skbio.metadata.MetadataColumn#

class skbio.metadata.MetadataColumn(series, missing_scheme='blank')[source]#

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

`missing_scheme`	Return the vocabulary used to encode missing values.
`name`	Metadata column name.
`type`

Attributes (inherited)

`id_count`	Number of metadata IDs.
`id_header`	Name identifying the IDs associated with the metadata.
`ids`	IDs associated with the metadata.

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.
`to_dataframe`([encode_missing])	Create a pandas dataframe from the metadata column.
`to_series`([encode_missing])	Create a pandas series from the metadata column.

Methods (inherited)

`read`([format])	Create a new `MetadataColumn` instance from a file.
`save`(filepath[, ext])	Save a TSV metadata file.
`write`(file[, format])	Write an instance of `MetadataColumn` to a file.

Special methods

`__eq__`(other)	Determine if this metadata column is equal to another.
`__ne__`(other)	Determine if this metadata column is not equal to another.

Special methods (inherited)

`__ge__`(value, /)	Return self>=value.
`__getstate__`(/)	Helper for pickle.
`__gt__`(value, /)	Return self>value.
`__le__`(value, /)	Return self<=value.
`__lt__`(value, /)	Return self<value.
`__str__`(/)	Return str(self).

Details

missing_scheme#

Return the vocabulary used to encode missing values.

This property is read-only.

Returns:

str: “blank”, “no-missing”, or “INSDC:missing”

name#

Metadata column name.

This property is read-only.

Returns:

str: Metadata column name.

type = None#

__eq__(other)[source]#

Determine if this metadata column is equal to another.

MetadataColumn objects are equal if their IDs, column names, column types, ID headers and metadata values are equal.

Parameters:

otherMetadataColumn: Metadata column to test for equality.

Returns:

bool: Indicates whether this MetadataColumn object is equal to other.