craftbeerpi4-pione/venv3/lib/python3.7/site-packages/pandas/tests/indexing/test_scalar.py
2021-03-03 23:49:41 +01:00

415 lines
13 KiB
Python

""" test scalar indexing, including at and iat """
from datetime import datetime, timedelta
import numpy as np
import pytest
from pandas import DataFrame, Series, Timedelta, Timestamp, date_range, period_range
import pandas._testing as tm
from pandas.tests.indexing.common import Base
class TestScalar(Base):
@pytest.mark.parametrize("kind", ["series", "frame"])
def test_at_and_iat_get(self, kind):
def _check(f, func, values=False):
if f is not None:
indices = self.generate_indices(f, values)
for i in indices:
result = getattr(f, func)[i]
expected = self.get_value(func, f, i, values)
tm.assert_almost_equal(result, expected)
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")
@pytest.mark.parametrize("kind", ["series", "frame"])
def test_at_and_iat_set(self, kind):
def _check(f, func, values=False):
if f is not None:
indices = self.generate_indices(f, values)
for i in indices:
getattr(f, func)[i] = 1
expected = self.get_value(func, f, i, values)
tm.assert_almost_equal(expected, 1)
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")
class TestScalar2:
# TODO: Better name, just separating things that dont need Base class
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_frame_at_with_duplicate_axes(self):
# GH#33041
arr = np.random.randn(6).reshape(3, 2)
df = DataFrame(arr, columns=["A", "A"])
result = df.at[0, "A"]
expected = df.iloc[0]
tm.assert_series_equal(result, expected)
result = df.T.at["A", 0]
tm.assert_series_equal(result, expected)
# setter
df.at[1, "A"] = 2
expected = Series([2.0, 2.0], index=["A", "A"], name=1)
tm.assert_series_equal(df.iloc[1], expected)
def test_frame_at_with_duplicate_axes_requires_scalar_lookup(self):
# GH#33041 check that falling back to loc doesn't allow non-scalar
# args to slip in
arr = np.random.randn(6).reshape(3, 2)
df = DataFrame(arr, columns=["A", "A"])
msg = "Invalid call for scalar access"
with pytest.raises(ValueError, match=msg):
df.at[[1, 2]]
with pytest.raises(ValueError, match=msg):
df.at[1, ["A"]]
with pytest.raises(ValueError, match=msg):
df.at[:, "A"]
with pytest.raises(ValueError, match=msg):
df.at[[1, 2]] = 1
with pytest.raises(ValueError, match=msg):
df.at[1, ["A"]] = 1
with pytest.raises(ValueError, match=msg):
df.at[:, "A"] = 1
def test_series_at_raises_type_error(self):
# at should not fallback
# GH 7814
# GH#31724 .at should match .loc
ser = Series([1, 2, 3], index=list("abc"))
result = ser.at["a"]
assert result == 1
result = ser.loc["a"]
assert result == 1
with pytest.raises(KeyError, match="^0$"):
ser.at[0]
with pytest.raises(KeyError, match="^0$"):
ser.loc[0]
def test_frame_raises_key_error(self):
# GH#31724 .at should match .loc
df = DataFrame({"A": [1, 2, 3]}, index=list("abc"))
result = df.at["a", "A"]
assert result == 1
result = df.loc["a", "A"]
assert result == 1
with pytest.raises(KeyError, match="^0$"):
df.at["a", 0]
with pytest.raises(KeyError, match="^0$"):
df.loc["a", 0]
def test_series_at_raises_key_error(self):
# GH#31724 .at should match .loc
ser = Series([1, 2, 3], index=[3, 2, 1])
result = ser.at[1]
assert result == 3
result = ser.loc[1]
assert result == 3
with pytest.raises(KeyError, match="a"):
ser.at["a"]
with pytest.raises(KeyError, match="a"):
# .at should match .loc
ser.loc["a"]
def test_frame_at_raises_key_error(self):
# GH#31724 .at should match .loc
df = DataFrame({0: [1, 2, 3]}, index=[3, 2, 1])
result = df.at[1, 0]
assert result == 3
result = df.loc[1, 0]
assert result == 3
with pytest.raises(KeyError, match="a"):
df.at["a", 0]
with pytest.raises(KeyError, match="a"):
df.loc["a", 0]
with pytest.raises(KeyError, match="a"):
df.at[1, "a"]
with pytest.raises(KeyError, match="a"):
df.loc[1, "a"]
# TODO: belongs somewhere else?
def test_getitem_list_missing_key(self):
# 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
def test_iat_dont_wrap_object_datetimelike():
# GH#32809 .iat calls go through DataFrame._get_value, should not
# call maybe_box_datetimelike
dti = date_range("2016-01-01", periods=3)
tdi = dti - dti
ser = Series(dti.to_pydatetime(), dtype=object)
ser2 = Series(tdi.to_pytimedelta(), dtype=object)
df = DataFrame({"A": ser, "B": ser2})
assert (df.dtypes == object).all()
for result in [df.at[0, "A"], df.iat[0, 0], df.loc[0, "A"], df.iloc[0, 0]]:
assert result is ser[0]
assert isinstance(result, datetime)
assert not isinstance(result, Timestamp)
for result in [df.at[1, "B"], df.iat[1, 1], df.loc[1, "B"], df.iloc[1, 1]]:
assert result is ser2[1]
assert isinstance(result, timedelta)
assert not isinstance(result, Timedelta)
def test_iat_series_with_period_index():
# GH 4390, iat incorrectly indexing
index = period_range("1/1/2001", periods=10)
ser = Series(np.random.randn(10), index=index)
expected = ser[index[0]]
result = ser.iat[0]
assert expected == result
def test_at_with_tuple_index_get():
# GH 26989
# DataFrame.at getter works with Index of tuples
df = DataFrame({"a": [1, 2]}, index=[(1, 2), (3, 4)])
assert df.index.nlevels == 1
assert df.at[(1, 2), "a"] == 1
# Series.at getter works with Index of tuples
series = df["a"]
assert series.index.nlevels == 1
assert series.at[(1, 2)] == 1
def test_at_with_tuple_index_set():
# GH 26989
# DataFrame.at setter works with Index of tuples
df = DataFrame({"a": [1, 2]}, index=[(1, 2), (3, 4)])
assert df.index.nlevels == 1
df.at[(1, 2), "a"] = 2
assert df.at[(1, 2), "a"] == 2
# Series.at setter works with Index of tuples
series = df["a"]
assert series.index.nlevels == 1
series.at[1, 2] = 3
assert series.at[1, 2] == 3
def test_multiindex_at_get():
# GH 26989
# DataFrame.at and DataFrame.loc getter works with MultiIndex
df = DataFrame({"a": [1, 2]}, index=[[1, 2], [3, 4]])
assert df.index.nlevels == 2
assert df.at[(1, 3), "a"] == 1
assert df.loc[(1, 3), "a"] == 1
# Series.at and Series.loc getter works with MultiIndex
series = df["a"]
assert series.index.nlevels == 2
assert series.at[1, 3] == 1
assert series.loc[1, 3] == 1
def test_multiindex_at_set():
# GH 26989
# DataFrame.at and DataFrame.loc setter works with MultiIndex
df = DataFrame({"a": [1, 2]}, index=[[1, 2], [3, 4]])
assert df.index.nlevels == 2
df.at[(1, 3), "a"] = 3
assert df.at[(1, 3), "a"] == 3
df.loc[(1, 3), "a"] = 4
assert df.loc[(1, 3), "a"] == 4
# Series.at and Series.loc setter works with MultiIndex
series = df["a"]
assert series.index.nlevels == 2
series.at[1, 3] = 5
assert series.at[1, 3] == 5
series.loc[1, 3] = 6
assert series.loc[1, 3] == 6