TabularMSA.positional_metadata¶pd.DataFrame containing metadata along an axis.
State: Stable as of 0.4.0.
Notes
This property can be set and deleted. When setting new positional
metadata, a shallow copy is made and the pd.DataFrame index is set
to pd.RangeIndex(start=0, stop=axis_len, step=1).
Examples
Note
scikit-bio objects with positional metadata share a common
interface for accessing and manipulating their positional metadata.
The following examples use scikit-bio’s DNA class to demonstrate
positional metadata behavior. These examples apply to all other
scikit-bio objects storing positional metadata.
Create a DNA sequence with positional metadata:
>>> from skbio import DNA
>>> seq = DNA(
... 'ACGT',
... positional_metadata={'quality': [3, 3, 20, 11],
... 'exons': [True, True, False, True]})
>>> seq
DNA
-----------------------------
Positional metadata:
'exons': <dtype: bool>
'quality': <dtype: int64>
Stats:
length: 4
has gaps: False
has degenerates: False
has definites: True
GC-content: 50.00%
-----------------------------
0 ACGT
Retrieve positional metadata:
>>> seq.positional_metadata
exons quality
0 True 3
1 True 3
2 False 20
3 True 11
Update positional metadata:
>>> seq.positional_metadata['gaps'] = seq.gaps()
>>> seq.positional_metadata
exons quality gaps
0 True 3 False
1 True 3 False
2 False 20 False
3 True 11 False
Set positional metadata:
>>> seq.positional_metadata = {'degenerates': seq.degenerates()}
>>> seq.positional_metadata
degenerates
0 False
1 False
2 False
3 False
Delete positional metadata:
>>> seq.has_positional_metadata()
True
>>> del seq.positional_metadata
>>> seq.positional_metadata
Empty DataFrame
Columns: []
Index: [0, 1, 2, 3]
>>> seq.has_positional_metadata()
False