DataInfo#

class pharmpy.model.DataInfo(columns=(), path=None, separator=',', force_absolute_path=True)[source]#

Bases: Sequence, Immutable

Metadata for the dataset

Can be indexed to get ColumnInfo for the columns.

Parameters:
  • columns (list) – List of column names

  • path (Path) – Path to dataset file

  • separator (str) – Character or regexp separator for dataset

Attributes Summary

descriptorix

Descriptor indexer

dv_column

The dv column

id_column

The id column

idv_column

The idv column

names

All column names

path

Path of dataset file

separator

Separator for dataset file

typeix

Type indexer

types

All column types

Methods Summary

create([columns, path, separator, ...])

from_dict(d)

from_json(s)

Create DataInfo from JSON string

get_dtype_dict()

Create a dictionary from column names to pandas dtypes

read_json(path)

Read DataInfo from JSON file

replace(**kwargs)

set_column(col)

Set ColumnInfo of an existing column of the same name

set_dv_column(name)

set_id_column(name)

set_idv_column(name)

set_types(value)

Set types for all columns

to_dict()

to_json([path])

Attributes Documentation

descriptorix#

Descriptor indexer

Example

>>> from pharmpy.modeling import load_example_model
>>> model = load_example_model("pheno")
>>> model.datainfo.descriptorix['body weight'].names
['WGT']
dv_column#

The dv column

Examples

>>> from pharmpy.modeling import load_example_model
>>> model = load_example_model("pheno")
>>> model.datainfo.dv_column.name
'DV'
id_column#

The id column

Examples

>>> from pharmpy.modeling import load_example_model
>>> model = load_example_model("pheno")
>>> model.datainfo.id_column.name
'ID'
idv_column#

The idv column

Examples

>>> from pharmpy.modeling import load_example_model
>>> model = load_example_model("pheno")
>>> model.datainfo.idv_column.name
'TIME'
names#

All column names

Examples

>>> from pharmpy.modeling import load_example_model
>>> model = load_example_model("pheno")
>>> model.datainfo.names
['ID', 'TIME', 'AMT', 'WGT', 'APGR', 'DV', 'FA1', 'FA2']
path#

Path of dataset file

Examples

>>> from pharmpy.modeling import load_example_model
>>> model = load_example_model("pheno")
>>> str(model.datainfo.path).replace('\\', '/')     
'.../pharmpy/internals/example_models/pheno.dta'
separator#

Separator for dataset file

Can be a single character or a regular expression string.

typeix#

Type indexer

Example

>>> from pharmpy.modeling import load_example_model
>>> model = load_example_model("pheno")
>>> model.datainfo.typeix['covariate'].names
['WGT', 'APGR']
types#

All column types

Methods Documentation

classmethod create(columns=None, path=None, separator=',', force_absolute_path=True)[source]#
classmethod from_dict(d)[source]#
static from_json(s)[source]#

Create DataInfo from JSON string

Parameters:

s (str) – JSON string

Returns:

DataInfo – Created DataInfo object

get_dtype_dict()[source]#

Create a dictionary from column names to pandas dtypes

This can be used as input to some pandas functions to convert column to the correct pandas dtype.

Returns:

dict – Column name to pandas dtype

Examples

>>> from pharmpy.modeling import *
>>> model = load_example_model("pheno")
>>> model.datainfo.get_dtype_dict()
{'ID': 'int32',
 'TIME': 'float64',
 'AMT': 'float64',
 'WGT': 'float64',
 'APGR': 'float64',
 'DV': 'float64',
 'FA1': 'float64',
 'FA2': 'float64'}
static read_json(path)[source]#

Read DataInfo from JSON file

Parameters:

path (Path or str) – Path to JSON datainfo file

Returns:

DataInfo – Created DataInfo object

replace(**kwargs)[source]#
set_column(col)[source]#

Set ColumnInfo of an existing column of the same name

Parameters:

col (ColumnInfo) – New ColumnInfo

Returns:

DataInfo – Updated DataInfo

set_dv_column(name)[source]#
set_id_column(name)[source]#
set_idv_column(name)[source]#
set_types(value)[source]#

Set types for all columns

Parameters:

value (list or str) – Types to set. If only one this will be broadcast

Returns:

DataInfo – Updated datainfo

to_dict()[source]#
to_json(path=None)[source]#