tables_io.utils.slice_utils

Slicing functions for tables_io

Functions

slice_table(obj, the_slice)	Slice a Table-like object. The slice may be supplied as a single integer,
slice_tabledict(→ Mapping)	Slice many Table-like objects inside a TableDict-like object.

Module Contents

slice_table(obj, the_slice: slice)

Slice a Table-like object. The slice may be supplied as a single integer, or as a python slice(start,stop,step) object.

Parameters:

• obj (table-like) – Table like object to slice

• the_slice (slice or int) – The slice of the object to take. Either a single integer, or a python slice(start, stop, step) object.

Returns:

tab – The slice of the table

Return type:

table-like

Example

>>> import tables_io
>>> import pandas as pd
>>> df = pd.DataFrame({'col1': [1,2,3], 'col2':[3,4,5]})
>>> tables_io.slice_table(df, slice(1,2))
   col1  col2
1     2     4

slice_tabledict(odict: Mapping, the_slice: slice) → Mapping

Slice many Table-like objects inside a TableDict-like object. This will take the same slice from each of the Table-like objects, and return a TableDict-like object with those slices.

Parameters:

• odict (TableDict-like) – Dictionary of objects to slice

• the_slice (slice) – A python slice(start, stop, step) object of the slice to take.

Returns:

odict – The sliced tables

Return type:

TableDict-like

Example

>>> import tables_io
>>> from astropy.table import Table
>>> odict = OrderedDict([('tab_1', Table([[1,2],[5,3]],names=("x","y"))),
... ('tab_2', Table([[1,2,4],[5,3,7]],names=("x","y")))])
>>> tables_io.slice(odict, slice(2,3))
OrderedDict([('tab_1',
      <Table length=0>
        x     y
      int64 int64
      ----- -----),
     ('tab_2',
      <Table length=1>
        x     y
      int64 int64
      ----- -----
          4     7)])