peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/pandas
/tests
/indexing
/test_iat.py
import numpy as np | |
from pandas import ( | |
DataFrame, | |
Series, | |
period_range, | |
) | |
import pandas._testing as tm | |
def test_iat(float_frame): | |
for i, row in enumerate(float_frame.index): | |
for j, col in enumerate(float_frame.columns): | |
result = float_frame.iat[i, j] | |
expected = float_frame.at[row, col] | |
assert result == expected | |
def test_iat_duplicate_columns(): | |
# https://github.com/pandas-dev/pandas/issues/11754 | |
df = DataFrame([[1, 2]], columns=["x", "x"]) | |
assert df.iat[0, 0] == 1 | |
def test_iat_getitem_series_with_period_index(): | |
# GH#4390, iat incorrectly indexing | |
index = period_range("1/1/2001", periods=10) | |
ser = Series(np.random.default_rng(2).standard_normal(10), index=index) | |
expected = ser[index[0]] | |
result = ser.iat[0] | |
assert expected == result | |
def test_iat_setitem_item_cache_cleared( | |
indexer_ial, using_copy_on_write, warn_copy_on_write | |
): | |
# GH#45684 | |
data = {"x": np.arange(8, dtype=np.int64), "y": np.int64(0)} | |
df = DataFrame(data).copy() | |
ser = df["y"] | |
# previously this iat setting would split the block and fail to clear | |
# the item_cache. | |
with tm.assert_cow_warning(warn_copy_on_write): | |
indexer_ial(df)[7, 0] = 9999 | |
with tm.assert_cow_warning(warn_copy_on_write): | |
indexer_ial(df)[7, 1] = 1234 | |
assert df.iat[7, 1] == 1234 | |
if not using_copy_on_write: | |
assert ser.iloc[-1] == 1234 | |
assert df.iloc[-1, -1] == 1234 | |