hstack

astropy.table.hstack(tables, join_type='outer', uniq_col_name='{col_name}_{table_name}', table_names=None, metadata_conflicts='warn')[source]

Stack tables along columns (horizontally)

A join_type of ‘exact’ means that the tables must all have exactly the same number of rows. If join_type is ‘inner’ then the intersection of rows will be the output. A value of ‘outer’ (default) means the output will have the union of all rows, with table values being masked where no common values are available.

Parameters:
tablesTable or Row or python:list thereof

Tables to stack along columns (horizontally) with the current table

join_typepython:str

Join type (‘inner’ | ‘exact’ | ‘outer’), default is ‘outer’

uniq_col_namepython:str or python:None

String generate a unique output column name in case of a conflict. The default is ‘{col_name}_{table_name}’.

table_namespython:list of python:str or python:None

Two-element list of table names used when generating unique output column names. The default is [‘1’, ‘2’, ..].

metadata_conflictspython:str
How to proceed with metadata conflicts. This should be one of:
  • 'silent': silently pick the last conflicting meta-data value

  • 'warn': pick the last conflicting meta-data value, but emit a warning (default)

  • 'error': raise an exception.

Returns:
stacked_tableTable object

New table containing the stacked data from the input tables.

Examples

To stack two tables horizontally (along columns) do:

>>> from astropy.table import Table, hstack
>>> t1 = Table({'a': [1, 2], 'b': [3, 4]}, names=('a', 'b'))
>>> t2 = Table({'c': [5, 6], 'd': [7, 8]}, names=('c', 'd'))
>>> print(t1)
 a   b
--- ---
  1   3
  2   4
>>> print(t2)
 c   d
--- ---
  5   7
  6   8
>>> print(hstack([t1, t2]))
 a   b   c   d
--- --- --- ---
  1   3   5   7
  2   4   6   8