ColumnInfo#

class pharmpy.model.ColumnInfo(name, variable_mapping, variable_id=None, drop=False, datatype='float64')[source]#

Bases: Immutable

Information about one data column

Parameters:

name (str) – Column name
variable_mapping (Mapping[int, DataVariable]) – A single DataVariable or a Mapping from identifier column to the DataVariable
variable_id (str) – The DataVariable identifier column
drop (bool) – Should column be dropped (i.e. barred from being used)
datatype (str) – Pandas datatype or special Pharmpy datatype (see the “dtype” attribute)

Attributes Summary

`datatype`	Column datatype
`drop`	Should this column be dropped
`name`	Column name
`symbol`	Symbol having the column name
`type`	The type of the column.
`variable`	If the column represent a single DataVariable return it else raise
`variable_id`	Name of identifier column (e.g. DVID or ADMID).
`variable_mapping`	Mapping from value in identifier column to DataVariable
`variables`	All datavariables defined in this column

Methods Summary

`convert_datatype_to_pd_dtype`(datatype)	Convert Pharmpy datatype to pandas dtype
`convert_pd_dtype_to_datatype`(dtype)	Convert pandas dtype to Pharmpy datatype
`create`(name[, variable_mapping, ...])
`from_dict`(d)
`is_integer`()	Check if the column datatype is integral
`replace`(**kwargs)	Replace properties and create a new ColumnInfo
`to_dict`()

Attributes Documentation

datatype#

Column datatype

datatype	Description	Size	Range	NA allowed?
int8	Signed integer	8 bits	-128 to +127.	No
int16	Signed integer	16 bits	-32,768 to +32,767.	No
int32	Signed integer	32 bits	-2,147,483,648 to +2,147,483,647.	No
int64	Signed integer	64 bits	-9,223,372,036,854,775,808 to 9,223,372,036,854,775,807.	No
uint8	Unsigned integer	8 bits	0 to 256.	No
uint16	Unsigned integer	16 bit	0 to 65,535.	No
uint32	Unsigned integer	32 bit	0 to 4,294,967,295.	No
uint64	Unsigned integer	64 bit	0 to 18,446,744,073,709,551,615	No
float16	Binary float	16 bits	≈ ±6.55×10⁴	Yes
float32	Binary float	32 bits	≈ ±3.4×10³⁸	Yes
float64	Binary float	64 bits	≈ ±1.8×10³⁰⁸	Yes
float128	Binary float	128 bits	≈ ±1.2×10⁴⁹³²	Yes
nmtran-time	NM-TRAN time	n		No
nmtran-date	NM-TRAN date	n		No
str	General string	n		No

The default, and most common datatype, is float64.

drop#: Should this column be dropped

name#: Column name

symbol#: Symbol having the column name

type#: The type of the column. See DataVariable.type Note that all variables in one column must have the same type

variable#: If the column represent a single DataVariable return it else raise

variable_id#: Name of identifier column (e.g. DVID or ADMID)

variable_mapping#: Mapping from value in identifier column to DataVariable

variables#: All datavariables defined in this column

Methods Documentation

static convert_datatype_to_pd_dtype(datatype)[source]#

Convert Pharmpy datatype to pandas dtype

Parameters:: datatype (str) – String representing a Pharmpy datatype
Returns:: str – String representing a pandas dtype

Examples

>>> from pharmpy.model import ColumnInfo
>>> ColumnInfo.convert_datatype_to_pd_dtype("float64")
'float64'
>>> ColumnInfo.convert_datatype_to_pd_dtype("nmtran-date")
'str'

static convert_pd_dtype_to_datatype(dtype)[source]#

Convert pandas dtype to Pharmpy datatype

Parameters:: dtype (str) – String representing a pandas dtype
Returns:: str – String representing a Pharmpy datatype

Examples

>>> from pharmpy.model import ColumnInfo
>>> ColumnInfo.convert_pd_dtype_to_datatype("float64")
'float64'

classmethod create(name, variable_mapping=None, variable_id=None, drop=False, datatype='float64')[source]#

classmethod from_dict(d)[source]#

is_integer()[source]#

Check if the column datatype is integral

Returns:: bool – True if of integral datatype