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test_filter.py
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test_filter.py
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import numpy as np
import pytest
import pandas as pd
from pandas import DataFrame
import pandas._testing as tm
class TestDataFrameFilter:
def test_filter(self, float_frame, float_string_frame):
# Items
filtered = float_frame.filter(["A", "B", "E"])
assert len(filtered.columns) == 2
assert "E" not in filtered
filtered = float_frame.filter(["A", "B", "E"], axis="columns")
assert len(filtered.columns) == 2
assert "E" not in filtered
# Other axis
idx = float_frame.index[0:4]
filtered = float_frame.filter(idx, axis="index")
expected = float_frame.reindex(index=idx)
tm.assert_frame_equal(filtered, expected)
# like
fcopy = float_frame.copy()
fcopy["AA"] = 1
filtered = fcopy.filter(like="A")
assert len(filtered.columns) == 2
assert "AA" in filtered
# like with ints in column names
df = DataFrame(0.0, index=[0, 1, 2], columns=[0, 1, "_A", "_B"])
filtered = df.filter(like="_")
assert len(filtered.columns) == 2
# regex with ints in column names
# from PR #10384
df = DataFrame(0.0, index=[0, 1, 2], columns=["A1", 1, "B", 2, "C"])
expected = DataFrame(
0.0, index=[0, 1, 2], columns=pd.Index([1, 2], dtype=object)
)
filtered = df.filter(regex="^[0-9]+$")
tm.assert_frame_equal(filtered, expected)
expected = DataFrame(0.0, index=[0, 1, 2], columns=[0, "0", 1, "1"])
# shouldn't remove anything
filtered = expected.filter(regex="^[0-9]+$")
tm.assert_frame_equal(filtered, expected)
# pass in None
with pytest.raises(TypeError, match="Must pass"):
float_frame.filter()
with pytest.raises(TypeError, match="Must pass"):
float_frame.filter(items=None)
with pytest.raises(TypeError, match="Must pass"):
float_frame.filter(axis=1)
# test mutually exclusive arguments
with pytest.raises(TypeError, match="mutually exclusive"):
float_frame.filter(items=["one", "three"], regex="e$", like="bbi")
with pytest.raises(TypeError, match="mutually exclusive"):
float_frame.filter(items=["one", "three"], regex="e$", axis=1)
with pytest.raises(TypeError, match="mutually exclusive"):
float_frame.filter(items=["one", "three"], regex="e$")
with pytest.raises(TypeError, match="mutually exclusive"):
float_frame.filter(items=["one", "three"], like="bbi", axis=0)
with pytest.raises(TypeError, match="mutually exclusive"):
float_frame.filter(items=["one", "three"], like="bbi")
# objects
filtered = float_string_frame.filter(like="foo")
assert "foo" in filtered
# unicode columns, won't ascii-encode
df = float_frame.rename(columns={"B": "\u2202"})
filtered = df.filter(like="C")
assert "C" in filtered
def test_filter_regex_search(self, float_frame):
fcopy = float_frame.copy()
fcopy["AA"] = 1
# regex
filtered = fcopy.filter(regex="[A]+")
assert len(filtered.columns) == 2
assert "AA" in filtered
# doesn't have to be at beginning
df = DataFrame(
{"aBBa": [1, 2], "BBaBB": [1, 2], "aCCa": [1, 2], "aCCaBB": [1, 2]}
)
result = df.filter(regex="BB")
exp = df[[x for x in df.columns if "BB" in x]]
tm.assert_frame_equal(result, exp)
@pytest.mark.parametrize(
"name,expected_data",
[
("a", {"a": [1, 2]}),
("あ", {"あ": [3, 4]}),
],
)
def test_filter_unicode(self, name, expected_data):
# GH13101
df = DataFrame({"a": [1, 2], "あ": [3, 4]})
expected = DataFrame(expected_data)
tm.assert_frame_equal(df.filter(like=name), expected)
tm.assert_frame_equal(df.filter(regex=name), expected)
def test_filter_bytestring(self):
# GH13101
name = "a"
df = DataFrame({b"a": [1, 2], b"b": [3, 4]})
expected = DataFrame({b"a": [1, 2]})
tm.assert_frame_equal(df.filter(like=name), expected)
tm.assert_frame_equal(df.filter(regex=name), expected)
def test_filter_corner(self):
empty = DataFrame()
result = empty.filter([])
tm.assert_frame_equal(result, empty)
result = empty.filter(like="foo")
tm.assert_frame_equal(result, empty)
def test_filter_regex_non_string(self):
# GH#5798 trying to filter on non-string columns should drop,
# not raise
df = DataFrame(np.random.default_rng(2).random((3, 2)), columns=["STRING", 123])
result = df.filter(regex="STRING")
expected = df[["STRING"]]
tm.assert_frame_equal(result, expected)
def test_filter_keep_order(self):
# GH#54980
df = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
result = df.filter(items=["B", "A"])
expected = df[["B", "A"]]
tm.assert_frame_equal(result, expected)
def test_filter_different_dtype(self):
# GH#54980
df = DataFrame({1: [1, 2, 3], 2: [4, 5, 6]})
result = df.filter(items=["B", "A"])
expected = df[[]]
tm.assert_frame_equal(result, expected)