You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
164 lines
4.9 KiB
164 lines
4.9 KiB
6 months ago
|
import numpy as np
|
||
|
|
||
|
import pandas as pd
|
||
|
import pandas._testing as tm
|
||
|
|
||
|
|
||
|
def test_group_by_copy():
|
||
|
# GH#44803
|
||
|
df = pd.DataFrame(
|
||
|
{
|
||
|
"name": ["Alice", "Bob", "Carl"],
|
||
|
"age": [20, 21, 20],
|
||
|
}
|
||
|
).set_index("name")
|
||
|
|
||
|
msg = "DataFrameGroupBy.apply operated on the grouping columns"
|
||
|
with tm.assert_produces_warning(DeprecationWarning, match=msg):
|
||
|
grp_by_same_value = df.groupby(["age"], group_keys=False).apply(
|
||
|
lambda group: group
|
||
|
)
|
||
|
msg = "DataFrameGroupBy.apply operated on the grouping columns"
|
||
|
with tm.assert_produces_warning(DeprecationWarning, match=msg):
|
||
|
grp_by_copy = df.groupby(["age"], group_keys=False).apply(
|
||
|
lambda group: group.copy()
|
||
|
)
|
||
|
tm.assert_frame_equal(grp_by_same_value, grp_by_copy)
|
||
|
|
||
|
|
||
|
def test_mutate_groups():
|
||
|
# GH3380
|
||
|
|
||
|
df = pd.DataFrame(
|
||
|
{
|
||
|
"cat1": ["a"] * 8 + ["b"] * 6,
|
||
|
"cat2": ["c"] * 2
|
||
|
+ ["d"] * 2
|
||
|
+ ["e"] * 2
|
||
|
+ ["f"] * 2
|
||
|
+ ["c"] * 2
|
||
|
+ ["d"] * 2
|
||
|
+ ["e"] * 2,
|
||
|
"cat3": [f"g{x}" for x in range(1, 15)],
|
||
|
"val": np.random.default_rng(2).integers(100, size=14),
|
||
|
}
|
||
|
)
|
||
|
|
||
|
def f_copy(x):
|
||
|
x = x.copy()
|
||
|
x["rank"] = x.val.rank(method="min")
|
||
|
return x.groupby("cat2")["rank"].min()
|
||
|
|
||
|
def f_no_copy(x):
|
||
|
x["rank"] = x.val.rank(method="min")
|
||
|
return x.groupby("cat2")["rank"].min()
|
||
|
|
||
|
msg = "DataFrameGroupBy.apply operated on the grouping columns"
|
||
|
with tm.assert_produces_warning(DeprecationWarning, match=msg):
|
||
|
grpby_copy = df.groupby("cat1").apply(f_copy)
|
||
|
with tm.assert_produces_warning(DeprecationWarning, match=msg):
|
||
|
grpby_no_copy = df.groupby("cat1").apply(f_no_copy)
|
||
|
tm.assert_series_equal(grpby_copy, grpby_no_copy)
|
||
|
|
||
|
|
||
|
def test_no_mutate_but_looks_like():
|
||
|
# GH 8467
|
||
|
# first show's mutation indicator
|
||
|
# second does not, but should yield the same results
|
||
|
df = pd.DataFrame({"key": [1, 1, 1, 2, 2, 2, 3, 3, 3], "value": range(9)})
|
||
|
|
||
|
msg = "DataFrameGroupBy.apply operated on the grouping columns"
|
||
|
with tm.assert_produces_warning(DeprecationWarning, match=msg):
|
||
|
result1 = df.groupby("key", group_keys=True).apply(lambda x: x[:].key)
|
||
|
with tm.assert_produces_warning(DeprecationWarning, match=msg):
|
||
|
result2 = df.groupby("key", group_keys=True).apply(lambda x: x.key)
|
||
|
tm.assert_series_equal(result1, result2)
|
||
|
|
||
|
|
||
|
def test_apply_function_with_indexing(warn_copy_on_write):
|
||
|
# GH: 33058
|
||
|
df = pd.DataFrame(
|
||
|
{"col1": ["A", "A", "A", "B", "B", "B"], "col2": [1, 2, 3, 4, 5, 6]}
|
||
|
)
|
||
|
|
||
|
def fn(x):
|
||
|
x.loc[x.index[-1], "col2"] = 0
|
||
|
return x.col2
|
||
|
|
||
|
msg = "DataFrameGroupBy.apply operated on the grouping columns"
|
||
|
with tm.assert_produces_warning(
|
||
|
DeprecationWarning, match=msg, raise_on_extra_warnings=not warn_copy_on_write
|
||
|
):
|
||
|
result = df.groupby(["col1"], as_index=False).apply(fn)
|
||
|
expected = pd.Series(
|
||
|
[1, 2, 0, 4, 5, 0],
|
||
|
index=pd.MultiIndex.from_tuples(
|
||
|
[(0, 0), (0, 1), (0, 2), (1, 3), (1, 4), (1, 5)]
|
||
|
),
|
||
|
name="col2",
|
||
|
)
|
||
|
tm.assert_series_equal(result, expected)
|
||
|
|
||
|
|
||
|
def test_apply_mutate_columns_multiindex():
|
||
|
# GH 12652
|
||
|
df = pd.DataFrame(
|
||
|
{
|
||
|
("C", "julian"): [1, 2, 3],
|
||
|
("B", "geoffrey"): [1, 2, 3],
|
||
|
("A", "julian"): [1, 2, 3],
|
||
|
("B", "julian"): [1, 2, 3],
|
||
|
("A", "geoffrey"): [1, 2, 3],
|
||
|
("C", "geoffrey"): [1, 2, 3],
|
||
|
},
|
||
|
columns=pd.MultiIndex.from_tuples(
|
||
|
[
|
||
|
("A", "julian"),
|
||
|
("A", "geoffrey"),
|
||
|
("B", "julian"),
|
||
|
("B", "geoffrey"),
|
||
|
("C", "julian"),
|
||
|
("C", "geoffrey"),
|
||
|
]
|
||
|
),
|
||
|
)
|
||
|
|
||
|
def add_column(grouped):
|
||
|
name = grouped.columns[0][1]
|
||
|
grouped["sum", name] = grouped.sum(axis=1)
|
||
|
return grouped
|
||
|
|
||
|
msg = "DataFrame.groupby with axis=1 is deprecated"
|
||
|
with tm.assert_produces_warning(FutureWarning, match=msg):
|
||
|
gb = df.groupby(level=1, axis=1)
|
||
|
result = gb.apply(add_column)
|
||
|
expected = pd.DataFrame(
|
||
|
[
|
||
|
[1, 1, 1, 3, 1, 1, 1, 3],
|
||
|
[2, 2, 2, 6, 2, 2, 2, 6],
|
||
|
[
|
||
|
3,
|
||
|
3,
|
||
|
3,
|
||
|
9,
|
||
|
3,
|
||
|
3,
|
||
|
3,
|
||
|
9,
|
||
|
],
|
||
|
],
|
||
|
columns=pd.MultiIndex.from_tuples(
|
||
|
[
|
||
|
("geoffrey", "A", "geoffrey"),
|
||
|
("geoffrey", "B", "geoffrey"),
|
||
|
("geoffrey", "C", "geoffrey"),
|
||
|
("geoffrey", "sum", "geoffrey"),
|
||
|
("julian", "A", "julian"),
|
||
|
("julian", "B", "julian"),
|
||
|
("julian", "C", "julian"),
|
||
|
("julian", "sum", "julian"),
|
||
|
]
|
||
|
),
|
||
|
)
|
||
|
tm.assert_frame_equal(result, expected)
|