DataInfo

class pharmpy.model.DataInfo(columns=(), path=None, separator=',', missing_data_token=None)

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

• missing_data_token (str) – Token for missing data

Attributes Summary

descriptorix	Descriptor indexer
dv_column	The dv column
id_column	The id column
idv_column	The idv column
missing_data_token	Token for missing data
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, ...])
find_single_column_name(type[, default])	Find name of single column given type
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'

missing_data_token

Token for missing data

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=',', missing_data_token=None)

find_single_column_name(type, default=None)

Find name of single column given type

Finds single column name with a given type, else provided default. Raises if more than one column is found or if no column is found and no default is given.

Parameters:

• type (str) – Column type

• default (Optional[str]) – Default if column type is not found

Returns:

str – Name of column

classmethod from_dict(d)

static from_json(s)

Create DataInfo from JSON string

Parameters:

s (str) – JSON string

Returns:

DataInfo – Created DataInfo object

get_dtype_dict()

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)

Read DataInfo from JSON file

Parameters:

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

Returns:

DataInfo – Created DataInfo object

replace(**kwargs)

set_column(col)

Set ColumnInfo of an existing column of the same name

Parameters:

col (ColumnInfo) – New ColumnInfo

Returns:

DataInfo – Updated DataInfo

set_dv_column(name)

set_id_column(name)

set_idv_column(name)

set_types(value)

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()

to_json(path=None)