issues

Table actions

2 rows where type = "issue" and user = 25102059 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date), closed_at (date)

state 2

type 1

  • issue · 2 ✖

repo 1

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
1817880272 I_kwDOAMm_X85sWqbQ 8013 np.cumproduct deprecated quantsnus 25102059 closed 0     4 2023-07-24T08:11:01Z 2023-07-31T16:46:00Z 2023-07-31T16:46:00Z CONTRIBUTOR      

What is your issue?

Since numpy version 1.25.0 np.cumproduct is deprecated in favor of np.cumprod.

The coordinates to_index() method still uses it https://github.com/pydata/xarray/blob/971be103d6376d6572d1f12d32526f12f07ae2c7/xarray/core/coordinates.py#L144 which results in an unecessary DeprecationWarning.

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/8013/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   completed xarray 13221727 issue
1613054013 I_kwDOAMm_X85gJUA9 7593 Plotting with time-zone-aware pd.Timestamp axis not possible quantsnus 25102059 open 0     6 2023-03-07T09:32:49Z 2023-05-06T03:24:46Z   CONTRIBUTOR      

What is your issue?

When trying to use the plot-method on a DataArray that contains a time axis with time zone aware pandas Timestamps a TypeError is raised.

As a minimal example: python import pandas as pd import numpy as np import xarray as xr time = pd.date_range("2000-02-02 08:00+01:00","2000-02-02 09:00+01:00", 121) val = np.arange(121)**2 xar = xr.DataArray(val, coords=dict(time=time)) xar.plot() Results in:

TypeError: Plotting requires coordinates to be numeric, boolean, or dates of type numpy.datetime64, datetime.datetime, cftime.datetime or pandas.Interval. Received data of type object instead.

While matplotlib is capable of handling it. Not in a nice way, but at least without crashing: python import matplotlib.pyplot as plt plt.figure() plt.plot(xar.time, xar.values)

I tried that the same result can be achieved, if in the method issuing the TypeError https://github.com/pydata/xarray/blob/830ee6de0d545c997df84fe69b0ac2334bde1d1b/xarray/plot/utils.py#L669-L681 also accepts the pandas DatetimeTZDtype as a dtype, i.e. it is added to the tuple numpy_types.

If there are no objections I would issue a PR extending the tuple.

Related observations

_ensure_plottable removal

I found discussions on removing the _ensure_plottable method entirely (#5762, #5763), which was not followed through but would likely also solve this issue.

Pandas

Pandas itself is able to even plot the time stamps in a nice way. So, maybe in the long-term it might make sense to use these capabilities. python xar.to_series().plot() 

{
    "url": "https://api.github.com/repos/pydata/xarray/issues/7593/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 issue

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [issues] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [state] TEXT,
   [locked] INTEGER,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [comments] INTEGER,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [author_association] TEXT,
   [active_lock_reason] TEXT,
   [draft] INTEGER,
   [pull_request] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [state_reason] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [type] TEXT
);
CREATE INDEX [idx_issues_repo]
    ON [issues] ([repo]);
CREATE INDEX [idx_issues_milestone]
    ON [issues] ([milestone]);
CREATE INDEX [idx_issues_assignee]
    ON [issues] ([assignee]);
CREATE INDEX [idx_issues_user]
    ON [issues] ([user]);