id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
166449498,MDU6SXNzdWUxNjY0NDk0OTg=,908,Histogram plot of DataArray can be extremely slow,222557,closed,0,,,3,2016-07-19T22:11:38Z,2016-10-22T00:58:11Z,2016-10-22T00:58:11Z,NONE,,,,"The speed of plotting a histogram of a large DataArray depends a lot how you do it:

```
import xarray as xr
import numpy as np
import matplotlib.pyplot as plt

nPoints = 100000
data = xr.DataArray(np.random.random(nPoints),dims=['time'],coords=[np.arange(nPoints)])
```

It take sonly some ms if you use

```
plt.figure()
%time data.plot.hist()

plt.figure()
%time plt.hist(data.values)
```

However, if you omit `.values` it takes extremely long:

```
In [12]: %time plt.hist(data)
CPU times: user 2min, sys: 9.73 s, total: 2min 9s
Wall time: 2min 3s
```

Do if one forgets to add `.values` or to use xarray's plot routine, one can be stuck for a long time. I have to kill python 1-2 per day due to that issue.
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