Implement functions that will return pandas'es DataFrame instead of xarray's DataArray

[ramil-quantnet]

[gborodin]

def xr_to_pd(names: list, min_date: str) -> dict:
    xarray_data = load_data(min_date=min_date,
                            dims=("time", "field", "asset"),
                            assets=names)
    pandas_dict = {}
    for i in range(len(names)):
        single_asset = xarray_data.loc[:, :, names[i]].to_pandas()
        pandas_dict[names[i].split(':')[1]] = single_asset
    return pandas_dict

[gborodin]

Example of work:
xr_to_pd(['NASDAQ:GOOG','NASDAQ:AAPL'],'2016-01-01')

[qnt-dmitry]

It is not necessary, you can simply convert xarray's structures to pandas structures and back using these functions:

http://xarray.pydata.org/en/stable/generated/xarray.DataArray.to_pandas.html
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_xarray.html

However, if there are some other participants, who want this feature, we will add it.