdf = pd.DataFrame(
{
"Density": [
0.03515491,
0.06834979,
0.00663503,
0.02372059,
0.06834979,
0.01806934,
0.01806934,
0.06834979,
0.02372059,
],
"names": ["a", "a", "a", "b", "b", "b", "c", "c", "c"],
"index": [-3.5, 5.5, 14.5, -3.5, 5.5, 14.5, -3.5, 5.5, 14.5],
}
)
actual = psdf.plot.kde(bw_method=5, ind=3)
expected = express.line(pdf, x="index", y="Density", color="names")
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_frame_plot_plotly import * # noqa: F401
try:
import xmlrunner # type: ignore[import]
testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2)
except ImportError:
testRunner = None
unittest.main(testRunner=testRunner, verbosity=2)