separate

separate(__data, col, into, sep='\[^a-zA-Z0-9\]', remove=True, convert=False, extra='warn', fill='warn')

Split col into len(into) piece. Return DataFrame with a column added for each piece.

Parameters

Name	Description	Default
`__data`	a DataFrame.	required
`col`	name of column to split (either string, or siu expression).	required
`into`	names of resulting columns holding each entry in split.	required
`sep`	regular expression used to split col. Passed to col.str.split method.	`'[^a-zA-Z0-9]'`
`remove`	whether to remove col from the returned DataFrame.	`True`
`convert`	whether to attempt to convert the split columns to numerics.	`False`
`extra`	what to do when more splits than into names. One of (“warn”, “drop” or “merge”). “warn” produces a warning; “drop” and “merge” currently not implemented.	`'warn'`
`fill`	what to do when fewer splits than into names. Currently not implemented.	`'warn'`

>>> import pandas as pd
>>> from siuba import separate

>>> df = pd.DataFrame({"label": ["S1-1", "S2-2"]})

Split into two columns:

>>> separate(df, "label", into = ["season", "episode"])
  season episode
0     S1       1
1     S2       2

Split, and try to convert columns to numerics:

>>> separate(df, "label", into = ["season", "episode"], convert = True)
  season  episode
0     S1        1
1     S2        2