gather

gather(__data, key='key', value='value', *args, *, drop_na=False, convert=False)

Reshape table by gathering it in to long format.

Parameters

Name	Description	Default
`__data`	The input data.	required
`key`	Name of the key (or measure) column, which holds the names of the columns that were turned into rows.	`'key'`
`value`	Name of the value column, which holds the values from the columns that were turned into rows.	`'value'`
`*args`	A selection of columns. If unspecified, all columns are selected. Any arguments you could pass to the select() verb are allowed.	`()`
`drop_na`	Whether to remove any rows where the value column is NA.	`False`

>>> import pandas as pd
>>> from siuba import _, gather

>>> df = pd.DataFrame({"id": ["a", "b"], "x": [1, 2], "y": [3, None]})

The code below gathers in all columns, except id:

>>> gather(df, "key", "value", -_.id)
  id key  value
0  a   x    1.0
1  b   x    2.0
2  a   y    3.0
3  b   y    NaN

>>> gather(df, "measure", "result", _.x, _.y, drop_na=True)
  id measure  result
0  a       x     1.0
1  b       x     2.0
2  a       y     3.0