153 lines
4.6 KiB
Python
153 lines
4.6 KiB
Python
|
"""
|
||
|
Tests for DataFrame.mask; tests DataFrame.where as a side-effect.
|
||
|
"""
|
||
|
|
||
|
import numpy as np
|
||
|
|
||
|
from pandas import (
|
||
|
NA,
|
||
|
DataFrame,
|
||
|
Float64Dtype,
|
||
|
Series,
|
||
|
StringDtype,
|
||
|
Timedelta,
|
||
|
isna,
|
||
|
)
|
||
|
import pandas._testing as tm
|
||
|
|
||
|
|
||
|
class TestDataFrameMask:
|
||
|
def test_mask(self):
|
||
|
df = DataFrame(np.random.randn(5, 3))
|
||
|
cond = df > 0
|
||
|
|
||
|
rs = df.where(cond, np.nan)
|
||
|
tm.assert_frame_equal(rs, df.mask(df <= 0))
|
||
|
tm.assert_frame_equal(rs, df.mask(~cond))
|
||
|
|
||
|
other = DataFrame(np.random.randn(5, 3))
|
||
|
rs = df.where(cond, other)
|
||
|
tm.assert_frame_equal(rs, df.mask(df <= 0, other))
|
||
|
tm.assert_frame_equal(rs, df.mask(~cond, other))
|
||
|
|
||
|
def test_mask2(self):
|
||
|
# see GH#21891
|
||
|
df = DataFrame([1, 2])
|
||
|
res = df.mask([[True], [False]])
|
||
|
|
||
|
exp = DataFrame([np.nan, 2])
|
||
|
tm.assert_frame_equal(res, exp)
|
||
|
|
||
|
def test_mask_inplace(self):
|
||
|
# GH#8801
|
||
|
df = DataFrame(np.random.randn(5, 3))
|
||
|
cond = df > 0
|
||
|
|
||
|
rdf = df.copy()
|
||
|
|
||
|
return_value = rdf.where(cond, inplace=True)
|
||
|
assert return_value is None
|
||
|
tm.assert_frame_equal(rdf, df.where(cond))
|
||
|
tm.assert_frame_equal(rdf, df.mask(~cond))
|
||
|
|
||
|
rdf = df.copy()
|
||
|
return_value = rdf.where(cond, -df, inplace=True)
|
||
|
assert return_value is None
|
||
|
tm.assert_frame_equal(rdf, df.where(cond, -df))
|
||
|
tm.assert_frame_equal(rdf, df.mask(~cond, -df))
|
||
|
|
||
|
def test_mask_edge_case_1xN_frame(self):
|
||
|
# GH#4071
|
||
|
df = DataFrame([[1, 2]])
|
||
|
res = df.mask(DataFrame([[True, False]]))
|
||
|
expec = DataFrame([[np.nan, 2]])
|
||
|
tm.assert_frame_equal(res, expec)
|
||
|
|
||
|
def test_mask_callable(self):
|
||
|
# GH#12533
|
||
|
df = DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
|
||
|
result = df.mask(lambda x: x > 4, lambda x: x + 1)
|
||
|
exp = DataFrame([[1, 2, 3], [4, 6, 7], [8, 9, 10]])
|
||
|
tm.assert_frame_equal(result, exp)
|
||
|
tm.assert_frame_equal(result, df.mask(df > 4, df + 1))
|
||
|
|
||
|
# return ndarray and scalar
|
||
|
result = df.mask(lambda x: (x % 2 == 0).values, lambda x: 99)
|
||
|
exp = DataFrame([[1, 99, 3], [99, 5, 99], [7, 99, 9]])
|
||
|
tm.assert_frame_equal(result, exp)
|
||
|
tm.assert_frame_equal(result, df.mask(df % 2 == 0, 99))
|
||
|
|
||
|
# chain
|
||
|
result = (df + 2).mask(lambda x: x > 8, lambda x: x + 10)
|
||
|
exp = DataFrame([[3, 4, 5], [6, 7, 8], [19, 20, 21]])
|
||
|
tm.assert_frame_equal(result, exp)
|
||
|
tm.assert_frame_equal(result, (df + 2).mask((df + 2) > 8, (df + 2) + 10))
|
||
|
|
||
|
def test_mask_dtype_bool_conversion(self):
|
||
|
# GH#3733
|
||
|
df = DataFrame(data=np.random.randn(100, 50))
|
||
|
df = df.where(df > 0) # create nans
|
||
|
bools = df > 0
|
||
|
mask = isna(df)
|
||
|
expected = bools.astype(object).mask(mask)
|
||
|
result = bools.mask(mask)
|
||
|
tm.assert_frame_equal(result, expected)
|
||
|
|
||
|
|
||
|
def test_mask_stringdtype(frame_or_series):
|
||
|
# GH 40824
|
||
|
obj = DataFrame(
|
||
|
{"A": ["foo", "bar", "baz", NA]},
|
||
|
index=["id1", "id2", "id3", "id4"],
|
||
|
dtype=StringDtype(),
|
||
|
)
|
||
|
filtered_obj = DataFrame(
|
||
|
{"A": ["this", "that"]}, index=["id2", "id3"], dtype=StringDtype()
|
||
|
)
|
||
|
expected = DataFrame(
|
||
|
{"A": [NA, "this", "that", NA]},
|
||
|
index=["id1", "id2", "id3", "id4"],
|
||
|
dtype=StringDtype(),
|
||
|
)
|
||
|
if frame_or_series is Series:
|
||
|
obj = obj["A"]
|
||
|
filtered_obj = filtered_obj["A"]
|
||
|
expected = expected["A"]
|
||
|
|
||
|
filter_ser = Series([False, True, True, False])
|
||
|
result = obj.mask(filter_ser, filtered_obj)
|
||
|
|
||
|
tm.assert_equal(result, expected)
|
||
|
|
||
|
|
||
|
def test_mask_where_dtype_timedelta():
|
||
|
# https://github.com/pandas-dev/pandas/issues/39548
|
||
|
df = DataFrame([Timedelta(i, unit="d") for i in range(5)])
|
||
|
|
||
|
expected = DataFrame(np.full(5, np.nan, dtype="timedelta64[ns]"))
|
||
|
tm.assert_frame_equal(df.mask(df.notna()), expected)
|
||
|
|
||
|
expected = DataFrame(
|
||
|
[np.nan, np.nan, np.nan, Timedelta("3 day"), Timedelta("4 day")]
|
||
|
)
|
||
|
tm.assert_frame_equal(df.where(df > Timedelta(2, unit="d")), expected)
|
||
|
|
||
|
|
||
|
def test_mask_return_dtype():
|
||
|
# GH#50488
|
||
|
ser = Series([0.0, 1.0, 2.0, 3.0], dtype=Float64Dtype())
|
||
|
cond = ~ser.isna()
|
||
|
other = Series([True, False, True, False])
|
||
|
excepted = Series([1.0, 0.0, 1.0, 0.0], dtype=ser.dtype)
|
||
|
result = ser.mask(cond, other)
|
||
|
tm.assert_series_equal(result, excepted)
|
||
|
|
||
|
|
||
|
def test_mask_inplace_no_other():
|
||
|
# GH#51685
|
||
|
df = DataFrame({"a": [1, 2], "b": ["x", "y"]})
|
||
|
cond = DataFrame({"a": [True, False], "b": [False, True]})
|
||
|
df.mask(cond, inplace=True)
|
||
|
expected = DataFrame({"a": [np.nan, 2], "b": ["x", np.nan]})
|
||
|
tm.assert_frame_equal(df, expected)
|