issues: 166449498
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| 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
Do if one forgets to add |
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completed | 13221727 | issue |