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Python library for extract property from data.

Project description

DataProperty

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Summary

A Python library for extract property from data.

Installation

pip install DataProperty

Usage

Extract property of data

e.g. Extract a float value property

>>> from dataproperty import DataProperty
>>> DataProperty(-1.1)
data=-1.1, typename=REAL_NUMBER, align=right, ascii_char_width=4, integer_digits=1, decimal_places=1, additional_format_len=1

e.g. Extract a int value property

>>> from dataproperty import DataProperty
>>> DataProperty(123456789)
data=123456789, typename=INTEGER, align=right, ascii_char_width=9, integer_digits=9, decimal_places=0, additional_format_len=0

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

>>> from dataproperty import DataProperty
>>> DataProperty("sample string")
data=sample string, typename=STRING, align=left, length=13, ascii_char_width=13, additional_format_len=0

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

>>> import six
>>> from dataproperty import DataProperty
>>> six.text_type(DataProperty("吾輩は猫である"))
data=吾輩は猫である, typename=STRING, align=left, length=7, ascii_char_width=14, additional_format_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, typename=DATETIME, align=left, ascii_char_width=19, additional_format_len=0

e.g. Extract a bool value property

>>> from dataproperty import DataProperty
>>> DataProperty(True)
data=True, typename=BOOL, align=left, ascii_char_width=4, additional_format_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, typename=INTEGER, align=right, ascii_char_width=1, integer_digits=1, decimal_places=0, additional_format_len=0
row=0, col=1, data=1.1, typename=REAL_NUMBER, align=right, ascii_char_width=3, integer_digits=1, decimal_places=1, additional_format_len=0
row=0, col=2, data=aa, typename=STRING, align=left, ascii_char_width=2, length=2, additional_format_len=0
row=0, col=3, data=1, typename=INTEGER, align=right, ascii_char_width=1, integer_digits=1, decimal_places=0, additional_format_len=0
row=0, col=4, data=1, typename=INTEGER, align=right, ascii_char_width=1, integer_digits=1, decimal_places=0, additional_format_len=0
row=0, col=5, data=True, typename=BOOL, align=left, ascii_char_width=4, additional_format_len=0
row=0, col=6, data=Infinity, typename=INFINITY, align=left, ascii_char_width=8, additional_format_len=0
row=0, col=7, data=NaN, typename=NAN, align=left, ascii_char_width=3, additional_format_len=0
row=0, col=8, data=2017-01-01 00:00:00, typename=DATETIME, align=left, ascii_char_width=19, additional_format_len=0
row=1, col=0, data=2, typename=INTEGER, align=right, ascii_char_width=1, integer_digits=1, decimal_places=0, additional_format_len=0
row=1, col=1, data=2.2, typename=REAL_NUMBER, align=right, ascii_char_width=3, integer_digits=1, decimal_places=1, additional_format_len=0
row=1, col=2, data=bbb, typename=STRING, align=left, ascii_char_width=3, length=3, additional_format_len=0
row=1, col=3, data=2.2, typename=REAL_NUMBER, align=right, ascii_char_width=3, integer_digits=1, decimal_places=1, additional_format_len=0
row=1, col=4, data=2.2, typename=REAL_NUMBER, align=right, ascii_char_width=3, integer_digits=1, decimal_places=1, additional_format_len=0
row=1, col=5, data=False, typename=BOOL, align=left, ascii_char_width=5, additional_format_len=0
row=1, col=6, data=Infinity, typename=INFINITY, align=left, ascii_char_width=8, additional_format_len=0
row=1, col=7, data=NaN, typename=NAN, align=left, ascii_char_width=3, additional_format_len=0
row=1, col=8, data=2017-01-01 00:00:00, typename=DATETIME, align=left, ascii_char_width=19, additional_format_len=0
row=2, col=0, data=3, typename=INTEGER, align=right, ascii_char_width=1, integer_digits=1, decimal_places=0, additional_format_len=0
row=2, col=1, data=3.33, typename=REAL_NUMBER, align=right, ascii_char_width=4, integer_digits=1, decimal_places=2, additional_format_len=0
row=2, col=2, data=cccc, typename=STRING, align=left, ascii_char_width=4, length=4, additional_format_len=0
row=2, col=3, data=-3, typename=INTEGER, align=right, ascii_char_width=2, integer_digits=1, decimal_places=0, additional_format_len=1
row=2, col=4, data=ccc, typename=STRING, align=left, ascii_char_width=3, length=3, additional_format_len=0
row=2, col=5, data=True, typename=BOOL, align=left, ascii_char_width=4, additional_format_len=0
row=2, col=6, data=Infinity, typename=INFINITY, align=left, ascii_char_width=8, additional_format_len=0
row=2, col=7, data=NaN, typename=NAN, align=left, ascii_char_width=3, additional_format_len=0
row=2, col=8, data=2017-01-01T01:23:45+0900, typename=STRING, align=left, ascii_char_width=24, length=24, additional_format_len=0

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

Extract property 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.header_list = ["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, typename=INTEGER, align=right, ascii_char_width=3, bit_len=2, integer_digits=1, decimal_places=0
column=1, typename=REAL_NUMBER, align=right, ascii_char_width=5, integer_digits=1, decimal_places=(min=1, max=2)
column=2, typename=STRING, align=left, ascii_char_width=4
column=3, typename=REAL_NUMBER, align=right, ascii_char_width=4, integer_digits=1, decimal_places=(min=0, max=1), additional_format_len=(min=0, max=1)
column=4, typename=STRING, align=left, ascii_char_width=3, integer_digits=1, decimal_places=(min=0, max=1)
column=5, typename=BOOL, align=left, ascii_char_width=5
column=6, typename=INFINITY, align=left, ascii_char_width=8
column=7, typename=NAN, align=left, ascii_char_width=3
column=8, typename=STRING, align=left, ascii_char_width=24

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

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