neurotools.misc.text.name_replace(in_obj, to_replace, replace_with)#

Helper function to perform simple text replacement but over arbitrary objects.

  • in_obj (list, set or pandas.DataFrame) –

    The object in which to replace all sub objects of, or in the case of DataFrame input the column names of.

    Note: This replacement occurs in some cases in-place rather than on a copy of the object (except in the case of set input).

  • to_replace (str or list of str) – The str in which to replace with other argument replace_with. In the case that a list of str is passed, then any of the elements of the passed list will be if found replaced with the passed argument for replace_with.

  • replace_with (str) – The str in which all instances of to_replace should be replaced with.


out_obj – The in_obj but with text replacement performed / column name replacement.

Return type

list, set or pandas.DataFrame


In [1]: import pandas as pd

In [2]: from neurotools.misc.text import name_replace

# Base case
In [3]: name_replace(['cow123', 'goat123', 'somethingelse'], '123', '456')
Out[3]: ['cow456', 'goat456', 'somethingelse']

# DataFrame case
In [4]: df = pd.DataFrame(columns=['cow123', 'goat123', 'somethingelse'])

In [5]: name_replace(df, '123', '456')
Empty DataFrame
Columns: [cow456, goat456, somethingelse]
Index: []

# to_replace list case
In [6]: name_replace(in_obj=['cow123', 'goat123', 'somethingelse'],
   ...:              to_replace=['123', 'something'],
   ...:              replace_with='456')
Out[6]: ['cow456', 'goat456', '456else']