issues

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

Hello,

I'm totally new to xray. I wonder if xray have odo support http://odo.readthedocs.org/

Kind regards

Should fix https://github.com/xray/xray/issues/684

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]: <xray.Dataset> 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]: <xray.Dataset> Dimensions: () Coordinates: empty Data variables: 0 int64 5 1 int64 7 2 int64 9

In [650]: ds0.sum() Out[650]: <xray.Dataset> Dimensions: () Coordinates: empty Data variables: 0 int64 5 1 int64 7 2 int64 9

In [651]: ds0.sum().sum() Out[651]: <xray.Dataset> Dimensions: () Coordinates: empty Data variables: 0 int64 5 1 int64 7 2 int64 9 ```

Kind regards

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