pandas.DataFrame.dex.to_indexset#

DataFrame.dex.to_indexset()#

Cast a DataFrame into an IndexSet1D/IndexSetND.

Note: The docplex-extensions pacakge has to be imported first to use this method with pandas.

Returns:
IndexSet1D or IndexSetND

  • A single-column DataFrame will be cast into an IndexSet1D consisting of its column values. The column name will be set as the IndexSet1D.name attribute (as str).

  • A multi-column DataFrame will be cast into an IndexSetND consisting of tuples, each containing row values. The column names will be set as the IndexSetND.names attribute (as list[str]).

Raises:
ValueError

If the DataFrame is empty.

TypeError

If the DataFrame has non-scalar value(s) (any iterable except string).

ValueError

If the DataFrame has duplicate rows.

See also

pandas.Series.dex.to_indexset

Cast a Series into an IndexSet1D.

pandas.Index.dex.to_indexset

Cast an Index into an IndexSet1D/IndexSetND.

Examples

>>> import pandas as pd
>>> import docplex_extensions  # required to access this method

Casting a single-column DataFrame into an IndexSet1D

>>> warehouses = pd.DataFrame(['WH-A', 'WH-B', 'WH-C'], columns=['WAREHOUSE'])
>>> warehouses
  WAREHOUSE
0      WH-A
1      WH-B
2      WH-C

>>> warehouses.dex.to_indexset()
IndexSet1D: (WAREHOUSE)
['WH-A', 'WH-B', 'WH-C']

Casting a multi-column DataFrame into an IndexSetND

>>> df = pd.DataFrame(
...     {
...         'PRODUCT': ['chair', 'chair', 'desk', 'desk'],
...         'WAREHOUSE': ['WH-A', 'WH-B', 'WH-B', 'WH-C'],
...         'PERIOD': [0, 1, 0, 1],
...     }
... )
>>> df
  PRODUCT WAREHOUSE  PERIOD
0   chair      WH-A       0
1   chair      WH-B       1
2    desk      WH-B       0
3    desk      WH-C       1

>>> df.dex.to_indexset()
IndexSetND: (PRODUCT, WAREHOUSE, PERIOD)
[('chair', 'WH-A', 0),
 ('chair', 'WH-B', 1),
 ('desk', 'WH-B', 0),
 ('desk', 'WH-C', 1)]

>>> df.set_index('WAREHOUSE')[['PRODUCT', 'PERIOD']].dex.to_indexset()
IndexSetND: (PRODUCT, PERIOD)
[('chair', 0),
 ('chair', 1),
 ('desk', 0),
 ('desk', 1)]
On this page