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import numpy as np
import pytest
import pandas.util._test_decorators as td
from pandas import (
DataFrame,
DatetimeIndex,
MultiIndex,
date_range,
)
import pandas._testing as tm
class TestMultiIndexPartial:
def test_getitem_partial_int(self):
# GH 12416
# with single item
l1 = [10, 20]
l2 = ["a", "b"]
df = DataFrame(index=range(2), columns=MultiIndex.from_product([l1, l2]))
expected = DataFrame(index=range(2), columns=l2)
result = df[20]
tm.assert_frame_equal(result, expected)
# with list
expected = DataFrame(
index=range(2), columns=MultiIndex.from_product([l1[1:], l2])
)
result = df[[20]]
tm.assert_frame_equal(result, expected)
# missing item:
with pytest.raises(KeyError, match="1"):
df[1]
with pytest.raises(KeyError, match=r"'\[1\] not in index'"):
df[[1]]
def test_series_slice_partial(self):
pass
def test_xs_partial(
self,
multiindex_dataframe_random_data,
multiindex_year_month_day_dataframe_random_data,
):
frame = multiindex_dataframe_random_data
ymd = multiindex_year_month_day_dataframe_random_data
result = frame.xs("foo")
result2 = frame.loc["foo"]
expected = frame.T["foo"].T
tm.assert_frame_equal(result, expected)
tm.assert_frame_equal(result, result2)
result = ymd.xs((2000, 4))
expected = ymd.loc[2000, 4]
tm.assert_frame_equal(result, expected)
# ex from #1796
index = MultiIndex(
levels=[["foo", "bar"], ["one", "two"], [-1, 1]],
codes=[
[0, 0, 0, 0, 1, 1, 1, 1],
[0, 0, 1, 1, 0, 0, 1, 1],
[0, 1, 0, 1, 0, 1, 0, 1],
],
)
df = DataFrame(
np.random.default_rng(2).standard_normal((8, 4)),
index=index,
columns=list("abcd"),
)
result = df.xs(("foo", "one"))
expected = df.loc["foo", "one"]
tm.assert_frame_equal(result, expected)
def test_getitem_partial(self, multiindex_year_month_day_dataframe_random_data):
ymd = multiindex_year_month_day_dataframe_random_data
ymd = ymd.T
result = ymd[2000, 2]
expected = ymd.reindex(columns=ymd.columns[ymd.columns.codes[1] == 1])
expected.columns = expected.columns.droplevel(0).droplevel(0)
tm.assert_frame_equal(result, expected)
def test_fancy_slice_partial(
self,
multiindex_dataframe_random_data,
multiindex_year_month_day_dataframe_random_data,
):
frame = multiindex_dataframe_random_data
result = frame.loc["bar":"baz"]
expected = frame[3:7]
tm.assert_frame_equal(result, expected)
ymd = multiindex_year_month_day_dataframe_random_data
result = ymd.loc[(2000, 2):(2000, 4)]
lev = ymd.index.codes[1]
expected = ymd[(lev >= 1) & (lev <= 3)]
tm.assert_frame_equal(result, expected)
def test_getitem_partial_column_select(self):
idx = MultiIndex(
codes=[[0, 0, 0], [0, 1, 1], [1, 0, 1]],
levels=[["a", "b"], ["x", "y"], ["p", "q"]],
)
df = DataFrame(np.random.default_rng(2).random((3, 2)), index=idx)
result = df.loc[("a", "y"), :]
expected = df.loc[("a", "y")]
tm.assert_frame_equal(result, expected)
result = df.loc[("a", "y"), [1, 0]]
expected = df.loc[("a", "y")][[1, 0]]
tm.assert_frame_equal(result, expected)
with pytest.raises(KeyError, match=r"\('a', 'foo'\)"):
df.loc[("a", "foo"), :]
# TODO(ArrayManager) rewrite test to not use .values
# exp.loc[2000, 4].values[:] select multiple columns -> .values is not a view
@td.skip_array_manager_invalid_test
def test_partial_set(
self,
multiindex_year_month_day_dataframe_random_data,
using_copy_on_write,
warn_copy_on_write,
):
# GH #397
ymd = multiindex_year_month_day_dataframe_random_data
df = ymd.copy()
exp = ymd.copy()
df.loc[2000, 4] = 0
exp.iloc[65:85] = 0
tm.assert_frame_equal(df, exp)
if using_copy_on_write:
with tm.raises_chained_assignment_error():
df["A"].loc[2000, 4] = 1
df.loc[(2000, 4), "A"] = 1
else:
with tm.raises_chained_assignment_error():
df["A"].loc[2000, 4] = 1
exp.iloc[65:85, 0] = 1
tm.assert_frame_equal(df, exp)
df.loc[2000] = 5
exp.iloc[:100] = 5
tm.assert_frame_equal(df, exp)
# this works...for now
with tm.raises_chained_assignment_error():
df["A"].iloc[14] = 5
if using_copy_on_write:
assert df["A"].iloc[14] == exp["A"].iloc[14]
else:
assert df["A"].iloc[14] == 5
@pytest.mark.parametrize("dtype", [int, float])
def test_getitem_intkey_leading_level(
self, multiindex_year_month_day_dataframe_random_data, dtype
):
# GH#33355 dont fall-back to positional when leading level is int
ymd = multiindex_year_month_day_dataframe_random_data
levels = ymd.index.levels
ymd.index = ymd.index.set_levels([levels[0].astype(dtype)] + levels[1:])
ser = ymd["A"]
mi = ser.index
assert isinstance(mi, MultiIndex)
if dtype is int:
assert mi.levels[0].dtype == np.dtype(int)
else:
assert mi.levels[0].dtype == np.float64
assert 14 not in mi.levels[0]
assert not mi.levels[0]._should_fallback_to_positional
assert not mi._should_fallback_to_positional
with pytest.raises(KeyError, match="14"):
ser[14]
# ---------------------------------------------------------------------
def test_setitem_multiple_partial(self, multiindex_dataframe_random_data):
frame = multiindex_dataframe_random_data
expected = frame.copy()
result = frame.copy()
result.loc[["foo", "bar"]] = 0
expected.loc["foo"] = 0
expected.loc["bar"] = 0
tm.assert_frame_equal(result, expected)
expected = frame.copy()
result = frame.copy()
result.loc["foo":"bar"] = 0
expected.loc["foo"] = 0
expected.loc["bar"] = 0
tm.assert_frame_equal(result, expected)
expected = frame["A"].copy()
result = frame["A"].copy()
result.loc[["foo", "bar"]] = 0
expected.loc["foo"] = 0
expected.loc["bar"] = 0
tm.assert_series_equal(result, expected)
expected = frame["A"].copy()
result = frame["A"].copy()
result.loc["foo":"bar"] = 0
expected.loc["foo"] = 0
expected.loc["bar"] = 0
tm.assert_series_equal(result, expected)
@pytest.mark.parametrize(
"indexer, exp_idx, exp_values",
[
(
slice("2019-2", None),
DatetimeIndex(["2019-02-01"], dtype="M8[ns]"),
[2, 3],
),
(
slice(None, "2019-2"),
date_range("2019", periods=2, freq="MS"),
[0, 1, 2, 3],
),
],
)
def test_partial_getitem_loc_datetime(self, indexer, exp_idx, exp_values):
# GH: 25165
date_idx = date_range("2019", periods=2, freq="MS")
df = DataFrame(
list(range(4)),
index=MultiIndex.from_product([date_idx, [0, 1]], names=["x", "y"]),
)
expected = DataFrame(
exp_values,
index=MultiIndex.from_product([exp_idx, [0, 1]], names=["x", "y"]),
)
result = df[indexer]
tm.assert_frame_equal(result, expected)
result = df.loc[indexer]
tm.assert_frame_equal(result, expected)
result = df.loc(axis=0)[indexer]
tm.assert_frame_equal(result, expected)
result = df.loc[indexer, :]
tm.assert_frame_equal(result, expected)
df2 = df.swaplevel(0, 1).sort_index()
expected = expected.swaplevel(0, 1).sort_index()
result = df2.loc[:, indexer, :]
tm.assert_frame_equal(result, expected)
def test_loc_getitem_partial_both_axis():
# gh-12660
iterables = [["a", "b"], [2, 1]]
columns = MultiIndex.from_product(iterables, names=["col1", "col2"])
rows = MultiIndex.from_product(iterables, names=["row1", "row2"])
df = DataFrame(
np.random.default_rng(2).standard_normal((4, 4)), index=rows, columns=columns
)
expected = df.iloc[:2, 2:].droplevel("row1").droplevel("col1", axis=1)
result = df.loc["a", "b"]
tm.assert_frame_equal(result, expected)