html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/2459#issuecomment-648721465,https://api.github.com/repos/pydata/xarray/issues/2459,648721465,MDEyOklzc3VlQ29tbWVudDY0ODcyMTQ2NQ==,5442433,2020-06-24T09:55:00Z,2020-06-24T09:55:00Z,NONE,"Hi All. I stumble across the same issue trying to convert a 5000 column dataframe to xarray (it was never going to happen...).
I found a workaround and I am posting the test below. Hope it helps.

```python
import xarray as xr
import pandas as pd
import numpy as np

xr.__version__

    '0.15.1'

pd.__version__

    '1.0.5'

df = pd.DataFrame(np.random.randn(200, 500))

%%time
one = df.to_xarray()

    CPU times: user 29.6 s, sys: 60.4 ms, total: 29.6 s
    Wall time: 29.7 s

%%time
dic={}
for name in df.columns:
    dic.update({name:(['index'],df[name].values)})

two = xr.Dataset(dic, coords={'index': ('index', df.index.values)})         

    CPU times: user 17.6 ms, sys: 158 µs, total: 17.8 ms
    Wall time: 17.8 ms

one.equals(two)

    True

```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,365973662
https://github.com/pydata/xarray/issues/2459#issuecomment-586552823,https://api.github.com/repos/pydata/xarray/issues/2459,586552823,MDEyOklzc3VlQ29tbWVudDU4NjU1MjgyMw==,40251676,2020-02-15T04:31:54Z,2020-02-15T04:31:54Z,NONE,"@crusaderky Thanks for the pointer to `xarray.DataArray(df)` -- that makes my life a ton easier. 

<br>

That said, if it helps anyone to know, I did just want a `DataArray`, but figured there was no alternative to first running the rather singular `to_xarray`. I also still find the runtime surprising, though I know nothing about `xarray`'s internals.



","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,365973662
https://github.com/pydata/xarray/issues/2459#issuecomment-586066908,https://api.github.com/repos/pydata/xarray/issues/2459,586066908,MDEyOklzc3VlQ29tbWVudDU4NjA2NjkwOA==,40251676,2020-02-14T02:25:25Z,2020-02-14T02:25:25Z,NONE,"I've run into this twice. This time I'm seeing a difference of very roughly 100x or more just using a transpose -- I can't test or time it properly right now, but this is what it looks like:

```
ipdb> df
x              a       b  ...    c      d
y              0       0  ...    7      7
z                         ...            
0       0.000000     0.0  ...  0.0    0.0
1      -0.000416     0.0  ...  0.0    0.0

[2 rows x 2932 columns]
ipdb> df.to_xarray()

<I quit out because it takes at least 30s>

ipdb> df.T.to_xarray()

<Finishes instantly>

```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,365973662