def test_get_dummies_date_datetime(self):
df = pd.DataFrame({
'd': [
datetime.date(2019, 1, 1),
datetime.date(2019, 1, 2),
datetime.date(2019, 1, 1)
],
'dt': [
datetime.datetime(2019, 1, 1, 0, 0, 0),
datetime.datetime(2019, 1, 1, 0, 0, 1),
datetime.datetime(2019, 1, 1, 0, 0, 0)
]
})
ddf = self.spark.from_pandas(df)
exp = pd.get_dummies(df)
res = pyspark.get_dummies(ddf)
self.assertPandasAlmostEqual(res.toPandas(), exp)
exp = pd.get_dummies(df.d)
res = pyspark.get_dummies(ddf.d)
self.assertPandasAlmostEqual(res.toPandas(), exp)
exp = pd.get_dummies(df.dt)
res = pyspark.get_dummies(ddf.dt)
self.assertPandasAlmostEqual(res.toPandas(), exp)
def test_get_dummies_kwargs(self):
# s = pd.Series([1, 1, 1, 2, 2, 1, 3, 4], dtype='category')
s = pd.Series([1, 1, 1, 2, 2, 1, 3, 4])
exp = pd.get_dummies(s, prefix='X', prefix_sep='-')
ds = self.spark.from_pandas(s)
res = pyspark.get_dummies(ds, prefix='X', prefix_sep='-')
self.assertPandasAlmostEqual(res.toPandas(), exp)
exp = pd.get_dummies(s, drop_first=True)
ds = self.spark.from_pandas(s)
res = pyspark.get_dummies(ds, drop_first=True)
self.assertPandasAlmostEqual(res.toPandas(), exp)
# nan
# s = pd.Series([1, 1, 1, 2, np.nan, 3, np.nan, 5], dtype='category')
s = pd.Series([1, 1, 1, 2, np.nan, 3, np.nan, 5])
exp = pd.get_dummies(s)
ds = self.spark.from_pandas(s)
res = pyspark.get_dummies(ds)
self.assertPandasAlmostEqual(res.toPandas(), exp)
# dummy_na
exp = pd.get_dummies(s, dummy_na=True)
ds = self.spark.from_pandas(s)
res = pyspark.get_dummies(ds, dummy_na=True)
self.assertPandasAlmostEqual(res.toPandas(), exp)
def test_get_dummies_object(self):
df = pd.DataFrame({
'a': [1, 2, 3, 4, 4, 3, 2, 1],
# 'a': pd.Categorical([1, 2, 3, 4, 4, 3, 2, 1]),
'b': list('abcdabcd'),
# 'c': pd.Categorical(list('abcdabcd')),
'c': list('abcdabcd')
})
ddf = self.spark.from_pandas(df)
# Explicitly exclude object columns
exp = pd.get_dummies(df, columns=['a', 'c'])
res = pyspark.get_dummies(ddf, columns=['a', 'c'])
self.assertPandasAlmostEqual(res.toPandas(), exp)
exp = pd.get_dummies(df)
res = pyspark.get_dummies(ddf)
self.assertPandasAlmostEqual(res.toPandas(), exp)
exp = pd.get_dummies(df.b)
res = pyspark.get_dummies(ddf.b)
self.assertPandasAlmostEqual(res.toPandas(), exp)
exp = pd.get_dummies(df, columns=['b'])
res = pyspark.get_dummies(ddf, columns=['b'])
self.assertPandasAlmostEqual(res.toPandas(), exp)
def test_get_dummies_decimal(self):
df = pd.DataFrame({'d': [Decimal(1.0), Decimal(2.0), Decimal(1)]})
ddf = self.spark.from_pandas(df)
exp = pd.get_dummies(df)
res = pyspark.get_dummies(ddf)
self.assertPandasAlmostEqual(res.toPandas(), exp)
exp = pd.get_dummies(df.d)
res = pyspark.get_dummies(ddf.d)
self.assertPandasAlmostEqual(res.toPandas(), exp)
def test_get_dummies_boolean(self):
df = pd.DataFrame({'b': [True, False, True]})
ddf = self.spark.from_pandas(df)
exp = pd.get_dummies(df)
res = pyspark.get_dummies(ddf)
self.assertPandasAlmostEqual(res.toPandas(), exp)
exp = pd.get_dummies(df.b)
res = pyspark.get_dummies(ddf.b)
self.assertPandasAlmostEqual(res.toPandas(), exp)
def test_get_dummies_dtype(self):
df = pd.DataFrame({
# "A": pd.Categorical(['a', 'b', 'a'], categories=['a', 'b', 'c']),
"A": ['a', 'b', 'a'],
"B": [0, 0, 1],
})
ddf = self.spark.from_pandas(df)
if LooseVersion("0.23.0") <= LooseVersion(pd.__version__):
exp = pd.get_dummies(df, dtype='float64')
else:
exp = pd.get_dummies(df)
exp = exp.astype({'A_a': 'float64', 'A_b': 'float64'})
res = pyspark.get_dummies(ddf, dtype='float64')
self.assertPandasAlmostEqual(exp, res.toPandas())
def test_get_dummies_prefix(self):
df = pd.DataFrame({
"A": ['a', 'b', 'a'],
"B": ['b', 'a', 'c'],
"D": [0, 0, 1],
})
ddf = self.spark.from_pandas(df)
exp = pd.get_dummies(df, prefix=['foo', 'bar'])
res = pyspark.get_dummies(ddf, prefix=['foo', 'bar'])
self.assertPandasAlmostEqual(res.toPandas(), exp)
exp = pd.get_dummies(df, prefix=['foo'], columns=['B'])
res = pyspark.get_dummies(ddf, prefix=['foo'], columns=['B'])
self.assertPandasAlmostEqual(res.toPandas(), exp)
with self.assertRaisesRegex(ValueError, "string types"):
pyspark.get_dummies(ddf, prefix='foo')
with self.assertRaisesRegex(ValueError,
"Length of 'prefix' \\(1\\) .* \\(2\\)"):
pyspark.get_dummies(ddf, prefix=['foo'])
with self.assertRaisesRegex(ValueError,
"Length of 'prefix' \\(2\\) .* \\(1\\)"):
pyspark.get_dummies(ddf, prefix=['foo', 'bar'], columns=['B'])
s = pd.Series([1, 1, 1, 2, 2, 1, 3, 4], name='A')
ds = self.spark.from_pandas(s)
exp = pd.get_dummies(s, prefix='foo')
res = pyspark.get_dummies(ds, prefix='foo')
self.assertPandasAlmostEqual(res.toPandas(), exp)
# columns are ignored.
exp = pd.get_dummies(s, prefix=['foo'], columns=['B'])
res = pyspark.get_dummies(ds, prefix=['foo'], columns=['B'])
self.assertPandasAlmostEqual(res.toPandas(), exp)
def test_get_dummies(self):
for data in [
pd.Series([1, 1, 1, 2, 2, 1, 3, 4]),
# pd.Series([1, 1, 1, 2, 2, 1, 3, 4], dtype='category'),
# pd.Series(pd.Categorical([1, 1, 1, 2, 2, 1, 3, 4], categories=[4, 3, 2, 1])),
pd.DataFrame({
'a': [1, 2, 3, 4, 4, 3, 2, 1],
# 'b': pd.Categorical(list('abcdabcd')),
'b': list('abcdabcd')
})
]:
exp = pd.get_dummies(data)
ddata = self.spark.from_pandas(data)
res = pyspark.get_dummies(ddata)
self.assertPandasAlmostEqual(res.toPandas(), exp)
