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Upgrade to release 1.1.4: - Fixed regression in read_csv() raising a ValueError when names was of type dict_keys - Fixed regression in read_csv() with more than 1M rows and specifying a index_col argument - Fixed regression where attempting to mutate a DateOffset object would no longer raise an AttributeError - Fixed regression where DataFrame.agg() would fail with TypeError when passed positional arguments to be passed on to the aggregation function - Fixed regression in RollingGroupby with sort=False not being respected - Fixed regression in Series.astype() converting None to "nan" when casting to string - Fixed regression in Series.rank() method failing for read-only data - Fixed regression in RollingGroupby causing a segmentation fault with Index of dtype object - Fixed regression in DataFrame.resample(...).apply(...)() raised AttributeError when input was a DataFrame and only a Series was evaluated - Fixed regression in DataFrame.groupby(..).std() with nullable integer dtype - Fixed regression in PeriodDtype comparing both equal and unequal to its string representation - Fixed regression where slicing DatetimeIndex raised AssertionError on irregular time series with pd.NaT or on unsorted indices - Fixed regression in certain offsets (pd.offsets.Day() and below) no longer being hashable - Fixed regression in StataReader which required chunksize to be manually set when using an iterator to read a dataset - Fixed regression in setitem with DataFrame.iloc() which raised error when trying to set a value while filtering with a boolean list - Fixed regression in setitem with a Series getting aligned before setting the values - Fixed regression in MultiIndex.is_monotonic_increasing returning wrong results with NaN in at least one of the levels - Fixed regression in inplace arithmetic operation on a Series not updating the parent DataFrame - Fixed bug causing groupby(...).sum() and similar to not preserve metadata - Fixed bug in Series.isin() and DataFrame.isin() raising a ValueError when the target was read-only - Fixed bug in GroupBy.fillna() that introduced a performance regression after 1.0.5 - Fixed bug in DataFrame.info() was raising a KeyError when the DataFrame has integer column names - Fixed bug in DataFrameGroupby.apply() would drop a CategoricalIndex when grouped on Signed-off-by: Leon Anavi <leon.anavi@konsulko.com> Acked-by: Trevor Gamblin <trevor.gamblin@windriver.com> Signed-off-by: Khem Raj <raj.khem@gmail.com>
26 lines
832 B
BlitzBasic
26 lines
832 B
BlitzBasic
SUMMARY = "pandas library for high-performance data analysis tools"
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DESCRIPTION = "pandas is an open source, BSD-licensed library providing \
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high-performance, easy-to-use data structures and data analysis tools for \
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the Python programming language."
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HOMEPAGE = "http://pandas.pydata.org/"
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LICENSE = "BSD-3-Clause"
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LIC_FILES_CHKSUM = "file://LICENSE;md5=c2a8f987b2ce77c368c6b3e1b5b10774"
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SRC_URI[md5sum] = "594e6a429f297c77470e37d3510cccbb"
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SRC_URI[sha256sum] = "a979d0404b135c63954dea79e6246c45dd45371a88631cdbb4877d844e6de3b6"
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inherit pypi setuptools3
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DEPENDS += " \
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${PYTHON_PN}-numpy-native ${PYTHON_PN}-cython-native \
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"
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CFLAGS_append_toolchain-clang = " -Wno-error=deprecated-declarations"
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RDEPENDS_${PN} += " \
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${PYTHON_PN}-json \
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${PYTHON_PN}-numpy \
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${PYTHON_PN}-dateutil \
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${PYTHON_PN}-pytz \
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"
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