skbio.table.Table.align_to_dataframe#

Table.align_to_dataframe(metadata, axis='sample')[source]#

Aligns dataframe against biom table, only keeping common ids.

Parameters:

metadatapd.DataFrame: The metadata, either respect to the sample metadata or observation metadata.
axis{‘sample’, ‘observation’}: The axis on which to operate.

Returns:

biom.Table: A filtered biom table.
pd.DataFrame: A filtered metadata table.

Examples

>>> from biom import Table
>>> import numpy as np
>>> import pandas as pd
>>> table = Table(np.array([[0, 0, 1, 1],
...                         [2, 2, 4, 4],
...                         [5, 5, 3, 3],
...                         [0, 0, 0, 1]]),
...               ['o1', 'o2', 'o3', 'o4'],
...               ['s1', 's2', 's3', 's4'])
>>> metadata = pd.DataFrame([['a', 'control'],
...                          ['c', 'diseased'],
...                          ['b', 'control']],
...                         index=['s1', 's3', 's2'],
...                         columns=['Barcode', 'Treatment'])
>>> res_table, res_metadata = table.align_to_dataframe(metadata)
>>> print(res_table)
# Constructed from biom file
#OTU ID s1      s2      s3
o1      0.0     0.0     1.0
o2      2.0     2.0     4.0
o3      5.0     5.0     3.0
>>> print(res_metadata)
   Barcode Treatment
s1       a   control
s2       b   control
s3       c  diseased