DataFrame.
count
Count non-NA cells for each column.
Counts are based on exists queries against ES.
This is inefficient, as it creates N queries (N is number of fields). An alternative approach is to use value_count aggregations. However, they have issues in that:
TODO - add additional pandas.DataFrame.count features
Summary of column counts
See also
Examples
>>> df = ed.DataFrame('localhost', 'ecommerce', columns=['customer_first_name', 'geoip.city_name']) >>> df.count() customer_first_name 4675 geoip.city_name 4094 dtype: int64