enframe

In [1]:

# https://tibble.tidyverse.org/reference/enframe.html
%run nb_helpers.py

from datar.tibble import *
from datar.base import seq

nb_header(enframe, deframe, book='enframe')

# https://tibble.tidyverse.org/reference/enframe.html %run nb_helpers.py from datar.tibble import * from datar.base import seq nb_header(enframe, deframe, book='enframe')

Try this notebook on binder.

★ enframe

¶

Converts mappings or lists to one- or two-column data frames.¶

Args:¶

  x: a list, a dictionary or a dataframe with one or two columns
  name: and
  value: value Names of the columns that store the names and values.
    If None, a one-column dataframe is returned.
    value cannot be None

Returns:¶

  A data frame with two columns if name is not None (default) or
  one-column otherwise.

★ deframe

¶

Converts two-column data frames to a dictionary¶

using the first column as name and the second column as value.
If the input has only one column, a list.

Args:¶

  x: A data frame.

Returns:¶

  A dictionary or a list if only one column in the data frame.

In [2]:

enframe(seq(1,3))

enframe(seq(1,3))

Out[2]:

	name	value
	<int64>	<int64>
0	0	1
1	1	2
2	2	3

In [3]:

enframe(dict(a=5, b=7))

enframe(dict(a=5, b=7))

Out[3]:

	name	value
	<object>	<int64>
0	a	5
1	b	7

In [4]:

enframe(dict(one=1, two=[2,3], three=[4,5,6]))

enframe(dict(one=1, two=[2,3], three=[4,5,6]))

Out[4]:

	name	value
	<object>	<object>
0	one	1
1	two	[2, 3]
2	three	[4, 5, 6]

In [5]:

deframe(enframe(seq(3,1)))

deframe(enframe(seq(3,1)))

Out[5]:

{0: 3, 1: 2, 2: 1}

In [6]:

deframe(tibble(a=seq(1,3)))

deframe(tibble(a=seq(1,3)))

Out[6]:

array([1, 2, 3])

In [7]:

deframe(tibble(a=[seq(1,3)]))

deframe(tibble(a=[seq(1,3)]))

Out[7]:

array([array([1, 2, 3])], dtype=object)