248 lines
7.8 KiB
Python
248 lines
7.8 KiB
Python
""" test scalar indexing, including at and iat """
|
|
|
|
import numpy as np
|
|
import pytest
|
|
|
|
from pandas import DataFrame, Series, Timedelta, Timestamp, date_range
|
|
import pandas._testing as tm
|
|
from pandas.tests.indexing.common import Base
|
|
|
|
|
|
class TestScalar(Base):
|
|
def test_at_and_iat_get(self):
|
|
def _check(f, func, values=False):
|
|
|
|
if f is not None:
|
|
indicies = self.generate_indices(f, values)
|
|
for i in indicies:
|
|
result = getattr(f, func)[i]
|
|
expected = self.get_value(func, f, i, values)
|
|
tm.assert_almost_equal(result, expected)
|
|
|
|
for kind in self._kinds:
|
|
|
|
d = getattr(self, kind)
|
|
|
|
# iat
|
|
for f in [d["ints"], d["uints"]]:
|
|
_check(f, "iat", values=True)
|
|
|
|
for f in [d["labels"], d["ts"], d["floats"]]:
|
|
if f is not None:
|
|
msg = "iAt based indexing can only have integer indexers"
|
|
with pytest.raises(ValueError, match=msg):
|
|
self.check_values(f, "iat")
|
|
|
|
# at
|
|
for f in [d["ints"], d["uints"], d["labels"], d["ts"], d["floats"]]:
|
|
_check(f, "at")
|
|
|
|
def test_at_and_iat_set(self):
|
|
def _check(f, func, values=False):
|
|
|
|
if f is not None:
|
|
indicies = self.generate_indices(f, values)
|
|
for i in indicies:
|
|
getattr(f, func)[i] = 1
|
|
expected = self.get_value(func, f, i, values)
|
|
tm.assert_almost_equal(expected, 1)
|
|
|
|
for kind in self._kinds:
|
|
|
|
d = getattr(self, kind)
|
|
|
|
# iat
|
|
for f in [d["ints"], d["uints"]]:
|
|
_check(f, "iat", values=True)
|
|
|
|
for f in [d["labels"], d["ts"], d["floats"]]:
|
|
if f is not None:
|
|
msg = "iAt based indexing can only have integer indexers"
|
|
with pytest.raises(ValueError, match=msg):
|
|
_check(f, "iat")
|
|
|
|
# at
|
|
for f in [d["ints"], d["uints"], d["labels"], d["ts"], d["floats"]]:
|
|
_check(f, "at")
|
|
|
|
def test_at_iat_coercion(self):
|
|
|
|
# as timestamp is not a tuple!
|
|
dates = date_range("1/1/2000", periods=8)
|
|
df = DataFrame(np.random.randn(8, 4), index=dates, columns=["A", "B", "C", "D"])
|
|
s = df["A"]
|
|
|
|
result = s.at[dates[5]]
|
|
xp = s.values[5]
|
|
assert result == xp
|
|
|
|
# GH 7729
|
|
# make sure we are boxing the returns
|
|
s = Series(["2014-01-01", "2014-02-02"], dtype="datetime64[ns]")
|
|
expected = Timestamp("2014-02-02")
|
|
|
|
for r in [lambda: s.iat[1], lambda: s.iloc[1]]:
|
|
result = r()
|
|
assert result == expected
|
|
|
|
s = Series(["1 days", "2 days"], dtype="timedelta64[ns]")
|
|
expected = Timedelta("2 days")
|
|
|
|
for r in [lambda: s.iat[1], lambda: s.iloc[1]]:
|
|
result = r()
|
|
assert result == expected
|
|
|
|
def test_iat_invalid_args(self):
|
|
pass
|
|
|
|
def test_imethods_with_dups(self):
|
|
|
|
# GH6493
|
|
# iat/iloc with dups
|
|
|
|
s = Series(range(5), index=[1, 1, 2, 2, 3], dtype="int64")
|
|
result = s.iloc[2]
|
|
assert result == 2
|
|
result = s.iat[2]
|
|
assert result == 2
|
|
|
|
msg = "index 10 is out of bounds for axis 0 with size 5"
|
|
with pytest.raises(IndexError, match=msg):
|
|
s.iat[10]
|
|
msg = "index -10 is out of bounds for axis 0 with size 5"
|
|
with pytest.raises(IndexError, match=msg):
|
|
s.iat[-10]
|
|
|
|
result = s.iloc[[2, 3]]
|
|
expected = Series([2, 3], [2, 2], dtype="int64")
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
df = s.to_frame()
|
|
result = df.iloc[2]
|
|
expected = Series(2, index=[0], name=2)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
result = df.iat[2, 0]
|
|
assert result == 2
|
|
|
|
def test_at_to_fail(self):
|
|
# at should not fallback
|
|
# GH 7814
|
|
s = Series([1, 2, 3], index=list("abc"))
|
|
result = s.at["a"]
|
|
assert result == 1
|
|
msg = (
|
|
"At based indexing on an non-integer index can only have "
|
|
"non-integer indexers"
|
|
)
|
|
with pytest.raises(ValueError, match=msg):
|
|
s.at[0]
|
|
|
|
df = DataFrame({"A": [1, 2, 3]}, index=list("abc"))
|
|
result = df.at["a", "A"]
|
|
assert result == 1
|
|
with pytest.raises(ValueError, match=msg):
|
|
df.at["a", 0]
|
|
|
|
s = Series([1, 2, 3], index=[3, 2, 1])
|
|
result = s.at[1]
|
|
assert result == 3
|
|
msg = "At based indexing on an integer index can only have integer indexers"
|
|
with pytest.raises(ValueError, match=msg):
|
|
s.at["a"]
|
|
|
|
df = DataFrame({0: [1, 2, 3]}, index=[3, 2, 1])
|
|
result = df.at[1, 0]
|
|
assert result == 3
|
|
with pytest.raises(ValueError, match=msg):
|
|
df.at["a", 0]
|
|
|
|
# GH 13822, incorrect error string with non-unique columns when missing
|
|
# column is accessed
|
|
df = DataFrame({"x": [1.0], "y": [2.0], "z": [3.0]})
|
|
df.columns = ["x", "x", "z"]
|
|
|
|
# Check that we get the correct value in the KeyError
|
|
with pytest.raises(KeyError, match=r"\['y'\] not in index"):
|
|
df[["x", "y", "z"]]
|
|
|
|
def test_at_with_tz(self):
|
|
# gh-15822
|
|
df = DataFrame(
|
|
{
|
|
"name": ["John", "Anderson"],
|
|
"date": [
|
|
Timestamp(2017, 3, 13, 13, 32, 56),
|
|
Timestamp(2017, 2, 16, 12, 10, 3),
|
|
],
|
|
}
|
|
)
|
|
df["date"] = df["date"].dt.tz_localize("Asia/Shanghai")
|
|
|
|
expected = Timestamp("2017-03-13 13:32:56+0800", tz="Asia/Shanghai")
|
|
|
|
result = df.loc[0, "date"]
|
|
assert result == expected
|
|
|
|
result = df.at[0, "date"]
|
|
assert result == expected
|
|
|
|
def test_series_set_tz_timestamp(self, tz_naive_fixture):
|
|
# GH 25506
|
|
ts = Timestamp("2017-08-05 00:00:00+0100", tz=tz_naive_fixture)
|
|
result = Series(ts)
|
|
result.at[1] = ts
|
|
expected = Series([ts, ts])
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
def test_mixed_index_at_iat_loc_iloc_series(self):
|
|
# GH 19860
|
|
s = Series([1, 2, 3, 4, 5], index=["a", "b", "c", 1, 2])
|
|
for el, item in s.items():
|
|
assert s.at[el] == s.loc[el] == item
|
|
for i in range(len(s)):
|
|
assert s.iat[i] == s.iloc[i] == i + 1
|
|
|
|
with pytest.raises(KeyError, match="^4$"):
|
|
s.at[4]
|
|
with pytest.raises(KeyError, match="^4$"):
|
|
s.loc[4]
|
|
|
|
def test_mixed_index_at_iat_loc_iloc_dataframe(self):
|
|
# GH 19860
|
|
df = DataFrame(
|
|
[[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]], columns=["a", "b", "c", 1, 2]
|
|
)
|
|
for rowIdx, row in df.iterrows():
|
|
for el, item in row.items():
|
|
assert df.at[rowIdx, el] == df.loc[rowIdx, el] == item
|
|
|
|
for row in range(2):
|
|
for i in range(5):
|
|
assert df.iat[row, i] == df.iloc[row, i] == row * 5 + i
|
|
|
|
with pytest.raises(KeyError, match="^3$"):
|
|
df.at[0, 3]
|
|
with pytest.raises(KeyError, match="^3$"):
|
|
df.loc[0, 3]
|
|
|
|
def test_iat_setter_incompatible_assignment(self):
|
|
# GH 23236
|
|
result = DataFrame({"a": [0, 1], "b": [4, 5]})
|
|
result.iat[0, 0] = None
|
|
expected = DataFrame({"a": [None, 1], "b": [4, 5]})
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_getitem_zerodim_np_array(self):
|
|
# GH24924
|
|
# dataframe __getitem__
|
|
df = DataFrame([[1, 2], [3, 4]])
|
|
result = df[np.array(0)]
|
|
expected = Series([1, 3], name=0)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# series __getitem__
|
|
s = Series([1, 2])
|
|
result = s[np.array(0)]
|
|
assert result == 1
|