DataVariable

class pharmpy.model.DataVariable(name, type='unknown', scale='ratio', count=False, properties={})

Bases: Immutable

Information about one variable represented by data

For long format datasets a data column can contain multiple data variables.

Parameters:

• name (str) – Variable name. Not the same as the name of the column

• type (str) – Type of variable (see the “type” attribute)

• scale (str) – Scale of measurement (see the “scale” attribute)

• count (bool) – True if count data or False otherwise

• properties (dict) – Other properties of the variable (see the “properties” attribute)

Attributes Summary

count	Does the data variable represent count data
name	Variable name
properties	Other properties of the DataVariable
scale	Scale of measurement
symbol	Symbol having the variable name
type	Type of column

Methods Summary

create(name[, type, scale, count, properties])
from_dict(d)
get_property(property)	Get a variable property with default if not defined
is_categorical()	Check if the data variable is categorical
is_numerical()	Check if the data variable is numerical
remove_property(property)	Remove a property
replace(**kwargs)	Replace properties and create a new DataVariable
set_property(property, value)	Set the value for a property
to_dict()

Attributes Documentation

count

Does the data variable represent count data

name

Variable name

properties

Other properties of the DataVariable

descriptor

Kind of data

descriptor	Description
age	Age (since birth)
body height	Human body height
body surface area	Body surface area (calculated)
body weight	Human body weight
lean body mass	Lean body mass
fat free mass	Fat free mass
time after dose	Time after dose
plasma concentration	Concentration of substance in blood plasma
subject identifier	Unique integer identifier for a subject
observation identifier	Unique integer identifier for an observation
pk measurement	Any kind of PK measurement
pd measurement	Any kind of PD measurement

unit

Unit of the data variable

Custom units are allowed, but units that are available in sympy.physics.units can be recognized.

categories

All possible values of categorical data

molar_mass

The molar mass of a substance in g/mol

scale

Scale of measurement

The statistical scale of measurement for the data variable. Can be one of ‘nominal’, ‘ordinal’, ‘interval’ and ‘rational’.

symbol

Symbol having the variable name

type

Type of column

type	Description
id	Individual identifier. Max one per DataFrame. All values have to be unique
idv	Independent variable. Max one per DataFrame.
dv	Observations of the dependent variable
dvid	Dependent variable ID
covariate	Covariate
dose	Dose amount
rate	Rate of infusion
additional	Number of additional doses
ii	Interdose interval
ss	Steady state dosing
event	0 = observation
mdv	0 = DV is observation value, 1 = DV is missing
admid	Administration ID
compartment	Compartment information (not yet exactly specified)
lloq	Lower limit of quantification
blq	Below limit of quantification indicator
unknown	Unkown type. This will be the default for columns that hasn’t been assigned a type

Methods Documentation

classmethod create(name, type='unknown', scale='ratio', count=False, properties={})

classmethod from_dict(d)

get_property(property)

Get a variable property with default if not defined

Parameters:

property (str) – The property to get

Returns:

Any – The value of the property or its default value

Examples

>>> from pharmpy.model import DataVariable
>>> var1 = DataVariable.create("WGT", properties={"unit": "kg"})
>>> var1.get_property("unit")
kilogram
>>> var2 = DataVariable.create("ID")
>>> var2.get_property("unit")
1

is_categorical()

Check if the data variable is categorical

Returns:

bool – True if categorical (nominal or ordinal) and False otherwise.

See also

is_numerical

Check if the data variable is numerical

Examples

>>> from pharmpy.model import DataVariable
>>> var1 = DataVariable.create("WGT", scale='ratio')
>>> var1.is_categorical()
False
>>> var2 = DataVariable.create("ID", scale='nominal')
>>> var2.is_categorical()
True

is_numerical()

Check if the data variable is numerical

Returns:

bool – True if numerical (interval or ratio) and False otherwise.

See also

is_categorical

Check if the data variable is categorical

Examples

>>> from pharmpy.model import DataVariable
>>> var1 = DataVariable.create("WGT", scale='ratio')
>>> var1.is_numerical()
True
>>> var2 = DataVariable.create("ID", scale='nominal')
>>> var2.is_numerical()
False

remove_property(property)

Remove a property

Parameters:

property (str) – The property to remove

Returns:

DataVariable – The updated DataVariable

Examples

>>> from pharmpy.model import DataVariable
>>> var1 = DataVariable.create("WGT", properties={"descriptor": "body weight"})
>>> var2 = var1.remove_property("body weight")

replace(**kwargs)

Replace properties and create a new DataVariable

set_property(property, value)

Set the value for a property

Parameters:

• property (str) – The property to set

• value (Any) – Value for the property

Returns:

DataVariable – The updated DataVariable

Examples

>>> from pharmpy.model import DataVariable
>>> var1 = DataVariable.create("WGT")
>>> var2 = var1.set_property("unit", "kg")
>>> var2.get_property("unit")
kilogram

to_dict()