Series.to_numpy() → None

Not implemented.

In pandas this returns a Numpy representation of the Series. This would involve scan/scrolling the entire index.

If this is required, call ed.eland_to_pandas(ed_series).values, but beware this will scan/scroll the entire Elasticsearch index(s) into memory.


>>> ed_s = ed.Series('localhost', 'flights', name='Carrier').head(5)
>>> pd_s = ed.eland_to_pandas(ed_s)
>>> print(f"type(ed_s)={type(ed_s)}\ntype(pd_s)={type(pd_s)}")
type(ed_s)=<class 'eland.series.Series'>
type(pd_s)=<class 'pandas.core.series.Series'>
>>> ed_s
0     Kibana Airlines
1    Logstash Airways
2    Logstash Airways
3     Kibana Airlines
4     Kibana Airlines
Name: Carrier, dtype: object
>>> pd_s.to_numpy()
array(['Kibana Airlines', 'Logstash Airways', 'Logstash Airways',
       'Kibana Airlines', 'Kibana Airlines'], dtype=object)