GitHub - thombashi/DataProperty at 074c51483405431e34cd86c06c7404396d204c4b

DataProperty

Summary

A Python library for extract property from data.

Installation

Installation: pip

pip install DataProperty

Installation: conda

conda install -c conda-forge dataproperty

Installation: apt

sudo add-apt-repository ppa:thombashi/ppa
sudo apt update
sudo apt install python3-dataproperty

Usage

Extract property of data

e.g. Extract a `float` value property

>>> from dataproperty import DataProperty
>>> DataProperty(-1.1)
data=-1.1, type=REAL_NUMBER, align=right, ascii_width=4, int_digits=1, decimal_places=1, extra_len=1

e.g. Extract a `int` value property

>>> from dataproperty import DataProperty
>>> DataProperty(123456789)
data=123456789, type=INTEGER, align=right, ascii_width=9, int_digits=9, decimal_places=0, extra_len=0

e.g. Extract a `str` (ascii) value property

>>> from dataproperty import DataProperty
>>> DataProperty("sample string")
data=sample string, type=STRING, align=left, length=13, ascii_width=13, extra_len=0

e.g. Extract a `str` (multi-byte) value property

>>> from dataproperty import DataProperty
>>> str(DataProperty("吾輩は猫である"))
data=吾輩は猫である, type=STRING, align=left, length=7, ascii_width=14, extra_len=0

e.g. Extract a time (`datetime`) value property

>>> import datetime
>>> from dataproperty import DataProperty
>>> DataProperty(datetime.datetime(2017, 1, 1, 0, 0, 0))
data=2017-01-01 00:00:00, type=DATETIME, align=left, ascii_width=19, extra_len=0

e.g. Extract a `bool` value property

>>> from dataproperty import DataProperty
>>> DataProperty(True)
data=True, type=BOOL, align=left, ascii_width=4, extra_len=0

Extract data property for each element from a matrix

DataPropertyExtractor.to_dp_matrix method returns a matrix of DataProperty instances from a data matrix. An example data set and the result are as follows:

Sample Code:

import datetime
from dataproperty import DataPropertyExtractor

dp_extractor = DataPropertyExtractor()
dt = datetime.datetime(2017, 1, 1, 0, 0, 0)
inf = float("inf")
nan = float("nan")

dp_matrix = dp_extractor.to_dp_matrix([
    [1, 1.1, "aa", 1, 1, True, inf, nan, dt],
    [2, 2.2, "bbb", 2.2, 2.2, False, "inf", "nan", dt],
    [3, 3.33, "cccc", -3, "ccc", "true", inf, "NAN", "2017-01-01T01:23:45 0900"],
])

for row, dp_list in enumerate(dp_matrix):
    for col, dp in enumerate(dp_list):
        print("row={:d}, col={:d}, {}".format(row, col, str(dp)))

Output:

row=0, col=0, data=1, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
row=0, col=1, data=1.1, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
row=0, col=2, data=aa, type=STRING, align=left, ascii_width=2, length=2, extra_len=0
row=0, col=3, data=1, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
row=0, col=4, data=1, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
row=0, col=5, data=True, type=BOOL, align=left, ascii_width=4, extra_len=0
row=0, col=6, data=Infinity, type=INFINITY, align=left, ascii_width=8, extra_len=0
row=0, col=7, data=NaN, type=NAN, align=left, ascii_width=3, extra_len=0
row=0, col=8, data=2017-01-01 00:00:00, type=DATETIME, align=left, ascii_width=19, extra_len=0
row=1, col=0, data=2, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
row=1, col=1, data=2.2, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
row=1, col=2, data=bbb, type=STRING, align=left, ascii_width=3, length=3, extra_len=0
row=1, col=3, data=2.2, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
row=1, col=4, data=2.2, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
row=1, col=5, data=False, type=BOOL, align=left, ascii_width=5, extra_len=0
row=1, col=6, data=Infinity, type=INFINITY, align=left, ascii_width=8, extra_len=0
row=1, col=7, data=NaN, type=NAN, align=left, ascii_width=3, extra_len=0
row=1, col=8, data=2017-01-01 00:00:00, type=DATETIME, align=left, ascii_width=19, extra_len=0
row=2, col=0, data=3, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
row=2, col=1, data=3.33, type=REAL_NUMBER, align=right, ascii_width=4, int_digits=1, decimal_places=2, extra_len=0
row=2, col=2, data=cccc, type=STRING, align=left, ascii_width=4, length=4, extra_len=0
row=2, col=3, data=-3, type=INTEGER, align=right, ascii_width=2, int_digits=1, decimal_places=0, extra_len=1
row=2, col=4, data=ccc, type=STRING, align=left, ascii_width=3, length=3, extra_len=0
row=2, col=5, data=True, type=BOOL, align=left, ascii_width=4, extra_len=0
row=2, col=6, data=Infinity, type=INFINITY, align=left, ascii_width=8, extra_len=0
row=2, col=7, data=NaN, type=NAN, align=left, ascii_width=3, extra_len=0
row=2, col=8, data=2017-01-01T01:23:45 0900, type=STRING, align=left, ascii_width=24, length=24, extra_len=0

Full example source code can be found at examples/py/to_dp_matrix.py

Extract properties for each column from a matrix

DataPropertyExtractor.to_column_dp_list method returns a list of DataProperty instances from a data matrix. The list represents the properties for each column. An example data set and the result are as follows:

Example data set and result are as follows:

Sample Code:

import datetime
from dataproperty import DataPropertyExtractor

dp_extractor = DataPropertyExtractor()
dt = datetime.datetime(2017, 1, 1, 0, 0, 0)
inf = float("inf")
nan = float("nan")

data_matrix = [
    [1, 1.1,  "aa",   1,   1,     True,   inf,   nan,   dt],
    [2, 2.2,  "bbb",  2.2, 2.2,   False,  "inf", "nan", dt],
    [3, 3.33, "cccc", -3,  "ccc", "true", inf,   "NAN", "2017-01-01T01:23:45 0900"],
]

dp_extractor.headers = ["int", "float", "str", "num", "mix", "bool", "inf", "nan", "time"]
col_dp_list = dp_extractor.to_column_dp_list(dp_extractor.to_dp_matrix(dp_matrix))

for col_idx, col_dp in enumerate(col_dp_list):
    print(str(col_dp))

Output:

column=0, type=INTEGER, align=right, ascii_width=3, bit_len=2, int_digits=1, decimal_places=0
column=1, type=REAL_NUMBER, align=right, ascii_width=5, int_digits=1, decimal_places=(min=1, max=2)
column=2, type=STRING, align=left, ascii_width=4
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)
column=4, type=STRING, align=left, ascii_width=3, int_digits=1, decimal_places=(min=0, max=1)
column=5, type=BOOL, align=left, ascii_width=5
column=6, type=INFINITY, align=left, ascii_width=8
column=7, type=NAN, align=left, ascii_width=3
column=8, type=STRING, align=left, ascii_width=24

Full example source code can be found at examples/py/to_column_dp_list.py

Dependencies

Python 3.7
Python package dependencies (automatically installed)

Optional dependencies

loguru
- Used for logging if the package installed

Name		Name	Last commit message	Last commit date
Latest commit History 1,418 Commits
.github/workflows		.github/workflows
dataproperty		dataproperty
examples		examples
misc		misc
requirements		requirements
test		test
.gitignore		.gitignore
LICENSE		LICENSE
MANIFEST.in		MANIFEST.in
Makefile		Makefile
README.rst		README.rst
pylama.ini		pylama.ini
pyproject.toml		pyproject.toml
setup.py		setup.py
tox.ini		tox.ini

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Summary

Installation

Installation: pip

Installation: conda

Installation: apt

Usage

Extract property of data

e.g. Extract a `float` value property

e.g. Extract a `int` value property

e.g. Extract a `str` (ascii) value property

e.g. Extract a `str` (multi-byte) value property

e.g. Extract a time (`datetime`) value property

e.g. Extract a `bool` value property

Extract data property for each element from a matrix

Extract properties for each column from a matrix

Dependencies

Optional dependencies

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