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 123923598,MDU6SXNzdWUxMjM5MjM1OTg=,683,Store xray.Dataset to MongoDB,5049737,closed,0,,,7,2015-12-26T10:33:06Z,2020-12-07T01:07:20Z,2020-12-07T01:07:20Z,MEMBER,,,,"Hello, it will be nice if xray Datasets could be stored easily to MongoDB. Maybe Monary (not Pymongo) should be considered https://monary.readthedocs.org/ Kind regards ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/683/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 109649145,MDU6SXNzdWUxMDk2NDkxNDU=,607,odo support,5049737,closed,0,,,2,2015-10-03T22:27:12Z,2019-01-15T20:15:22Z,2019-01-15T20:15:22Z,MEMBER,,,,"Hello, I'm totally new to xray. I wonder if xray have odo support http://odo.readthedocs.org/ Kind regards ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/607/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 123983561,MDU6SXNzdWUxMjM5ODM1NjE=,686,sum of sum,5049737,closed,0,,,2,2015-12-27T15:34:31Z,2015-12-27T20:00:05Z,2015-12-27T20:00:05Z,MEMBER,,,,"Hello, sum of sum behave differently between Pandas and xray. I don't if that's an issue or a feature. ``` In [644]: df0=pd.DataFrame([[1,2,3],[4,5,6]]) In [645]: df0.sum() Out[645]: 0 5 1 7 2 9 dtype: int64 In [646]: df0.sum().sum() Out[646]: 21 In [647]: ds0=xray.Dataset.from_dataframe(df0) In [648]: ds0 Out[648]: Dimensions: (index: 2) Coordinates: * index (index) int64 0 1 Data variables: 0 (index) int64 1 4 1 (index) int64 2 5 2 (index) int64 3 6 In [649]: ds0.sum().sum() Out[649]: Dimensions: () Coordinates: *empty* Data variables: 0 int64 5 1 int64 7 2 int64 9 In [650]: ds0.sum() Out[650]: Dimensions: () Coordinates: *empty* Data variables: 0 int64 5 1 int64 7 2 int64 9 In [651]: ds0.sum().sum() Out[651]: Dimensions: () Coordinates: *empty* Data variables: 0 int64 5 1 int64 7 2 int64 9 ``` Kind regards ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/686/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 123971294,MDU6SXNzdWUxMjM5NzEyOTQ=,684,to_masked_array should have an option to always return array,5049737,closed,0,,,1,2015-12-27T10:15:59Z,2015-12-27T19:40:02Z,2015-12-27T19:40:02Z,MEMBER,,,,"Hello, I'm working with Monary and xray and faced a problem because `xray.DataArray.to_masked_array` doesn't return an array of boolean but just a boolean. ``` In [1]: ma.masked_array(df['Bid'].values, df['Bid'].isnull()) Out[1]: masked_array(data = [0.81 0.88805 0.8880899999999999 ..., 0.87531 0.87531 0.87531], mask = [False False False ..., False False False], fill_value = 1e+20) In [2]: ds.Bid.to_masked_array() Out[2]: masked_array(data = [ 0.81 0.88805 0.88809 ..., 0.87531 0.87531 0.87531], mask = False, fill_value = 1e+20) ``` So we have ``` mask = False, ``` instead of ``` mask = [False False False ..., False False False], ``` It will be nice if a parameter could be passed to always return array. Here is my code With sample data from https://drive.google.com/file/d/0B8iUtWjZOTqla3ZZTC1FS0pkZXc/view?usp=sharing ``` import pandas as pd import xray df = pd.read_csv(""AUDUSD-2014-01.csv"", names=['Symbol', 'Date', 'Bid', 'Ask']) df['Date'] = pd.to_datetime(df['Date'], format='%Y%m%d %H:%M:%S.%f') ds = xray.Dataset.from_dataframe(df) ds = ds[['Bid', 'Ask']] lst_cols = list(map(lambda col: ds[col].to_masked_array(), ds.data_vars)) mparams = monary.MonaryParam.from_lists(lst_cols, list(ds.data_vars), ['float64', 'float64']) m.insert('monary_db', 'ticks', mparams) ``` It raises ``` //anaconda/lib/python3.4/site-packages/monary/monary.py in insert(self, db, coll, params, write_concern) 763 for i, param in enumerate(params): 764 data_p = param.array.data.ctypes.data_as(ctypes.c_void_p) --> 765 mask_p = param.array.mask.ctypes.data_as(ctypes.c_void_p) 766 767 if cmonary.monary_set_column_item( AttributeError: 'numpy.bool_' object has no attribute 'ctypes' ``` see `lst_cols` ``` [masked_array(data = [ 0.88796 0.88805 0.88809 ..., 0.87531 0.87531 0.87531], mask = False, fill_value = 1e+20), masked_array(data = [ 0.88922 0.88914 0.8891 ..., 0.87588 0.87574 0.87574], mask = False, fill_value = 1e+20)] ``` An other option could be to fix this on Monary side https://bitbucket.org/djcbeach/monary/issues/22/insert-doesnt-work-correctly-when-mask-is Kind regards ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/684/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue