dstack¶
- astropy.table.dstack(tables, join_type='outer', metadata_conflicts='warn')[source]¶
Stack columns within tables depth-wise
A
join_type
of ‘exact’ means that the tables must all have exactly the same column names (though the order can vary). Ifjoin_type
is ‘inner’ then the intersection of common columns will be the output. A value of ‘outer’ (default) means the output will have the union of all columns, with table values being masked where no common values are available.- Parameters:
- tables
Table
orRow
orpython:list
thereof Table(s) to stack along depth-wise with the current table Table columns should have same shape and name for depth-wise stacking
- join_type
python:str
Join type (‘inner’ | ‘exact’ | ‘outer’), default is ‘outer’
- metadata_conflicts
python: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.
- tables
- Returns:
- stacked_table
Table
object
New table containing the stacked data from the input tables.
- stacked_table
Examples
To stack two tables along rows do:
>>> from astropy.table import dstack, Table >>> t1 = Table({'a': [1., 2.], 'b': [3., 4.]}, names=('a', 'b')) >>> t2 = Table({'a': [5., 6.], 'b': [7., 8.]}, names=('a', 'b')) >>> print(t1) a b --- --- 1.0 3.0 2.0 4.0 >>> print(t2) a b --- --- 5.0 7.0 6.0 8.0 >>> print(dstack([t1, t2])) a b ---------- ---------- 1.0 .. 5.0 3.0 .. 7.0 2.0 .. 6.0 4.0 .. 8.0