-
DataFrame.to_xarray()
[source] -
Return an xarray object from the pandas object.
Returns: a DataArray for a Series
a Dataset for a DataFrame
a DataArray for higher dims
Notes
See the xarray docs
Examples
12345678>>> df
=
pd.DataFrame({
'A'
: [
1
,
1
,
2
],
'B'
: [
'foo'
,
'bar'
,
'foo'
],
'C'
: np.arange(
4.
,
7
)})
>>> df
A B C
0
1
foo
4.0
1
1
bar
5.0
2
2
foo
6.0
123456789>>> df.to_xarray()
<xarray.Dataset>
Dimensions: (index:
3
)
Coordinates:
*
index (index) int64
0
1
2
Data variables:
A (index) int64
1
1
2
B (index)
object
'foo'
'bar'
'foo'
C (index) float64
4.0
5.0
6.0
12345678910>>> df
=
pd.DataFrame({
'A'
: [
1
,
1
,
2
],
'B'
: [
'foo'
,
'bar'
,
'foo'
],
'C'
: np.arange(
4.
,
7
)}
).set_index([
'B'
,
'A'
])
>>> df
C
B A
foo
1
4.0
bar
1
5.0
foo
2
6.0
12345678>>> df.to_xarray()
<xarray.Dataset>
Dimensions: (A:
2
, B:
2
)
Coordinates:
*
B (B)
object
'bar'
'foo'
*
A (A) int64
1
2
Data variables:
C (B, A) float64
5.0
nan
4.0
6.0
12345678910>>> p
=
pd.Panel(np.arange(
24
).reshape(
4
,
3
,
2
),
items
=
list
(
'ABCD'
),
major_axis
=
pd.date_range(
'20130101'
, periods
=
3
),
minor_axis
=
[
'first'
,
'second'
])
>>> p
<
class
'pandas.core.panel.Panel'
>
Dimensions:
4
(items) x
3
(major_axis) x
2
(minor_axis)
Items axis: A to D
Major_axis axis:
2013
-
01
-
01
00
:
00
:
00
to
2013
-
01
-
03
00
:
00
:
00
Minor_axis axis: first to second
123456789101112131415161718>>> p.to_xarray()
<xarray.DataArray (items:
4
, major_axis:
3
, minor_axis:
2
)>
array([[[
0
,
1
],
[
2
,
3
],
[
4
,
5
]],
[[
6
,
7
],
[
8
,
9
],
[
10
,
11
]],
[[
12
,
13
],
[
14
,
15
],
[
16
,
17
]],
[[
18
,
19
],
[
20
,
21
],
[
22
,
23
]]])
Coordinates:
*
items (items)
object
'A'
'B'
'C'
'D'
*
major_axis (major_axis) datetime64[ns]
2013
-
01
-
01
2013
-
01
-
02
2013
-
01
-
03
# noqa
*
minor_axis (minor_axis)
object
'first'
'second'
DataFrame.to_xarray()

2025-01-10 15:47:30
Please login to continue.