plydata.tidy.gather

class plydata.tidy.gather(*args, **kwargs)

Collapse multiple columns into key-value pairs.

You use gather() when you notice that you have columns that are not variables.

Parameters

datadataframe, optional

Useful when not using the >> operator.

keystr

Name of the variable column

valuestr

Name of the value column

*columnslist-like | select | str | slice

Columns to be gathered and whose contents will make values.

Examples

>>> import pandas as pd
>>> df = pd.DataFrame({
...     'name': ['mary', 'oscar', 'martha', 'john'],
...     'math': [92, 83, 85, 90],
...     'art': [75, 95, 80, 72]
... })
>>> df
     name  math  art
0    mary    92   75
1   oscar    83   95
2  martha    85   80
3    john    90   72
>>> df >> gather('subject', 'grade', ['math', 'art'])
     name subject  grade
0    mary    math     92
1   oscar    math     83
2  martha    math     85
3    john    math     90
4    mary     art     75
5   oscar     art     95
6  martha     art     80
7    john     art     72

You can use the select verb to choose the columns

>>> df >> gather('subject', 'grade', select('math', 'art'))
     name subject  grade
0    mary    math     92
1   oscar    math     83
2  martha    math     85
3    john    math     90
4    mary     art     75
5   oscar     art     95
6  martha     art     80
7    john     art     72
>>> df >> gather('subject', 'grade', select('-name'))
     name subject  grade
0    mary    math     92
1   oscar    math     83
2  martha    math     85
3    john    math     90
4    mary     art     75
5   oscar     art     95
6  martha     art     80
7    john     art     72

gather('subject', 'grade', '-name') without the select would have worked.

>>> df >> gather('subject', 'grade', select(startswith='m'))
     name  art subject  grade
0    mary   75    math     92
1   oscar   95    math     83
2  martha   80    math     85
3    john   72    math     90