skbio.metadata.MetadataColumn

class skbio.metadata.MetadataColumn(series, missing_scheme='blank')

Abstract base class representing a single metadata column.

Concrete subclasses represent specific metadata column types, e.g. CategoricalMetadataColumn and NumericMetadataColumn.

See the Metadata class docstring for details about Metadata and MetadataColumn objects, including a description of column types.

The main difference in constructing MetadataColumn vs Metadata objects is that MetadataColumn objects are constructed from a pandas.Series object instead of a pandas.DataFrame. Otherwise, the same restrictions, considerations, and data normalization are applied as with Metadata objects.

Parameters:

seriespd.Series

The series to construct a column from.

missing_scheme“blank”, “no-missing”, “INSDC:missing”

How to interpret terms for missing values. These will be converted to NaN. The default treatment is to take no action.

Attributes

id_count	Number of metadata IDs.
id_header	Name identifying the IDs associated with the metadata.
ids	IDs associated with the metadata.
missing_scheme	Return the vocabulary used to encode missing values.
name	Metadata column name.
type

Built-ins

__eq__(other)	Determine if this metadata column is equal to another.
__ge__(value, /)	Return self>=value.
__getstate__(/)	Helper for pickle.
__gt__(value, /)	Return self>value.
__le__(value, /)	Return self<=value.
__lt__(value, /)	Return self<value.
__ne__(other)	Determine if this metadata column is not equal to another.
__str__(/)	Return str(self).

Methods

drop_missing_values()	Filter out missing values from the metadata column.
filter_ids(ids_to_keep)	Filter metadata column by IDs.
get_ids([where_values_missing])	Retrieve IDs matching search criteria.
get_missing()	Return a series containing only missing values (with an index).
get_value(id)	Retrieve metadata column value associated with an ID.
has_missing_values()	Determine if the metadata column has one or more missing values.
save(filepath[, ext])	Save a TSV metadata file.
to_dataframe([encode_missing])	Create a pandas dataframe from the metadata column.
to_series([encode_missing])	Create a pandas series from the metadata column.