cd1e8e8158
### What changes were proposed in this pull request? Now that we merged the Koalas main code into the PySpark code base (#32036), we should port the Koalas plot unit tests to PySpark. ### Why are the changes needed? Currently, the pandas-on-Spark modules are not tested fully. We should enable the plot unit tests. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Enable plot unit tests. Closes #32151 from xinrong-databricks/port.plot_tests. Authored-by: Xinrong Meng <xinrong.meng@databricks.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
470 lines
18 KiB
Python
470 lines
18 KiB
Python
#
|
|
# 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 base64
|
|
from distutils.version import LooseVersion
|
|
from io import BytesIO
|
|
import unittest
|
|
|
|
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.testing.utils import have_matplotlib, ReusedSQLTestCase, TestUtils
|
|
|
|
if have_matplotlib:
|
|
import matplotlib
|
|
from matplotlib import pyplot as plt
|
|
|
|
matplotlib.use("agg")
|
|
|
|
|
|
@unittest.skipIf(not have_matplotlib, "matplotlib is not installed.")
|
|
class DataFramePlotMatplotlibTest(ReusedSQLTestCase, TestUtils):
|
|
sample_ratio_default = None
|
|
|
|
@classmethod
|
|
def setUpClass(cls):
|
|
super().setUpClass()
|
|
if LooseVersion(pd.__version__) >= LooseVersion("0.25"):
|
|
pd.set_option("plotting.backend", "matplotlib")
|
|
set_option("plotting.backend", "matplotlib")
|
|
set_option("plotting.max_rows", 2000)
|
|
set_option("plotting.sample_ratio", None)
|
|
|
|
@classmethod
|
|
def tearDownClass(cls):
|
|
if LooseVersion(pd.__version__) >= LooseVersion("0.25"):
|
|
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 kdf1(self):
|
|
return ps.from_pandas(self.pdf1)
|
|
|
|
@staticmethod
|
|
def plot_to_base64(ax):
|
|
bytes_data = BytesIO()
|
|
ax.figure.savefig(bytes_data, format="png")
|
|
bytes_data.seek(0)
|
|
b64_data = base64.b64encode(bytes_data.read())
|
|
plt.close(ax.figure)
|
|
return b64_data
|
|
|
|
def test_line_plot(self):
|
|
def check_line_plot(pdf, kdf):
|
|
ax1 = pdf.plot(kind="line", colormap="Paired")
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot(kind="line", colormap="Paired")
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax3 = pdf.plot.line(colormap="Paired")
|
|
bin3 = self.plot_to_base64(ax3)
|
|
ax4 = kdf.plot.line(colormap="Paired")
|
|
bin4 = self.plot_to_base64(ax4)
|
|
self.assertEqual(bin3, bin4)
|
|
|
|
pdf1 = self.pdf1
|
|
kdf1 = self.kdf1
|
|
check_line_plot(pdf1, kdf1)
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "a"), ("y", "b")])
|
|
pdf1.columns = columns
|
|
kdf1.columns = columns
|
|
check_line_plot(pdf1, kdf1)
|
|
|
|
def test_area_plot(self):
|
|
def check_area_plot(pdf, kdf):
|
|
ax1 = pdf.plot(kind="area", colormap="Paired")
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot(kind="area", colormap="Paired")
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax3 = pdf.plot.area(colormap="Paired")
|
|
bin3 = self.plot_to_base64(ax3)
|
|
ax4 = kdf.plot.area(colormap="Paired")
|
|
bin4 = self.plot_to_base64(ax4)
|
|
self.assertEqual(bin3, bin4)
|
|
|
|
pdf = self.pdf1
|
|
kdf = self.kdf1
|
|
check_area_plot(pdf, kdf)
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "a"), ("y", "b")])
|
|
pdf.columns = columns
|
|
kdf.columns = columns
|
|
check_area_plot(pdf, kdf)
|
|
|
|
def test_area_plot_stacked_false(self):
|
|
def check_area_plot_stacked_false(pdf, kdf):
|
|
ax1 = pdf.plot.area(stacked=False)
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot.area(stacked=False)
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
# test if frame area plot is correct when stacked=False because default is True
|
|
|
|
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"),
|
|
)
|
|
kdf = ps.from_pandas(pdf)
|
|
check_area_plot_stacked_false(pdf, kdf)
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "sales"), ("x", "signups"), ("y", "visits")])
|
|
pdf.columns = columns
|
|
kdf.columns = columns
|
|
check_area_plot_stacked_false(pdf, kdf)
|
|
|
|
def test_area_plot_y(self):
|
|
def check_area_plot_y(pdf, kdf, y):
|
|
ax1 = pdf.plot.area(y=y)
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot.area(y=y)
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
# 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"),
|
|
)
|
|
kdf = ps.from_pandas(pdf)
|
|
check_area_plot_y(pdf, kdf, y="sales")
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "sales"), ("x", "signups"), ("y", "visits")])
|
|
pdf.columns = columns
|
|
kdf.columns = columns
|
|
check_area_plot_y(pdf, kdf, y=("x", "sales"))
|
|
|
|
def test_barh_plot_with_x_y(self):
|
|
def check_barh_plot_with_x_y(pdf, kdf, x, y):
|
|
ax1 = pdf.plot(kind="barh", x=x, y=y, colormap="Paired")
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot(kind="barh", x=x, y=y, colormap="Paired")
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax3 = pdf.plot.barh(x=x, y=y, colormap="Paired")
|
|
bin3 = self.plot_to_base64(ax3)
|
|
ax4 = kdf.plot.barh(x=x, y=y, colormap="Paired")
|
|
bin4 = self.plot_to_base64(ax4)
|
|
self.assertEqual(bin3, bin4)
|
|
|
|
# this is testing plot with specified x and y
|
|
pdf1 = pd.DataFrame({"lab": ["A", "B", "C"], "val": [10, 30, 20]})
|
|
kdf1 = ps.from_pandas(pdf1)
|
|
check_barh_plot_with_x_y(pdf1, kdf1, x="lab", y="val")
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "lab"), ("y", "val")])
|
|
pdf1.columns = columns
|
|
kdf1.columns = columns
|
|
check_barh_plot_with_x_y(pdf1, kdf1, x=("x", "lab"), y=("y", "val"))
|
|
|
|
def test_barh_plot(self):
|
|
def check_barh_plot(pdf, kdf):
|
|
ax1 = pdf.plot(kind="barh", colormap="Paired")
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot(kind="barh", colormap="Paired")
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax3 = pdf.plot.barh(colormap="Paired")
|
|
bin3 = self.plot_to_base64(ax3)
|
|
ax4 = kdf.plot.barh(colormap="Paired")
|
|
bin4 = self.plot_to_base64(ax4)
|
|
self.assertEqual(bin3, bin4)
|
|
|
|
# this is testing when x or y is not assigned
|
|
pdf1 = pd.DataFrame({"lab": ["A", "B", "C"], "val": [10, 30, 20]})
|
|
kdf1 = ps.from_pandas(pdf1)
|
|
check_barh_plot(pdf1, kdf1)
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "lab"), ("y", "val")])
|
|
pdf1.columns = columns
|
|
kdf1.columns = columns
|
|
check_barh_plot(pdf1, kdf1)
|
|
|
|
def test_bar_plot(self):
|
|
def check_bar_plot(pdf, kdf):
|
|
ax1 = pdf.plot(kind="bar", colormap="Paired")
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot(kind="bar", colormap="Paired")
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax3 = pdf.plot.bar(colormap="Paired")
|
|
bin3 = self.plot_to_base64(ax3)
|
|
ax4 = kdf.plot.bar(colormap="Paired")
|
|
bin4 = self.plot_to_base64(ax4)
|
|
self.assertEqual(bin3, bin4)
|
|
|
|
pdf1 = self.pdf1
|
|
kdf1 = self.kdf1
|
|
check_bar_plot(pdf1, kdf1)
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "lab"), ("y", "val")])
|
|
pdf1.columns = columns
|
|
kdf1.columns = columns
|
|
check_bar_plot(pdf1, kdf1)
|
|
|
|
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]})
|
|
kdf = ps.from_pandas(pdf)
|
|
|
|
ax1 = pdf.plot(kind="bar", x="lab", y="val", colormap="Paired")
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot(kind="bar", x="lab", y="val", colormap="Paired")
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax3 = pdf.plot.bar(x="lab", y="val", colormap="Paired")
|
|
bin3 = self.plot_to_base64(ax3)
|
|
ax4 = kdf.plot.bar(x="lab", y="val", colormap="Paired")
|
|
bin4 = self.plot_to_base64(ax4)
|
|
self.assertEqual(bin3, bin4)
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "lab"), ("y", "val")])
|
|
pdf.columns = columns
|
|
kdf.columns = columns
|
|
|
|
ax5 = pdf.plot(kind="bar", x=("x", "lab"), y=("y", "val"), colormap="Paired")
|
|
bin5 = self.plot_to_base64(ax5)
|
|
ax6 = kdf.plot(kind="bar", x=("x", "lab"), y=("y", "val"), colormap="Paired")
|
|
bin6 = self.plot_to_base64(ax6)
|
|
self.assertEqual(bin5, bin6)
|
|
|
|
ax7 = pdf.plot.bar(x=("x", "lab"), y=("y", "val"), colormap="Paired")
|
|
bin7 = self.plot_to_base64(ax7)
|
|
ax8 = kdf.plot.bar(x=("x", "lab"), y=("y", "val"), colormap="Paired")
|
|
bin8 = self.plot_to_base64(ax8)
|
|
self.assertEqual(bin7, bin8)
|
|
|
|
def test_pie_plot(self):
|
|
def check_pie_plot(pdf, kdf, y):
|
|
ax1 = pdf.plot.pie(y=y, figsize=(5, 5), colormap="Paired")
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot.pie(y=y, figsize=(5, 5), colormap="Paired")
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax1 = pdf.plot(kind="pie", y=y, figsize=(5, 5), colormap="Paired")
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot(kind="pie", y=y, figsize=(5, 5), colormap="Paired")
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax11, ax12 = pdf.plot.pie(figsize=(5, 5), subplots=True, colormap="Paired")
|
|
bin11 = self.plot_to_base64(ax11)
|
|
bin12 = self.plot_to_base64(ax12)
|
|
self.assertEqual(bin11, bin12)
|
|
|
|
ax21, ax22 = kdf.plot.pie(figsize=(5, 5), subplots=True, colormap="Paired")
|
|
bin21 = self.plot_to_base64(ax21)
|
|
bin22 = self.plot_to_base64(ax22)
|
|
self.assertEqual(bin21, bin22)
|
|
|
|
ax11, ax12 = pdf.plot(kind="pie", figsize=(5, 5), subplots=True, colormap="Paired")
|
|
bin11 = self.plot_to_base64(ax11)
|
|
bin12 = self.plot_to_base64(ax12)
|
|
self.assertEqual(bin11, bin12)
|
|
|
|
ax21, ax22 = kdf.plot(kind="pie", figsize=(5, 5), subplots=True, colormap="Paired")
|
|
bin21 = self.plot_to_base64(ax21)
|
|
bin22 = self.plot_to_base64(ax22)
|
|
self.assertEqual(bin21, bin22)
|
|
|
|
pdf1 = pd.DataFrame(
|
|
{"mass": [0.330, 4.87, 5.97], "radius": [2439.7, 6051.8, 6378.1]},
|
|
index=["Mercury", "Venus", "Earth"],
|
|
)
|
|
kdf1 = ps.from_pandas(pdf1)
|
|
check_pie_plot(pdf1, kdf1, y="mass")
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "mass"), ("y", "radius")])
|
|
pdf1.columns = columns
|
|
kdf1.columns = columns
|
|
check_pie_plot(pdf1, kdf1, y=("x", "mass"))
|
|
|
|
def test_pie_plot_error_message(self):
|
|
# this is to test if error is correctly raising when y is not specified
|
|
# and subplots is not set to True
|
|
pdf = pd.DataFrame(
|
|
{"mass": [0.330, 4.87, 5.97], "radius": [2439.7, 6051.8, 6378.1]},
|
|
index=["Mercury", "Venus", "Earth"],
|
|
)
|
|
kdf = ps.from_pandas(pdf)
|
|
|
|
with self.assertRaises(ValueError) as context:
|
|
kdf.plot.pie(figsize=(5, 5), colormap="Paired")
|
|
error_message = "pie requires either y column or 'subplots=True'"
|
|
self.assertTrue(error_message in str(context.exception))
|
|
|
|
def test_scatter_plot(self):
|
|
def check_scatter_plot(pdf, kdf, x, y, c):
|
|
ax1 = pdf.plot.scatter(x=x, y=y)
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot.scatter(x=x, y=y)
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax1 = pdf.plot(kind="scatter", x=x, y=y)
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot(kind="scatter", x=x, y=y)
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
# check when keyword c is given as name of a column
|
|
ax1 = pdf.plot.scatter(x=x, y=y, c=c, s=50)
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot.scatter(x=x, y=y, c=c, s=50)
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
# Use pandas scatter plot example
|
|
pdf1 = pd.DataFrame(np.random.rand(50, 4), columns=["a", "b", "c", "d"])
|
|
kdf1 = ps.from_pandas(pdf1)
|
|
check_scatter_plot(pdf1, kdf1, x="a", y="b", c="c")
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "a"), ("x", "b"), ("y", "c"), ("z", "d")])
|
|
pdf1.columns = columns
|
|
kdf1.columns = columns
|
|
check_scatter_plot(pdf1, kdf1, x=("x", "a"), y=("x", "b"), c=("y", "c"))
|
|
|
|
def test_hist_plot(self):
|
|
def check_hist_plot(pdf, kdf):
|
|
_, ax1 = plt.subplots(1, 1)
|
|
ax1 = pdf.plot.hist()
|
|
bin1 = self.plot_to_base64(ax1)
|
|
_, ax2 = plt.subplots(1, 1)
|
|
ax2 = kdf.plot.hist()
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax1 = pdf.plot.hist(bins=15)
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot.hist(bins=15)
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax1 = pdf.plot(kind="hist", bins=15)
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot(kind="hist", bins=15)
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
ax1 = pdf.plot.hist(bins=3, bottom=[2, 1, 3])
|
|
bin1 = self.plot_to_base64(ax1)
|
|
ax2 = kdf.plot.hist(bins=3, bottom=[2, 1, 3])
|
|
bin2 = self.plot_to_base64(ax2)
|
|
self.assertEqual(bin1, bin2)
|
|
|
|
pdf1 = self.pdf1
|
|
kdf1 = self.kdf1
|
|
check_hist_plot(pdf1, kdf1)
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "a"), ("y", "b")])
|
|
pdf1.columns = columns
|
|
kdf1.columns = columns
|
|
check_hist_plot(pdf1, kdf1)
|
|
|
|
def test_kde_plot(self):
|
|
def moving_average(a, n=10):
|
|
ret = np.cumsum(a, dtype=float)
|
|
ret[n:] = ret[n:] - ret[:-n]
|
|
return ret[n - 1:] / n
|
|
|
|
def check_kde_plot(pdf, kdf, *args, **kwargs):
|
|
_, ax1 = plt.subplots(1, 1)
|
|
ax1 = pdf.plot.kde(*args, **kwargs)
|
|
_, ax2 = plt.subplots(1, 1)
|
|
ax2 = kdf.plot.kde(*args, **kwargs)
|
|
|
|
try:
|
|
for i, (line1, line2) in enumerate(zip(ax1.get_lines(), ax2.get_lines())):
|
|
expected = line1.get_xydata().ravel()
|
|
actual = line2.get_xydata().ravel()
|
|
# TODO: Due to implementation difference, the output is different comparing
|
|
# to pandas'. We should identify the root cause of difference, and reduce
|
|
# the diff.
|
|
|
|
# Note: Data is from 1 to 50. So, it smooths them by moving average and compares
|
|
# both.
|
|
self.assertTrue(
|
|
np.allclose(moving_average(actual), moving_average(expected), rtol=3.0)
|
|
)
|
|
finally:
|
|
ax1.cla()
|
|
ax2.cla()
|
|
|
|
pdf1 = self.pdf1
|
|
kdf1 = self.kdf1
|
|
check_kde_plot(pdf1, kdf1, bw_method=0.3)
|
|
check_kde_plot(pdf1, kdf1, ind=[1, 2, 3], bw_method=3.0)
|
|
|
|
# multi-index columns
|
|
columns = pd.MultiIndex.from_tuples([("x", "a"), ("y", "b")])
|
|
pdf1.columns = columns
|
|
pdf1.columns = columns
|
|
check_kde_plot(pdf1, kdf1, bw_method=0.3)
|
|
check_kde_plot(pdf1, kdf1, ind=[1, 2, 3], bw_method=3.0)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
from pyspark.pandas.tests.plot.test_frame_plot_matplotlib 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)
|