Python pandas.util.testing.SubclassedDataFrame() Examples
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code examples of pandas.util.testing.SubclassedDataFrame().
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Example #1
| Source File: test_subclass.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_subclassed_wide_to_long(self):
# GH 9762
np.random.seed(123)
x = np.random.randn(3)
df = tm.SubclassedDataFrame({
"A1970": {0: "a", 1: "b", 2: "c"},
"A1980": {0: "d", 1: "e", 2: "f"},
"B1970": {0: 2.5, 1: 1.2, 2: .7},
"B1980": {0: 3.2, 1: 1.3, 2: .1},
"X": dict(zip(range(3), x))})
df["id"] = df.index
exp_data = {"X": x.tolist() + x.tolist(),
"A": ['a', 'b', 'c', 'd', 'e', 'f'],
"B": [2.5, 1.2, 0.7, 3.2, 1.3, 0.1],
"year": [1970, 1970, 1970, 1980, 1980, 1980],
"id": [0, 1, 2, 0, 1, 2]}
expected = tm.SubclassedDataFrame(exp_data)
expected = expected.set_index(['id', 'year'])[["X", "A", "B"]]
long_frame = pd.wide_to_long(df, ["A", "B"], i="id", j="year")
tm.assert_frame_equal(long_frame, expected)
Example #2
| Source File: test_subclass.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_subclassed_wide_to_long(self):
# GH 9762
np.random.seed(123)
x = np.random.randn(3)
df = tm.SubclassedDataFrame({
"A1970": {0: "a", 1: "b", 2: "c"},
"A1980": {0: "d", 1: "e", 2: "f"},
"B1970": {0: 2.5, 1: 1.2, 2: .7},
"B1980": {0: 3.2, 1: 1.3, 2: .1},
"X": dict(zip(range(3), x))})
df["id"] = df.index
exp_data = {"X": x.tolist() + x.tolist(),
"A": ['a', 'b', 'c', 'd', 'e', 'f'],
"B": [2.5, 1.2, 0.7, 3.2, 1.3, 0.1],
"year": [1970, 1970, 1970, 1980, 1980, 1980],
"id": [0, 1, 2, 0, 1, 2]}
expected = tm.SubclassedDataFrame(exp_data)
expected = expected.set_index(['id', 'year'])[["X", "A", "B"]]
long_frame = pd.wide_to_long(df, ["A", "B"], i="id", j="year")
tm.assert_frame_equal(long_frame, expected)
Example #3
| Source File: test_subclass.py From vnpy_crypto with MIT License | 6 votes |
|
def test_subclass_pivot(self):
# GH 15564
df = tm.SubclassedDataFrame({
'index': ['A', 'B', 'C', 'C', 'B', 'A'],
'columns': ['One', 'One', 'One', 'Two', 'Two', 'Two'],
'values': [1., 2., 3., 3., 2., 1.]})
pivoted = df.pivot(
index='index', columns='columns', values='values')
expected = tm.SubclassedDataFrame({
'One': {'A': 1., 'B': 2., 'C': 3.},
'Two': {'A': 1., 'B': 2., 'C': 3.}})
expected.index.name, expected.columns.name = 'index', 'columns'
tm.assert_frame_equal(pivoted, expected)
Example #4
| Source File: test_subclass.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def test_dataframe_metadata(self):
df = tm.SubclassedDataFrame({'X': [1, 2, 3], 'Y': [1, 2, 3]},
index=['a', 'b', 'c'])
df.testattr = 'XXX'
assert df.testattr == 'XXX'
assert df[['X']].testattr == 'XXX'
assert df.loc[['a', 'b'], :].testattr == 'XXX'
assert df.iloc[[0, 1], :].testattr == 'XXX'
# see gh-9776
assert df.iloc[0:1, :].testattr == 'XXX'
# see gh-10553
unpickled = tm.round_trip_pickle(df)
tm.assert_frame_equal(df, unpickled)
assert df._metadata == unpickled._metadata
assert df.testattr == unpickled.testattr
Example #5
| Source File: test_subclass.py From vnpy_crypto with MIT License | 6 votes |
|
def test_subclassed_melt(self):
# GH 15564
cheese = tm.SubclassedDataFrame({
'first': ['John', 'Mary'],
'last': ['Doe', 'Bo'],
'height': [5.5, 6.0],
'weight': [130, 150]})
melted = pd.melt(cheese, id_vars=['first', 'last'])
expected = tm.SubclassedDataFrame([
['John', 'Doe', 'height', 5.5],
['Mary', 'Bo', 'height', 6.0],
['John', 'Doe', 'weight', 130],
['Mary', 'Bo', 'weight', 150]],
columns=['first', 'last', 'variable', 'value'])
tm.assert_frame_equal(melted, expected)
Example #6
| Source File: test_subclass.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def test_subclass_align(self):
# GH 12983
df1 = tm.SubclassedDataFrame({'a': [1, 3, 5],
'b': [1, 3, 5]}, index=list('ACE'))
df2 = tm.SubclassedDataFrame({'c': [1, 2, 4],
'd': [1, 2, 4]}, index=list('ABD'))
res1, res2 = df1.align(df2, axis=0)
exp1 = tm.SubclassedDataFrame({'a': [1, np.nan, 3, np.nan, 5],
'b': [1, np.nan, 3, np.nan, 5]},
index=list('ABCDE'))
exp2 = tm.SubclassedDataFrame({'c': [1, 2, np.nan, 4, np.nan],
'd': [1, 2, np.nan, 4, np.nan]},
index=list('ABCDE'))
assert isinstance(res1, tm.SubclassedDataFrame)
tm.assert_frame_equal(res1, exp1)
assert isinstance(res2, tm.SubclassedDataFrame)
tm.assert_frame_equal(res2, exp2)
res1, res2 = df1.a.align(df2.c)
assert isinstance(res1, tm.SubclassedSeries)
tm.assert_series_equal(res1, exp1.a)
assert isinstance(res2, tm.SubclassedSeries)
tm.assert_series_equal(res2, exp2.c)
Example #7
| Source File: test_subclass.py From vnpy_crypto with MIT License | 6 votes |
|
def test_subclassed_wide_to_long(self):
# GH 9762
np.random.seed(123)
x = np.random.randn(3)
df = tm.SubclassedDataFrame({
"A1970": {0: "a", 1: "b", 2: "c"},
"A1980": {0: "d", 1: "e", 2: "f"},
"B1970": {0: 2.5, 1: 1.2, 2: .7},
"B1980": {0: 3.2, 1: 1.3, 2: .1},
"X": dict(zip(range(3), x))})
df["id"] = df.index
exp_data = {"X": x.tolist() + x.tolist(),
"A": ['a', 'b', 'c', 'd', 'e', 'f'],
"B": [2.5, 1.2, 0.7, 3.2, 1.3, 0.1],
"year": [1970, 1970, 1970, 1980, 1980, 1980],
"id": [0, 1, 2, 0, 1, 2]}
expected = tm.SubclassedDataFrame(exp_data)
expected = expected.set_index(['id', 'year'])[["X", "A", "B"]]
long_frame = pd.wide_to_long(df, ["A", "B"], i="id", j="year")
tm.assert_frame_equal(long_frame, expected)
Example #8
| Source File: test_subclass.py From vnpy_crypto with MIT License | 6 votes |
|
def test_subclass_align(self):
# GH 12983
df1 = tm.SubclassedDataFrame({'a': [1, 3, 5],
'b': [1, 3, 5]}, index=list('ACE'))
df2 = tm.SubclassedDataFrame({'c': [1, 2, 4],
'd': [1, 2, 4]}, index=list('ABD'))
res1, res2 = df1.align(df2, axis=0)
exp1 = tm.SubclassedDataFrame({'a': [1, np.nan, 3, np.nan, 5],
'b': [1, np.nan, 3, np.nan, 5]},
index=list('ABCDE'))
exp2 = tm.SubclassedDataFrame({'c': [1, 2, np.nan, 4, np.nan],
'd': [1, 2, np.nan, 4, np.nan]},
index=list('ABCDE'))
assert isinstance(res1, tm.SubclassedDataFrame)
tm.assert_frame_equal(res1, exp1)
assert isinstance(res2, tm.SubclassedDataFrame)
tm.assert_frame_equal(res2, exp2)
res1, res2 = df1.a.align(df2.c)
assert isinstance(res1, tm.SubclassedSeries)
tm.assert_series_equal(res1, exp1.a)
assert isinstance(res2, tm.SubclassedSeries)
tm.assert_series_equal(res2, exp2.c)
Example #9
| Source File: test_subclass.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_subclassed_melt(self):
# GH 15564
cheese = tm.SubclassedDataFrame({
'first': ['John', 'Mary'],
'last': ['Doe', 'Bo'],
'height': [5.5, 6.0],
'weight': [130, 150]})
melted = pd.melt(cheese, id_vars=['first', 'last'])
expected = tm.SubclassedDataFrame([
['John', 'Doe', 'height', 5.5],
['Mary', 'Bo', 'height', 6.0],
['John', 'Doe', 'weight', 130],
['Mary', 'Bo', 'weight', 150]],
columns=['first', 'last', 'variable', 'value'])
tm.assert_frame_equal(melted, expected)
Example #10
| Source File: test_subclass.py From vnpy_crypto with MIT License | 6 votes |
|
def test_dataframe_metadata(self):
df = tm.SubclassedDataFrame({'X': [1, 2, 3], 'Y': [1, 2, 3]},
index=['a', 'b', 'c'])
df.testattr = 'XXX'
assert df.testattr == 'XXX'
assert df[['X']].testattr == 'XXX'
assert df.loc[['a', 'b'], :].testattr == 'XXX'
assert df.iloc[[0, 1], :].testattr == 'XXX'
# see gh-9776
assert df.iloc[0:1, :].testattr == 'XXX'
# see gh-10553
unpickled = tm.round_trip_pickle(df)
tm.assert_frame_equal(df, unpickled)
assert df._metadata == unpickled._metadata
assert df.testattr == unpickled.testattr
Example #11
| Source File: test_subclass.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_subclass_pivot(self):
# GH 15564
df = tm.SubclassedDataFrame({
'index': ['A', 'B', 'C', 'C', 'B', 'A'],
'columns': ['One', 'One', 'One', 'Two', 'Two', 'Two'],
'values': [1., 2., 3., 3., 2., 1.]})
pivoted = df.pivot(
index='index', columns='columns', values='values')
expected = tm.SubclassedDataFrame({
'One': {'A': 1., 'B': 2., 'C': 3.},
'Two': {'A': 1., 'B': 2., 'C': 3.}})
expected.index.name, expected.columns.name = 'index', 'columns'
tm.assert_frame_equal(pivoted, expected)
Example #12
| Source File: test_subclass.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_dataframe_metadata(self):
df = tm.SubclassedDataFrame({'X': [1, 2, 3], 'Y': [1, 2, 3]},
index=['a', 'b', 'c'])
df.testattr = 'XXX'
assert df.testattr == 'XXX'
assert df[['X']].testattr == 'XXX'
assert df.loc[['a', 'b'], :].testattr == 'XXX'
assert df.iloc[[0, 1], :].testattr == 'XXX'
# see gh-9776
assert df.iloc[0:1, :].testattr == 'XXX'
# see gh-10553
unpickled = tm.round_trip_pickle(df)
tm.assert_frame_equal(df, unpickled)
assert df._metadata == unpickled._metadata
assert df.testattr == unpickled.testattr
Example #13
| Source File: test_subclass.py From recruit with Apache License 2.0 | 6 votes |
|
def test_subclassed_wide_to_long(self):
# GH 9762
np.random.seed(123)
x = np.random.randn(3)
df = tm.SubclassedDataFrame({
"A1970": {0: "a", 1: "b", 2: "c"},
"A1980": {0: "d", 1: "e", 2: "f"},
"B1970": {0: 2.5, 1: 1.2, 2: .7},
"B1980": {0: 3.2, 1: 1.3, 2: .1},
"X": dict(zip(range(3), x))})
df["id"] = df.index
exp_data = {"X": x.tolist() + x.tolist(),
"A": ['a', 'b', 'c', 'd', 'e', 'f'],
"B": [2.5, 1.2, 0.7, 3.2, 1.3, 0.1],
"year": [1970, 1970, 1970, 1980, 1980, 1980],
"id": [0, 1, 2, 0, 1, 2]}
expected = tm.SubclassedDataFrame(exp_data)
expected = expected.set_index(['id', 'year'])[["X", "A", "B"]]
long_frame = pd.wide_to_long(df, ["A", "B"], i="id", j="year")
tm.assert_frame_equal(long_frame, expected)
Example #14
| Source File: test_subclass.py From recruit with Apache License 2.0 | 6 votes |
|
def test_subclassed_melt(self):
# GH 15564
cheese = tm.SubclassedDataFrame({
'first': ['John', 'Mary'],
'last': ['Doe', 'Bo'],
'height': [5.5, 6.0],
'weight': [130, 150]})
melted = pd.melt(cheese, id_vars=['first', 'last'])
expected = tm.SubclassedDataFrame([
['John', 'Doe', 'height', 5.5],
['Mary', 'Bo', 'height', 6.0],
['John', 'Doe', 'weight', 130],
['Mary', 'Bo', 'weight', 150]],
columns=['first', 'last', 'variable', 'value'])
tm.assert_frame_equal(melted, expected)
Example #15
| Source File: test_subclass.py From recruit with Apache License 2.0 | 6 votes |
|
def test_subclass_pivot(self):
# GH 15564
df = tm.SubclassedDataFrame({
'index': ['A', 'B', 'C', 'C', 'B', 'A'],
'columns': ['One', 'One', 'One', 'Two', 'Two', 'Two'],
'values': [1., 2., 3., 3., 2., 1.]})
pivoted = df.pivot(
index='index', columns='columns', values='values')
expected = tm.SubclassedDataFrame({
'One': {'A': 1., 'B': 2., 'C': 3.},
'Two': {'A': 1., 'B': 2., 'C': 3.}})
expected.index.name, expected.columns.name = 'index', 'columns'
tm.assert_frame_equal(pivoted, expected)
Example #16
| Source File: test_subclass.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_subclass_align(self):
# GH 12983
df1 = tm.SubclassedDataFrame({'a': [1, 3, 5],
'b': [1, 3, 5]}, index=list('ACE'))
df2 = tm.SubclassedDataFrame({'c': [1, 2, 4],
'd': [1, 2, 4]}, index=list('ABD'))
res1, res2 = df1.align(df2, axis=0)
exp1 = tm.SubclassedDataFrame({'a': [1, np.nan, 3, np.nan, 5],
'b': [1, np.nan, 3, np.nan, 5]},
index=list('ABCDE'))
exp2 = tm.SubclassedDataFrame({'c': [1, 2, np.nan, 4, np.nan],
'd': [1, 2, np.nan, 4, np.nan]},
index=list('ABCDE'))
assert isinstance(res1, tm.SubclassedDataFrame)
tm.assert_frame_equal(res1, exp1)
assert isinstance(res2, tm.SubclassedDataFrame)
tm.assert_frame_equal(res2, exp2)
res1, res2 = df1.a.align(df2.c)
assert isinstance(res1, tm.SubclassedSeries)
tm.assert_series_equal(res1, exp1.a)
assert isinstance(res2, tm.SubclassedSeries)
tm.assert_series_equal(res2, exp2.c)
Example #17
| Source File: test_subclass.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_dataframe_metadata(self):
df = tm.SubclassedDataFrame({'X': [1, 2, 3], 'Y': [1, 2, 3]},
index=['a', 'b', 'c'])
df.testattr = 'XXX'
assert df.testattr == 'XXX'
assert df[['X']].testattr == 'XXX'
assert df.loc[['a', 'b'], :].testattr == 'XXX'
assert df.iloc[[0, 1], :].testattr == 'XXX'
# see gh-9776
assert df.iloc[0:1, :].testattr == 'XXX'
# see gh-10553
unpickled = tm.round_trip_pickle(df)
tm.assert_frame_equal(df, unpickled)
assert df._metadata == unpickled._metadata
assert df.testattr == unpickled.testattr
Example #18
| Source File: test_subclass.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_subclass_align(self):
# GH 12983
df1 = tm.SubclassedDataFrame({'a': [1, 3, 5],
'b': [1, 3, 5]}, index=list('ACE'))
df2 = tm.SubclassedDataFrame({'c': [1, 2, 4],
'd': [1, 2, 4]}, index=list('ABD'))
res1, res2 = df1.align(df2, axis=0)
exp1 = tm.SubclassedDataFrame({'a': [1, np.nan, 3, np.nan, 5],
'b': [1, np.nan, 3, np.nan, 5]},
index=list('ABCDE'))
exp2 = tm.SubclassedDataFrame({'c': [1, 2, np.nan, 4, np.nan],
'd': [1, 2, np.nan, 4, np.nan]},
index=list('ABCDE'))
assert isinstance(res1, tm.SubclassedDataFrame)
tm.assert_frame_equal(res1, exp1)
assert isinstance(res2, tm.SubclassedDataFrame)
tm.assert_frame_equal(res2, exp2)
res1, res2 = df1.a.align(df2.c)
assert isinstance(res1, tm.SubclassedSeries)
tm.assert_series_equal(res1, exp1.a)
assert isinstance(res2, tm.SubclassedSeries)
tm.assert_series_equal(res2, exp2.c)
Example #19
| Source File: test_subclass.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_subclass_pivot(self):
# GH 15564
df = tm.SubclassedDataFrame({
'index': ['A', 'B', 'C', 'C', 'B', 'A'],
'columns': ['One', 'One', 'One', 'Two', 'Two', 'Two'],
'values': [1., 2., 3., 3., 2., 1.]})
pivoted = df.pivot(
index='index', columns='columns', values='values')
expected = tm.SubclassedDataFrame({
'One': {'A': 1., 'B': 2., 'C': 3.},
'Two': {'A': 1., 'B': 2., 'C': 3.}})
expected.index.name, expected.columns.name = 'index', 'columns'
tm.assert_frame_equal(pivoted, expected)
Example #20
| Source File: test_subclass.py From recruit with Apache License 2.0 | 6 votes |
|
def test_subclass_align(self):
# GH 12983
df1 = tm.SubclassedDataFrame({'a': [1, 3, 5],
'b': [1, 3, 5]}, index=list('ACE'))
df2 = tm.SubclassedDataFrame({'c': [1, 2, 4],
'd': [1, 2, 4]}, index=list('ABD'))
res1, res2 = df1.align(df2, axis=0)
exp1 = tm.SubclassedDataFrame({'a': [1, np.nan, 3, np.nan, 5],
'b': [1, np.nan, 3, np.nan, 5]},
index=list('ABCDE'))
exp2 = tm.SubclassedDataFrame({'c': [1, 2, np.nan, 4, np.nan],
'd': [1, 2, np.nan, 4, np.nan]},
index=list('ABCDE'))
assert isinstance(res1, tm.SubclassedDataFrame)
tm.assert_frame_equal(res1, exp1)
assert isinstance(res2, tm.SubclassedDataFrame)
tm.assert_frame_equal(res2, exp2)
res1, res2 = df1.a.align(df2.c)
assert isinstance(res1, tm.SubclassedSeries)
tm.assert_series_equal(res1, exp1.a)
assert isinstance(res2, tm.SubclassedSeries)
tm.assert_series_equal(res2, exp2.c)
Example #21
| Source File: test_subclass.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_subclassed_melt(self):
# GH 15564
cheese = tm.SubclassedDataFrame({
'first': ['John', 'Mary'],
'last': ['Doe', 'Bo'],
'height': [5.5, 6.0],
'weight': [130, 150]})
melted = pd.melt(cheese, id_vars=['first', 'last'])
expected = tm.SubclassedDataFrame([
['John', 'Doe', 'height', 5.5],
['Mary', 'Bo', 'height', 6.0],
['John', 'Doe', 'weight', 130],
['Mary', 'Bo', 'weight', 150]],
columns=['first', 'last', 'variable', 'value'])
tm.assert_frame_equal(melted, expected)
Example #22
| Source File: test_subclass.py From recruit with Apache License 2.0 | 6 votes |
|
def test_dataframe_metadata(self):
df = tm.SubclassedDataFrame({'X': [1, 2, 3], 'Y': [1, 2, 3]},
index=['a', 'b', 'c'])
df.testattr = 'XXX'
assert df.testattr == 'XXX'
assert df[['X']].testattr == 'XXX'
assert df.loc[['a', 'b'], :].testattr == 'XXX'
assert df.iloc[[0, 1], :].testattr == 'XXX'
# see gh-9776
assert df.iloc[0:1, :].testattr == 'XXX'
# see gh-10553
unpickled = tm.round_trip_pickle(df)
tm.assert_frame_equal(df, unpickled)
assert df._metadata == unpickled._metadata
assert df.testattr == unpickled.testattr
Example #23
| Source File: test_subclass.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_indexing_sliced(self):
# GH 11559
df = tm.SubclassedDataFrame({'X': [1, 2, 3],
'Y': [4, 5, 6],
'Z': [7, 8, 9]},
index=['a', 'b', 'c'])
res = df.loc[:, 'X']
exp = tm.SubclassedSeries([1, 2, 3], index=list('abc'), name='X')
tm.assert_series_equal(res, exp)
assert isinstance(res, tm.SubclassedSeries)
res = df.iloc[:, 1]
exp = tm.SubclassedSeries([4, 5, 6], index=list('abc'), name='Y')
tm.assert_series_equal(res, exp)
assert isinstance(res, tm.SubclassedSeries)
res = df.loc[:, 'Z']
exp = tm.SubclassedSeries([7, 8, 9], index=list('abc'), name='Z')
tm.assert_series_equal(res, exp)
assert isinstance(res, tm.SubclassedSeries)
res = df.loc['a', :]
exp = tm.SubclassedSeries([1, 4, 7], index=list('XYZ'), name='a')
tm.assert_series_equal(res, exp)
assert isinstance(res, tm.SubclassedSeries)
res = df.iloc[1, :]
exp = tm.SubclassedSeries([2, 5, 8], index=list('XYZ'), name='b')
tm.assert_series_equal(res, exp)
assert isinstance(res, tm.SubclassedSeries)
res = df.loc['c', :]
exp = tm.SubclassedSeries([3, 6, 9], index=list('XYZ'), name='c')
tm.assert_series_equal(res, exp)
assert isinstance(res, tm.SubclassedSeries)
Example #24
| Source File: test_subclass.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_subclass_stack(self):
# GH 15564
df = tm.SubclassedDataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]],
index=['a', 'b', 'c'],
columns=['X', 'Y', 'Z'])
res = df.stack()
exp = tm.SubclassedSeries(
[1, 2, 3, 4, 5, 6, 7, 8, 9],
index=[list('aaabbbccc'), list('XYZXYZXYZ')])
tm.assert_series_equal(res, exp)
Example #25
| Source File: test_subclass.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_subclass_iterrows(self):
# GH 13977
df = tm.SubclassedDataFrame({'a': [1]})
for i, row in df.iterrows():
assert isinstance(row, tm.SubclassedSeries)
tm.assert_series_equal(row, df.loc[i])
Example #26
| Source File: test_subclass.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_subclass_unstack(self):
# GH 15564
df = tm.SubclassedDataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]],
index=['a', 'b', 'c'],
columns=['X', 'Y', 'Z'])
res = df.unstack()
exp = tm.SubclassedSeries(
[1, 4, 7, 2, 5, 8, 3, 6, 9],
index=[list('XXXYYYZZZ'), list('abcabcabc')])
tm.assert_series_equal(res, exp)
Example #27
| Source File: test_subclass.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_subclass_stack(self):
# GH 15564
df = tm.SubclassedDataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]],
index=['a', 'b', 'c'],
columns=['X', 'Y', 'Z'])
res = df.stack()
exp = tm.SubclassedSeries(
[1, 2, 3, 4, 5, 6, 7, 8, 9],
index=[list('aaabbbccc'), list('XYZXYZXYZ')])
tm.assert_series_equal(res, exp)
Example #28
| Source File: test_subclass.py From recruit with Apache License 2.0 | 5 votes |
|
def test_subclass_unstack(self):
# GH 15564
s = tm.SubclassedSeries(
[1, 2, 3, 4], index=[list('aabb'), list('xyxy')])
res = s.unstack()
exp = tm.SubclassedDataFrame(
{'x': [1, 3], 'y': [2, 4]}, index=['a', 'b'])
tm.assert_frame_equal(res, exp)
Example #29
| Source File: test_subclass.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_subclass_unstack(self):
# GH 15564
df = tm.SubclassedDataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]],
index=['a', 'b', 'c'],
columns=['X', 'Y', 'Z'])
res = df.unstack()
exp = tm.SubclassedSeries(
[1, 4, 7, 2, 5, 8, 3, 6, 9],
index=[list('XXXYYYZZZ'), list('abcabcabc')])
tm.assert_series_equal(res, exp)
Example #30
| Source File: test_subclass.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_subclass_unstack_multi_mixed(self):
# GH 15564
df = tm.SubclassedDataFrame([
[10, 11, 12.0, 13.0],
[20, 21, 22.0, 23.0],
[30, 31, 32.0, 33.0],
[40, 41, 42.0, 43.0]],
index=MultiIndex.from_tuples(
list(zip(list('AABB'), list('cdcd'))),
names=['aaa', 'ccc']),
columns=MultiIndex.from_tuples(
list(zip(list('WWXX'), list('yzyz'))),
names=['www', 'yyy']))
exp = tm.SubclassedDataFrame([
[10, 20, 11, 21, 12.0, 22.0, 13.0, 23.0],
[30, 40, 31, 41, 32.0, 42.0, 33.0, 43.0]],
index=Index(['A', 'B'], name='aaa'),
columns=MultiIndex.from_tuples(list(zip(
list('WWWWXXXX'), list('yyzzyyzz'), list('cdcdcdcd'))),
names=['www', 'yyy', 'ccc']))
res = df.unstack()
tm.assert_frame_equal(res, exp)
res = df.unstack('ccc')
tm.assert_frame_equal(res, exp)
exp = tm.SubclassedDataFrame([
[10, 30, 11, 31, 12.0, 32.0, 13.0, 33.0],
[20, 40, 21, 41, 22.0, 42.0, 23.0, 43.0]],
index=Index(['c', 'd'], name='ccc'),
columns=MultiIndex.from_tuples(list(zip(
list('WWWWXXXX'), list('yyzzyyzz'), list('ABABABAB'))),
names=['www', 'yyy', 'aaa']))
res = df.unstack('aaa')
tm.assert_frame_equal(res, exp)
