def computational_form(data):
"""
Input Series of numbers, Series, or DataFrames repackaged
for calculation.
Parameters
----------
data : pandas.Series
Series of numbers, Series, DataFrames
Returns
-------
pandas.Series, DataFrame, or Panel
repacked data, aligned by indices, ready for calculation
"""
if isinstance(data.iloc[0], DataFrame):
dslice = Panel.from_dict(
dict([(i, data.iloc[i]) for i in xrange(len(data))]))
elif isinstance(data.iloc[0], Series):
dslice = DataFrame(data.tolist())
dslice.index = data.index
else:
dslice = data
return dslice
def computational_form(data):
"""
Input Series of numbers, Series, or DataFrames repackaged
for calculation.
Parameters
----------
data : pandas.Series
Series of numbers, Series, DataFrames
Returns
-------
pandas.Series, DataFrame, or Panel
repacked data, aligned by indices, ready for calculation
"""
if isinstance(data.iloc[0], DataFrame):
dslice = Panel.from_dict(dict([(i,data.iloc[i])
for i in xrange(len(data))]))
elif isinstance(data.iloc[0], Series):
dslice = DataFrame(data.tolist())
dslice.index = data.index
else:
dslice = data
return dslice
def computational_form(data):
"""
Repackages numbers, Series, or DataFrames
Regardless of input format, mathematical operations may be performed on the output via the same pandas mechanisms.
This method may be particularly useful in analysis methods that aim to be instrument independent. pysat.Instrument objects can package data in a variety of ways within a DataFrame, depending upon the scientific data source. Thus, a variety of data types will be encountered by instrument independent methods and computational_form method may reduce the effort required to support more generalized processing.
Parameters
----------
data : pandas.Series
Series of numbers, Series, DataFrames
Returns
-------
pandas.Series, DataFrame, or Panel
repacked data, aligned by indices, ready for calculation
"""
from pysat import DataFrame, Series, datetime, Panel
if isinstance(data.iloc[0], DataFrame):
dslice = Panel.from_dict(
dict([(i, data.iloc[i]) for i in xrange(len(data))]))
elif isinstance(data.iloc[0], Series):
dslice = DataFrame(data.tolist())
dslice.index = data.index
else:
dslice = data
return dslice
def computational_form(data):
"""
Repackages numbers, Series, or DataFrames
.. deprecated:: 2.2.0
`computational_form` will be removed in pysat 3.0.0, it will
be added to pysatSeasons
Regardless of input format, mathematical operations may be performed on the
output via the same pandas mechanisms.
This method may be particularly useful in analysis methods that aim to be
instrument independent. pysat.Instrument objects can package data in a
variety of ways within a DataFrame, depending upon the scientific data
source. Thus, a variety of data types will be encountered by instrument
independent methods and computational_form method may reduce the effort
required to support more generalized processing.
Parameters
----------
data : pandas.Series
Series of numbers, Series, DataFrames
Returns
-------
pandas.Series, DataFrame, or Panel
repacked data, aligned by indices, ready for calculation
"""
from pysat import DataFrame, Series, Panel
import warnings
warnings.warn(' '.join([
"This function is deprecated here and will be",
"removed in pysat 3.0.0. Please use", "pysatSeasons instead:"
"https://github.com/pysat/pysatSeasons"
]),
DeprecationWarning,
stacklevel=2)
if isinstance(data.iloc[0], DataFrame):
dslice = Panel.from_dict(
dict([(i, data.iloc[i]) for i in range(len(data))]))
elif isinstance(data.iloc[0], Series):
dslice = DataFrame(data.tolist())
dslice.index = data.index
else:
dslice = data
return dslice
