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Metadata-Version: 2.1
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Name: DataProperty
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Version: 1.1.0
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Summary: Python library for extract property from data.
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Home-page: https://github.com/thombashi/DataProperty
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Author: Tsuyoshi Hombashi
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Author-email: tsuyoshi.hombashi@gmail.com
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Maintainer: Tsuyoshi Hombashi
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Maintainer-email: tsuyoshi.hombashi@gmail.com
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License: MIT License
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Project-URL: Changelog, https://github.com/thombashi/DataProperty/releases
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Project-URL: Source, https://github.com/thombashi/DataProperty
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Project-URL: Tracker, https://github.com/thombashi/DataProperty/issues
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Keywords: data,library,property
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Classifier: Development Status :: 5 - Production/Stable
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Classifier: Intended Audience :: Developers
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Classifier: Intended Audience :: Information Technology
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Classifier: License :: OSI Approved :: MIT License
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Classifier: Operating System :: OS Independent
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.10
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Classifier: Programming Language :: Python :: 3.11
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Classifier: Programming Language :: Python :: 3.12
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Classifier: Programming Language :: Python :: 3.13
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Classifier: Programming Language :: Python :: Implementation :: CPython
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Classifier: Programming Language :: Python :: Implementation :: PyPy
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Classifier: Topic :: Software Development :: Libraries
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Classifier: Topic :: Software Development :: Libraries :: Python Modules
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Classifier: Typing :: Typed
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Requires-Python: >=3.9
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Description-Content-Type: text/x-rst
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License-File: LICENSE
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Requires-Dist: mbstrdecoder<2,>=1.0.0
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Requires-Dist: typepy[datetime]<2,>=1.3.2
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Provides-Extra: logging
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Requires-Dist: loguru<1,>=0.4.1; extra == "logging"
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Provides-Extra: test
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Requires-Dist: pytest>=6.0.1; extra == "test"
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Requires-Dist: pytest-md-report>=0.6.2; extra == "test"
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Requires-Dist: tcolorpy>=0.1.2; extra == "test"
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.. contents:: **DataProperty**
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:backlinks: top
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:local:
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Summary
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=======
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A Python library for extract property from data.
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.. image:: https://badge.fury.io/py/DataProperty.svg
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:target: https://badge.fury.io/py/DataProperty
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:alt: PyPI package version
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.. image:: https://anaconda.org/conda-forge/DataProperty/badges/version.svg
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:target: https://anaconda.org/conda-forge/DataProperty
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:alt: conda-forge package version
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.. image:: https://img.shields.io/pypi/pyversions/DataProperty.svg
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:target: https://pypi.org/project/DataProperty
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:alt: Supported Python versions
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.. image:: https://img.shields.io/pypi/implementation/DataProperty.svg
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:target: https://pypi.org/project/DataProperty
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:alt: Supported Python implementations
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.. image:: https://github.com/thombashi/DataProperty/actions/workflows/ci.yml/badge.svg
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:target: https://github.com/thombashi/DataProperty/actions/workflows/ci.yml
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:alt: CI status of Linux/macOS/Windows
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.. image:: https://coveralls.io/repos/github/thombashi/DataProperty/badge.svg?branch=master
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:target: https://coveralls.io/github/thombashi/DataProperty?branch=master
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:alt: Test coverage
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.. image:: https://github.com/thombashi/DataProperty/actions/workflows/github-code-scanning/codeql/badge.svg
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:target: https://github.com/thombashi/DataProperty/actions/workflows/github-code-scanning/codeql
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:alt: CodeQL
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Installation
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============
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Installation: pip
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------------------------------
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::
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pip install DataProperty
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Installation: conda
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------------------------------
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::
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conda install -c conda-forge dataproperty
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Installation: apt
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------------------------------
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::
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sudo add-apt-repository ppa:thombashi/ppa
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sudo apt update
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sudo apt install python3-dataproperty
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Usage
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=====
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Extract property of data
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------------------------
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e.g. Extract a ``float`` value property
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code:: python
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>>> from dataproperty import DataProperty
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>>> DataProperty(-1.1)
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data=-1.1, type=REAL_NUMBER, align=right, ascii_width=4, int_digits=1, decimal_places=1, extra_len=1
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e.g. Extract a ``int`` value property
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code:: python
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>>> from dataproperty import DataProperty
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>>> DataProperty(123456789)
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data=123456789, type=INTEGER, align=right, ascii_width=9, int_digits=9, decimal_places=0, extra_len=0
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e.g. Extract a ``str`` (ascii) value property
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code:: python
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>>> from dataproperty import DataProperty
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>>> DataProperty("sample string")
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data=sample string, type=STRING, align=left, length=13, ascii_width=13, extra_len=0
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e.g. Extract a ``str`` (multi-byte) value property
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code:: python
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>>> from dataproperty import DataProperty
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>>> str(DataProperty("吾輩は猫である"))
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data=吾輩は猫である, type=STRING, align=left, length=7, ascii_width=14, extra_len=0
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e.g. Extract a time (``datetime``) value property
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code:: python
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>>> import datetime
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>>> from dataproperty import DataProperty
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>>> DataProperty(datetime.datetime(2017, 1, 1, 0, 0, 0))
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data=2017-01-01 00:00:00, type=DATETIME, align=left, ascii_width=19, extra_len=0
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e.g. Extract a ``bool`` value property
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code:: python
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>>> from dataproperty import DataProperty
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>>> DataProperty(True)
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data=True, type=BOOL, align=left, ascii_width=4, extra_len=0
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Extract data property for each element from a matrix
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----------------------------------------------------
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``DataPropertyExtractor.to_dp_matrix`` method returns a matrix of ``DataProperty`` instances from a data matrix.
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An example data set and the result are as follows:
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:Sample Code:
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.. code:: python
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import datetime
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from dataproperty import DataPropertyExtractor
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dp_extractor = DataPropertyExtractor()
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dt = datetime.datetime(2017, 1, 1, 0, 0, 0)
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inf = float("inf")
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nan = float("nan")
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dp_matrix = dp_extractor.to_dp_matrix([
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[1, 1.1, "aa", 1, 1, True, inf, nan, dt],
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[2, 2.2, "bbb", 2.2, 2.2, False, "inf", "nan", dt],
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[3, 3.33, "cccc", -3, "ccc", "true", inf, "NAN", "2017-01-01T01:23:45+0900"],
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])
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for row, dp_list in enumerate(dp_matrix):
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for col, dp in enumerate(dp_list):
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print("row={:d}, col={:d}, {}".format(row, col, str(dp)))
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:Output:
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::
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row=0, col=0, data=1, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
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row=0, col=1, data=1.1, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
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row=0, col=2, data=aa, type=STRING, align=left, ascii_width=2, length=2, extra_len=0
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row=0, col=3, data=1, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
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row=0, col=4, data=1, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
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row=0, col=5, data=True, type=BOOL, align=left, ascii_width=4, extra_len=0
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row=0, col=6, data=Infinity, type=INFINITY, align=left, ascii_width=8, extra_len=0
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row=0, col=7, data=NaN, type=NAN, align=left, ascii_width=3, extra_len=0
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row=0, col=8, data=2017-01-01 00:00:00, type=DATETIME, align=left, ascii_width=19, extra_len=0
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row=1, col=0, data=2, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
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row=1, col=1, data=2.2, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
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row=1, col=2, data=bbb, type=STRING, align=left, ascii_width=3, length=3, extra_len=0
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row=1, col=3, data=2.2, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
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row=1, col=4, data=2.2, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
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row=1, col=5, data=False, type=BOOL, align=left, ascii_width=5, extra_len=0
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row=1, col=6, data=Infinity, type=INFINITY, align=left, ascii_width=8, extra_len=0
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row=1, col=7, data=NaN, type=NAN, align=left, ascii_width=3, extra_len=0
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row=1, col=8, data=2017-01-01 00:00:00, type=DATETIME, align=left, ascii_width=19, extra_len=0
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row=2, col=0, data=3, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
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row=2, col=1, data=3.33, type=REAL_NUMBER, align=right, ascii_width=4, int_digits=1, decimal_places=2, extra_len=0
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row=2, col=2, data=cccc, type=STRING, align=left, ascii_width=4, length=4, extra_len=0
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row=2, col=3, data=-3, type=INTEGER, align=right, ascii_width=2, int_digits=1, decimal_places=0, extra_len=1
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row=2, col=4, data=ccc, type=STRING, align=left, ascii_width=3, length=3, extra_len=0
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row=2, col=5, data=True, type=BOOL, align=left, ascii_width=4, extra_len=0
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row=2, col=6, data=Infinity, type=INFINITY, align=left, ascii_width=8, extra_len=0
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row=2, col=7, data=NaN, type=NAN, align=left, ascii_width=3, extra_len=0
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row=2, col=8, data=2017-01-01T01:23:45+0900, type=STRING, align=left, ascii_width=24, length=24, extra_len=0
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Full example source code can be found at *examples/py/to_dp_matrix.py*
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Extract properties for each column from a matrix
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------------------------------------------------------
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``DataPropertyExtractor.to_column_dp_list`` method returns a list of ``DataProperty`` instances from a data matrix. The list represents the properties for each column.
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An example data set and the result are as follows:
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Example data set and result are as follows:
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:Sample Code:
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.. code:: python
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import datetime
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from dataproperty import DataPropertyExtractor
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dp_extractor = DataPropertyExtractor()
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dt = datetime.datetime(2017, 1, 1, 0, 0, 0)
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inf = float("inf")
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nan = float("nan")
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data_matrix = [
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[1, 1.1, "aa", 1, 1, True, inf, nan, dt],
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[2, 2.2, "bbb", 2.2, 2.2, False, "inf", "nan", dt],
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[3, 3.33, "cccc", -3, "ccc", "true", inf, "NAN", "2017-01-01T01:23:45+0900"],
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]
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dp_extractor.headers = ["int", "float", "str", "num", "mix", "bool", "inf", "nan", "time"]
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col_dp_list = dp_extractor.to_column_dp_list(dp_extractor.to_dp_matrix(dp_matrix))
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for col_idx, col_dp in enumerate(col_dp_list):
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print(str(col_dp))
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:Output:
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::
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column=0, type=INTEGER, align=right, ascii_width=3, bit_len=2, int_digits=1, decimal_places=0
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column=1, type=REAL_NUMBER, align=right, ascii_width=5, int_digits=1, decimal_places=(min=1, max=2)
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column=2, type=STRING, align=left, ascii_width=4
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column=3, type=REAL_NUMBER, align=right, ascii_width=4, int_digits=1, decimal_places=(min=0, max=1), extra_len=(min=0, max=1)
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column=4, type=STRING, align=left, ascii_width=3, int_digits=1, decimal_places=(min=0, max=1)
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column=5, type=BOOL, align=left, ascii_width=5
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column=6, type=INFINITY, align=left, ascii_width=8
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column=7, type=NAN, align=left, ascii_width=3
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column=8, type=STRING, align=left, ascii_width=24
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Full example source code can be found at *examples/py/to_column_dp_list.py*
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Dependencies
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============
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- Python 3.9+
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- `Python package dependencies (automatically installed) <https://github.com/thombashi/DataProperty/network/dependencies>`__
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Optional dependencies
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---------------------
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- `loguru <https://github.com/Delgan/loguru>`__
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- Used for logging if the package installed
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