Added Series metric aggs + Series docs

Also, improved Series.to_string()

docs/source/reference/api/eland.Series.add.rst

@@ -0,0 +1,6 @@
+eland.Series.add
+================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.add

docs/source/reference/api/eland.Series.describe.rst

@@ -0,0 +1,6 @@
+eland.Series.describe
+=====================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.describe

docs/source/reference/api/eland.Series.div.rst

@@ -0,0 +1,6 @@
+eland.Series.div
+================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.div

docs/source/reference/api/eland.Series.empty.rst

@@ -0,0 +1,6 @@
+eland.Series.empty
+==================
+
+.. currentmodule:: eland
+
+.. autoattribute:: Series.empty

docs/source/reference/api/eland.Series.floordiv.rst

@@ -0,0 +1,6 @@
+eland.Series.floordiv
+=====================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.floordiv

docs/source/reference/api/eland.Series.head.rst

@@ -0,0 +1,6 @@
+eland.Series.head
+=================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.head

docs/source/reference/api/eland.Series.index.rst

@@ -0,0 +1,6 @@
+eland.Series.index
+==================
+
+.. currentmodule:: eland
+
+.. autoattribute:: Series.index

docs/source/reference/api/eland.Series.max.rst

@@ -0,0 +1,6 @@
+eland.Series.max
+================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.max

docs/source/reference/api/eland.Series.mean.rst

@@ -0,0 +1,6 @@
+eland.Series.mean
+=================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.mean

docs/source/reference/api/eland.Series.min.rst

@@ -0,0 +1,6 @@
+eland.Series.min
+================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.min

docs/source/reference/api/eland.Series.mod.rst

@@ -0,0 +1,6 @@
+eland.Series.mod
+================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.mod

docs/source/reference/api/eland.Series.mul.rst

@@ -0,0 +1,6 @@
+eland.Series.mul
+================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.mul

docs/source/reference/api/eland.Series.name.rst

@@ -0,0 +1,6 @@
+eland.Series.name
+=================
+
+.. currentmodule:: eland
+
+.. autoattribute:: Series.name

docs/source/reference/api/eland.Series.nunique.rst

@@ -0,0 +1,6 @@
+eland.Series.nunique
+====================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.nunique

docs/source/reference/api/eland.Series.pow.rst

@@ -0,0 +1,6 @@
+eland.Series.pow
+================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.pow

docs/source/reference/api/eland.Series.rename.rst

@@ -0,0 +1,6 @@
+eland.Series.rename
+===================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.rename

docs/source/reference/api/eland.Series.rst

@@ -0,0 +1,6 @@
+eland.Series
+============
+
+.. currentmodule:: eland
+
+.. autoclass:: Series

docs/source/reference/api/eland.Series.shape.rst

@@ -0,0 +1,6 @@
+eland.Series.shape
+==================
+
+.. currentmodule:: eland
+
+.. autoattribute:: Series.shape

docs/source/reference/api/eland.Series.sub.rst

@@ -0,0 +1,6 @@
+eland.Series.sub
+================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.sub

docs/source/reference/api/eland.Series.sum.rst

@@ -0,0 +1,6 @@
+eland.Series.sum
+================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.sum

docs/source/reference/api/eland.Series.tail.rst

@@ -0,0 +1,6 @@
+eland.Series.tail
+=================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.tail

docs/source/reference/api/eland.Series.to_string.rst

@@ -0,0 +1,6 @@
+eland.Series.to_string
+======================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.to_string

docs/source/reference/api/eland.Series.truediv.rst

@@ -0,0 +1,6 @@
+eland.Series.truediv
+====================
+
+.. currentmodule:: eland
+
+.. automethod:: Series.truediv

docs/source/reference/api/eland.Series.value_counts.rst

@@ -1,5 +1,5 @@
 eland.Series.value_counts
-===========================
+=========================
 
 .. currentmodule:: eland
 

docs/source/reference/dataframe.rst

@@ -91,5 +91,3 @@ Elasticsearch utilities
    :toctree: api/
 
    DataFrame.info_es
-
-

docs/source/reference/series.rst

@@ -5,9 +5,77 @@ Series
 =========
 .. currentmodule:: eland
 
+Constructor
+~~~~~~~~~~~
+.. autosummary::
+   :toctree: api/
+
+   Series
+
+Attributes and underlying data
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+**Axes**
+
+.. autosummary::
+   :toctree: api/
+
+   Series.index
+   Series.shape
+   Series.name   
+   Series.empty   
+
+Indexing, iteration
+~~~~~~~~~~~~~~~~~~~
+.. autosummary::
+   :toctree: api/
+
+   Series.head
+   Series.tail
+
+Binary operator functions
+~~~~~~~~~~~~~~~~~~~~~~~~~
+.. autosummary::
+   :toctree: api/
+
+   Series.add
+   Series.sub
+   Series.mul
+   Series.div
+   Series.truediv
+   Series.floordiv
+   Series.mod
+   Series.pow
+
 Computations / descriptive stats
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
 
+   Series.describe
+   Series.max
+   Series.mean
+   Series.min
+   Series.sum
+   Series.nunique
    Series.value_counts
+
+Reindexing / selection / label manipulation
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+.. autosummary::
+   :toctree: api/
+
+   Series.rename
+
+Serialization / IO / conversion
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+.. autosummary::
+   :toctree: api/
+
+   Series.to_string
+
+Elasticsearch utilities
+~~~~~~~~~~~~~~~~~~~~~~~
+.. autosummary::
+   :toctree: api/
+
+   Series.info_es

eland/__init__.py

@@ -1,5 +1,6 @@
 from __future__ import absolute_import
 
+from eland.common import *
 from eland.client import *
 from eland.filter import *
 from eland.index import *

eland/common.py

@@ -0,0 +1,8 @@
+# Default number of rows displayed (different to pandas where ALL could be displayed)
+DEFAULT_NUM_ROWS_DISPLAYED = 60
+
+def docstring_parameter(*sub):
+    def dec(obj):
+        obj.__doc__ = obj.__doc__.format(*sub)
+        return obj
+    return dec

eland/dataframe.py

@@ -18,15 +18,7 @@ import eland.plotting as gfx
 from eland import NDFrame
 from eland import Series
 from eland.filter import BooleanFilter, ScriptFilter
-
+from eland.common import DEFAULT_NUM_ROWS_DISPLAYED, docstring_parameter
-# Default number of rows displayed (different to pandas where ALL could be displayed)
-DEFAULT_NUM_ROWS_DISPLAYED = 60
-
-def docstring_parameter(*sub):
-    def dec(obj):
-        obj.__doc__ = obj.__doc__.format(*sub)
-        return obj
-    return dec
 
 
 class DataFrame(NDFrame):
@@ -43,7 +35,7 @@ class DataFrame(NDFrame):
         - elasticsearch-py instance or
         - eland.Client instance
     index_pattern: str
-        Elasticsearch index pattern (e.g. 'flights' or 'filebeat-*')
+        Elasticsearch index pattern (e.g. 'flights' or 'filebeat-\*')
     columns: list of str, optional
         List of DataFrame columns. A subset of the Elasticsearch index's fields.
     index_field: str, optional
@@ -98,7 +90,6 @@ class DataFrame(NDFrame):
     <BLANKLINE>
     [5 rows x 2 columns]
     """
-
     def __init__(self,
                  client=None,
                  index_pattern=None,
@@ -586,7 +577,7 @@ class DataFrame(NDFrame):
             max_rows = 1
 
         # Create a slightly bigger dataframe than display
-        df = self._build_repr_df(max_rows + 1, max_cols)
+        df = self._build_repr(max_rows + 1)
 
         if buf is not None:
             _buf = _expand_user(_stringify_path(buf))
@@ -651,7 +642,7 @@ class DataFrame(NDFrame):
             max_rows = 1
 
         # Create a slightly bigger dataframe than display
-        df = self._build_repr_df(max_rows + 1, max_cols)
+        df = self._build_repr(max_rows + 1)
 
         if buf is not None:
             _buf = _expand_user(_stringify_path(buf))
@@ -1064,3 +1055,48 @@ class DataFrame(NDFrame):
             return self._getitem(key)
         else:
             return default
+
+    @property
+    def values(self):
+        """
+        Not implemented.
+
+        In pandas this returns a Numpy representation of the DataFrame. This would involve scan/scrolling the
+        entire index.
+
+        If this is required, call ``ed.eland_to_pandas(ed_df).values``, _but beware this will scan/scroll the entire
+        Elasticsearch index(s) into memory_
+
+        See Also
+        --------
+        :pandas_api_docs:`pandas.DataFrame.values`
+
+        Examples
+        --------
+        >>> ed_df = ed.DataFrame('localhost', 'flights', columns=['AvgTicketPrice', 'Carrier']).head(5)
+        >>> pd_df = ed.eland_to_pandas(ed_df)
+        >>> print("type(ed_df)={0}\\ntype(pd_df)={1}".format(type(ed_df), type(pd_df)))
+        type(ed_df)=<class 'eland.dataframe.DataFrame'>
+        type(pd_df)=<class 'pandas.core.frame.DataFrame'>
+        >>> ed_df
+           AvgTicketPrice           Carrier
+        0      841.265642   Kibana Airlines
+        1      882.982662  Logstash Airways
+        2      190.636904  Logstash Airways
+        3      181.694216   Kibana Airlines
+        4      730.041778   Kibana Airlines
+        <BLANKLINE>
+        [5 rows x 2 columns]
+        >>> pd_df.values
+        array([[841.2656419677076, 'Kibana Airlines'],
+               [882.9826615595518, 'Logstash Airways'],
+               [190.6369038508356, 'Logstash Airways'],
+               [181.69421554118, 'Kibana Airlines'],
+               [730.041778346198, 'Kibana Airlines']], dtype=object)
+        """
+        raise NotImplementedError(
+            "This method would scan/scroll the entire Elasticsearch index(s) into memory."
+            "If this is explicitly required and there is sufficient memory, call `ed.eland_to_pandas(ed_df).values`"
+        )
+
+    to_numpy = values

eland/ndframe.py

@@ -31,7 +31,6 @@ from pandas.util._validators import validate_bool_kwarg
 
 from eland import ElandQueryCompiler
 
-
 class NDFrame:
 
     def __init__(self,
@@ -65,6 +64,7 @@ class NDFrame:
         See Also
         --------
         :pandas_api_docs:`pandas.DataFrame.index`
+        :pandas_api_docs:`pandas.Series.index`
 
         Examples
         --------
@@ -72,6 +72,10 @@ class NDFrame:
         >>> assert isinstance(df.index, ed.Index)
         >>> df.index.index_field
         '_id'
+        >>> s = df['Carrier']
+        >>> assert isinstance(s.index, ed.Index)
+        >>> s.index.index_field
+        '_id'
         """
         return self._query_compiler.index
 
@@ -104,9 +108,8 @@ class NDFrame:
         """
         return self._query_compiler.dtypes
 
-    def _build_repr_df(self, num_rows, num_cols):
+    def _build_repr(self, num_rows):
-        # Overriden version of BasePandasDataset._build_repr_df
+        # self could be Series or DataFrame
-        # to avoid issues with concat
         if len(self.index) <= num_rows:
             return self._to_pandas()
 

eland/operations.py

@@ -588,6 +588,7 @@ class Operations:
             df = self._apply_df_post_processing(df, post_processing)
             collector.collect(df)
 
+
     def iloc(self, index, field_names):
         # index and field_names are indexers
         task = ('iloc', (index, field_names))
@@ -881,9 +882,10 @@ class Operations:
         left_field = item[1][1][1][0]
         right_field = item[1][1][1][1]
 
+        # https://www.elastic.co/guide/en/elasticsearch/painless/current/painless-api-reference-shared-java-lang.html#painless-api-reference-shared-Math
         if isinstance(right_field, str):
             """
-            (if op_name = 'truediv')
+            (if op_name = '__truediv__')
             
             "script_fields": {
                 "field_name": {
@@ -893,12 +895,23 @@ class Operations:
                 }
             }
             """
-            if op_name == 'truediv':
+            if op_name == '__add__':
-                op = '/'
+                source = "doc['{0}'].value + doc['{1}'].value".format(left_field, right_field)
+            elif op_name == '__truediv__':
+                source = "doc['{0}'].value / doc['{1}'].value".format(left_field, right_field)
+            elif op_name == '__floordiv__':
+                source = "Math.floor(doc['{0}'].value / doc['{1}'].value)".format(left_field, right_field)
+            elif op_name == '__pow__':
+                source = "Math.pow(doc['{0}'].value, doc['{1}'].value)".format(left_field, right_field)
+            elif op_name == '__mod__':
+                source = "doc['{0}'].value % doc['{1}'].value".format(left_field, right_field)
+            elif op_name == '__mul__':
+                source = "doc['{0}'].value * doc['{1}'].value".format(left_field, right_field)
+            elif op_name == '__sub__':
+                source = "doc['{0}'].value - doc['{1}'].value".format(left_field, right_field)
             else:
                 raise NotImplementedError("Not implemented operation '{0}'".format(op_name))
 
-            source = "doc['{0}'].value {1} doc['{2}'].value".format(left_field, op, right_field)
 
             if query_params['query_script_fields'] is None:
                 query_params['query_script_fields'] = {}
@@ -909,7 +922,7 @@ class Operations:
             }
         else:
             """
-            (if op_name = 'truediv')
+            (if op_name = '__truediv__')
 
             "script_fields": {
                 "field_name": {
@@ -919,12 +932,23 @@ class Operations:
                 }
             }
             """
-            if op_name == 'truediv':
+            if op_name == '__add__':
-                op = '/'
+                source = "doc['{0}'].value + {1}".format(left_field, right_field)
+            elif op_name == '__truediv__':
+                source = "doc['{0}'].value / {1}".format(left_field, right_field)
+            elif op_name == '__floordiv__':
+                source = "Math.floor(doc['{0}'].value / {1})".format(left_field, right_field)
+            elif op_name == '__pow__':
+                source = "Math.pow(doc['{0}'].value, {1})".format(left_field, right_field)
+            elif op_name == '__mod__':
+                source = "doc['{0}'].value % {1}".format(left_field, right_field)
+            elif op_name == '__mul__':
+                source = "doc['{0}'].value * {1}".format(left_field, right_field)
+            elif op_name == '__sub__':
+                source = "doc['{0}'].value - {1}".format(left_field, right_field)
             else:
                 raise NotImplementedError("Not implemented operation '{0}'".format(op_name))
 
-            source = "doc['{0}'].value {1} {2}".format(left_field, op, right_field)
 
             if query_params['query_script_fields'] is None:
                 query_params['query_script_fields'] = {}

eland/query_compiler.py

@@ -239,9 +239,9 @@ class ElandQueryCompiler:
         # Create pandas DataFrame
         df = pd.DataFrame(data=rows, index=index)
 
-        # _source may not contain all columns in the mapping
+        # _source may not contain all field_names in the mapping
-        # therefore, fill in missing columns
+        # therefore, fill in missing field_names
-        # (note this returns self.columns NOT IN df.columns)
+        # (note this returns self.field_names NOT IN df.columns)
         missing_field_names = list(set(self.field_names) - set(df.columns))
 
         for missing in missing_field_names:

eland/series.py

@@ -11,19 +11,26 @@ without storing the dataset in local memory.
 
 Implementation Details
 ----------------------
-Based on NDFrame which underpins eland.1DataFrame
+Based on NDFrame which underpins eland.DataFrame
 
 """
 
+import sys
+import warnings
 from io import StringIO
 
 import pandas as pd
-import numpy as np
+from pandas.io.common import _expand_user, _stringify_path
 
 from eland import NDFrame
+from eland.common import DEFAULT_NUM_ROWS_DISPLAYED
 from eland.filter import NotFilter, Equal, Greater, Less, GreaterEqual, LessEqual, ScriptFilter, IsIn
 
 
+def _get_method_name():
+    return sys._getframe(1).f_code.co_name
+
+
 class Series(NDFrame):
     """
     pandas.Series like API that proxies into Elasticsearch index(es).
@@ -34,35 +41,35 @@ class Series(NDFrame):
         A reference to a Elasticsearch python client
 
     index_pattern : str
-        An Elasticsearch index pattern. This can contain wildcards (e.g. filebeat-*).
+        An Elasticsearch index pattern. This can contain wildcards (e.g. filebeat-\*\).
 
     index_field : str
         The field to base the series on
 
-    See Also
-    --------
-
-    Examples
-    --------
-
-    import eland as ed
-    client = ed.Client(Elasticsearch())
-    s = ed.DataFrame(client, 'reviews', 'date')
-    df.head()
-       reviewerId  vendorId  rating              date
-    0           0         0       5  2006-04-07 17:08
-    1           1         1       5  2006-05-04 12:16
-    2           2         2       4  2006-04-21 12:26
-    3           3         3       5  2006-04-18 15:48
-    4           3         4       5  2006-04-18 15:49
-
-    Notice that the types are based on Elasticsearch mappings
-
     Notes
     -----
     If the Elasticsearch index is deleted or index mappings are changed after this
     object is created, the object is not rebuilt and so inconsistencies can occur.
 
+    See Also
+    --------
+    :pandas_api_docs:`pandas.Series`
+
+    Examples
+    --------
+    >>> ed.Series(client='localhost', index_pattern='flights', name='Carrier')
+    0         Kibana Airlines
+    1        Logstash Airways
+    2        Logstash Airways
+    3         Kibana Airlines
+    4         Kibana Airlines
+                   ...
+    13054    Logstash Airways
+    13055    Logstash Airways
+    13056    Logstash Airways
+    13057            JetBeats
+    13058            JetBeats
+    Name: Carrier, Length: 13059, dtype: object
     """
 
     def __init__(self,
@@ -94,6 +101,34 @@ class Series(NDFrame):
         """
         return len(self.index) == 0
 
+    @property
+    def shape(self):
+        """
+        Return a tuple representing the dimensionality of the Series.
+
+        Returns
+        -------
+        shape: tuple
+
+        0. number of rows
+        1. number of columns
+
+        Notes
+        -----
+        - number of rows ``len(series)`` queries Elasticsearch
+        - number of columns == 1
+
+        Examples
+        --------
+        >>> df = ed.Series('localhost', 'ecommerce', name='total_quantity')
+        >>> df.shape
+        (4675, 1)
+        """
+        num_rows = len(self)
+        num_columns = 1
+
+        return num_rows, num_columns
+
     def _get_name(self):
         return self._query_compiler.columns[0]
 
@@ -118,7 +153,7 @@ class Series(NDFrame):
 
         See Also
         --------
-        :pandas_api_docs:pandas.Series.rename
+        :pandas_api_docs:`pandas.Series.rename`
 
         Examples
         --------
@@ -200,12 +235,39 @@ class Series(NDFrame):
 
         return self._query_compiler.value_counts(es_size)
 
+    # dtype not implemented for Series as causes query to fail
+    # in pandas.core.computation.ops.Term.type
+
     # ----------------------------------------------------------------------
     # Rendering Methods
     def __repr__(self):
-        num_rows = pd.get_option("max_rows") or 60
+        """
+        Return a string representation for a particular Series.
+        """
+        buf = StringIO()
 
-        return self.to_string(max_rows=num_rows)
+        # max_rows and max_cols determine the maximum size of the pretty printed tabular
+        # representation of the series. pandas defaults are 60 and 20 respectively.
+        # series where len(series) > max_rows shows a truncated view with 10 rows shown.
+        max_rows = pd.get_option("display.max_rows")
+        min_rows = pd.get_option("display.min_rows")
+
+        if len(self) > max_rows:
+            max_rows = min_rows
+
+        show_dimensions = pd.get_option("display.show_dimensions")
+
+        self.to_string(
+            buf=buf,
+            name=self.name,
+            dtype=True,
+            min_rows=min_rows,
+            max_rows=max_rows,
+            length=show_dimensions,
+        )
+        result = buf.getvalue()
+
+        return result
 
     def to_string(
             self,
@@ -217,33 +279,69 @@ class Series(NDFrame):
             length=False,
             dtype=False,
             name=False,
-            max_rows=None):
+            max_rows=None,
-
+            min_rows=None,
+    ):
+        # In pandas calling 'to_string' without max_rows set, will dump ALL rows - we avoid this
+        # by limiting rows by default.
+        num_rows = len(self)  # avoid multiple calls
+        if num_rows <= DEFAULT_NUM_ROWS_DISPLAYED:
             if max_rows is None:
+                max_rows = num_rows
+            else:
+                max_rows = min(num_rows, max_rows)
+        elif max_rows is None:
             warnings.warn("Series.to_string called without max_rows set "
                           "- this will return entire index results. "
-                          "Setting max_rows=60, overwrite if different behaviour is required.")
+                          "Setting max_rows={default}"
-            max_rows = 60
+                          " overwrite if different behaviour is required."
+                          .format(default=DEFAULT_NUM_ROWS_DISPLAYED),
+                          UserWarning)
+            max_rows = DEFAULT_NUM_ROWS_DISPLAYED
+
+        # because of the way pandas handles max_rows=0, not having this throws an error
+        # see eland issue #56
+        if max_rows == 0:
+            max_rows = 1
 
         # Create a slightly bigger dataframe than display
-        temp_df = self._build_repr_df(max_rows + 1, None)
+        temp_series = self._build_repr(max_rows + 1)
-        if isinstance(temp_df, pd.DataFrame):
+
-            temp_df = temp_df[self.name]
+        if buf is not None:
-        temp_str = repr(temp_df)
+            _buf = _expand_user(_stringify_path(buf))
-        if self.name is not None:
-            name_str = "Name: {}, ".format(str(self.name))
         else:
-            name_str = ""
+            _buf = StringIO()
-        if len(self.index) > max_rows:
+
-            len_str = "Length: {}, ".format(len(self.index))
+        # Create repr of fake series without name, length, dtype summary
-        else:
+        temp_str = temp_series.to_string(buf=_buf,
-            len_str = ""
+                                         na_rep=na_rep,
-        dtype_str = "dtype: {}".format(temp_str.rsplit("dtype: ", 1)[-1])
+                                         float_format=float_format,
-        if len(self) == 0:
+                                         header=header,
-            return "Series([], {}{}".format(name_str, dtype_str)
+                                         index=index,
-        return temp_str.rsplit("\nName:", 1)[0] + "\n{}{}{}".format(
+                                         length=False,
-            name_str, len_str, dtype_str
+                                         dtype=False,
-        )
+                                         name=False,
+                                         max_rows=max_rows)
+
+        # Create the summary
+        footer = ""
+        if name and self.name is not None:
+            footer += "Name: {}".format(str(self.name))
+        if length and len(self) > max_rows:
+            if footer:
+                footer += ", "
+            footer += "Length: {}".format(len(self.index))
+        if dtype:
+            if footer:
+                footer += ", "
+            footer += "dtype: {}".format(temp_series.dtype)
+
+        if len(footer) > 0:
+            _buf.write("\n{}".format(footer))
+
+        if buf is None:
+            result = _buf.getvalue()
+            return result
 
     def _to_pandas(self):
         return self._query_compiler.to_pandas()[self.name]
@@ -321,13 +419,16 @@ class Series(NDFrame):
     @property
     def ndim(self):
         """
-        Returns 1 by definition of a Series1
+        Returns 1 by definition of a Series
 
         Returns
         -------
         int
             By definition 1
 
+        See Also
+        --------
+        :pandas_api_docs:`pandas.Series.ndim`
         """
         return 1
 
@@ -338,34 +439,317 @@ class Series(NDFrame):
 
         return buf.getvalue()
 
-    def __truediv__(self, right):
+    def __add__(self, right):
-        return self.truediv(right)
-
-    def truediv(self, right):
         """
-        return a / b
+        Return addition of series and right, element-wise (binary operator add).
+
+        Parameters
+        ----------
+        right: eland.Series
+
+        Returns
+        -------
+        eland.Series
+
+        Examples
+        --------
+        >>> df = ed.DataFrame('localhost', 'ecommerce').head(5)
+        >>> df.taxful_total_price
+        0     36.98
+        1     53.98
+        2    199.98
+        3    174.98
+        4     80.98
+        Name: taxful_total_price, dtype: float64
+        >>> df.total_quantity
+        0    2
+        1    2
+        2    2
+        3    2
+        4    2
+        Name: total_quantity, dtype: int64
+        >>> df.taxful_total_price + df.total_quantity
+        0     38.980000
+        1     55.980000
+        2    201.979996
+        3    176.979996
+        4     82.980003
+        dtype: float64
+        """
+        return self._numeric_op(right, _get_method_name())
+
+    def __truediv__(self, right):
+        """
+        Return floating division of series and right, element-wise (binary operator truediv).
+
+        Parameters
+        ----------
+        right: eland.Series
+
+        Returns
+        -------
+        eland.Series
+
+        Examples
+        --------
+        >>> df = ed.DataFrame('localhost', 'ecommerce').head(5)
+        >>> df.taxful_total_price
+        0     36.98
+        1     53.98
+        2    199.98
+        3    174.98
+        4     80.98
+        Name: taxful_total_price, dtype: float64
+        >>> df.total_quantity
+        0    2
+        1    2
+        2    2
+        3    2
+        4    2
+        Name: total_quantity, dtype: int64
+        >>> df.taxful_total_price / df.total_quantity
+        0    18.490000
+        1    26.990000
+        2    99.989998
+        3    87.489998
+        4    40.490002
+        dtype: float64
+        """
+        return self._numeric_op(right, _get_method_name())
+
+    def __floordiv__(self, right):
+        """
+        Return integer division of series and right, element-wise (binary operator floordiv //).
+
+        Parameters
+        ----------
+        right: eland.Series
+
+        Returns
+        -------
+        eland.Series
+
+        Examples
+        --------
+        >>> df = ed.DataFrame('localhost', 'ecommerce').head(5)
+        >>> df.taxful_total_price
+        0     36.98
+        1     53.98
+        2    199.98
+        3    174.98
+        4     80.98
+        Name: taxful_total_price, dtype: float64
+        >>> df.total_quantity
+        0    2
+        1    2
+        2    2
+        3    2
+        4    2
+        Name: total_quantity, dtype: int64
+        >>> df.taxful_total_price // df.total_quantity
+        0    18.0
+        1    26.0
+        2    99.0
+        3    87.0
+        4    40.0
+        dtype: float64
+        """
+        return self._numeric_op(right, _get_method_name())
+
+    def __mod__(self, right):
+        """
+        Return modulo of series and right, element-wise (binary operator mod %).
+
+        Parameters
+        ----------
+        right: eland.Series
+
+        Returns
+        -------
+        eland.Series
+
+        Examples
+        --------
+        >>> df = ed.DataFrame('localhost', 'ecommerce').head(5)
+        >>> df.taxful_total_price
+        0     36.98
+        1     53.98
+        2    199.98
+        3    174.98
+        4     80.98
+        Name: taxful_total_price, dtype: float64
+        >>> df.total_quantity
+        0    2
+        1    2
+        2    2
+        3    2
+        4    2
+        Name: total_quantity, dtype: int64
+        >>> df.taxful_total_price % df.total_quantity
+        0    0.980000
+        1    1.980000
+        2    1.979996
+        3    0.979996
+        4    0.980003
+        dtype: float64
+        """
+        return self._numeric_op(right, _get_method_name())
+
+    def __mul__(self, right):
+        """
+        Return multiplication of series and right, element-wise (binary operator mul).
+
+        Parameters
+        ----------
+        right: eland.Series
+
+        Returns
+        -------
+        eland.Series
+
+        Examples
+        --------
+        >>> df = ed.DataFrame('localhost', 'ecommerce').head(5)
+        >>> df.taxful_total_price
+        0     36.98
+        1     53.98
+        2    199.98
+        3    174.98
+        4     80.98
+        Name: taxful_total_price, dtype: float64
+        >>> df.total_quantity
+        0    2
+        1    2
+        2    2
+        3    2
+        4    2
+        Name: total_quantity, dtype: int64
+        >>> df.taxful_total_price * df.total_quantity
+        0     73.959999
+        1    107.959999
+        2    399.959991
+        3    349.959991
+        4    161.960007
+        dtype: float64
+        """
+        return self._numeric_op(right, _get_method_name())
+
+    def __sub__(self, right):
+        """
+        Return subtraction of series and right, element-wise (binary operator sub).
+
+        Parameters
+        ----------
+        right: eland.Series
+
+        Returns
+        -------
+        eland.Series
+
+        Examples
+        --------
+        >>> df = ed.DataFrame('localhost', 'ecommerce').head(5)
+        >>> df.taxful_total_price
+        0     36.98
+        1     53.98
+        2    199.98
+        3    174.98
+        4     80.98
+        Name: taxful_total_price, dtype: float64
+        >>> df.total_quantity
+        0    2
+        1    2
+        2    2
+        3    2
+        4    2
+        Name: total_quantity, dtype: int64
+        >>> df.taxful_total_price - df.total_quantity
+        0     34.980000
+        1     51.980000
+        2    197.979996
+        3    172.979996
+        4     78.980003
+        dtype: float64
+        """
+        return self._numeric_op(right, _get_method_name())
+
+    def __pow__(self, right):
+        """
+        Return exponential power of series and right, element-wise (binary operator pow \**\).
+
+        Parameters
+        ----------
+        right: eland.Series
+
+        Returns
+        -------
+        eland.Series
+
+        Examples
+        --------
+        >>> df = ed.DataFrame('localhost', 'ecommerce').head(5)
+        >>> df.taxful_total_price
+        0     36.98
+        1     53.98
+        2    199.98
+        3    174.98
+        4     80.98
+        Name: taxful_total_price, dtype: float64
+        >>> df.total_quantity
+        0    2
+        1    2
+        2    2
+        3    2
+        4    2
+        Name: total_quantity, dtype: int64
+        >>> df.taxful_total_price ** df.total_quantity
+        0     1367.520366
+        1     2913.840351
+        2    39991.998691
+        3    30617.998905
+        4     6557.760944
+        dtype: float64
+        """
+        return self._numeric_op(right, _get_method_name())
+
+    add = __add__
+    div = __truediv__
+    divide = __truediv__
+    floordiv = __floordiv__
+    mod = __mod__
+    mul = __mul__
+    multiply = __mul__
+    pow = __pow__
+    sub = __sub__
+    subtract = __sub__
+    truediv = __truediv__
+
+    def _numeric_op(self, right, method_name):
+        """
+        return a op b
 
         a & b == Series
             a & b must share same eland.Client, index_pattern and index_field
+        a == Series, b == numeric
         """
         if isinstance(right, Series):
             # Check compatibility
             self._query_compiler.check_arithmetics(right._query_compiler)
 
-            new_field_name = "{0}_{1}_{2}".format(self.name, "truediv", right.name)
+            new_field_name = "{0}_{1}_{2}".format(self.name, method_name, right.name)
 
             # Compatible, so create new Series
             series = Series(query_compiler=self._query_compiler.arithmetic_op_fields(
-                new_field_name, 'truediv', self.name, right.name))
+                new_field_name, method_name, self.name, right.name))
             series.name = None
 
             return series
         elif isinstance(right, (int, float)):  # TODO extend to numpy types
-            new_field_name = "{0}_{1}_{2}".format(self.name, "truediv", str(right).replace('.','_'))
+            new_field_name = "{0}_{1}_{2}".format(self.name, method_name, str(right).replace('.', '_'))
 
             # Compatible, so create new Series
             series = Series(query_compiler=self._query_compiler.arithmetic_op_fields(
-                new_field_name, 'truediv', self.name, float(right))) # force rhs to float
+                new_field_name, method_name, self.name, float(right)))  # force rhs to float
 
             # name of Series remains original name
             series.name = self.name
@@ -374,5 +758,123 @@ class Series(NDFrame):
         else:
             raise TypeError(
                 "Can only perform arithmetic operation on selected types "
-                "{0} != {1}".format(type(self), type(right))
+                "{0} != {1} for {2}".format(type(self), type(right), method_name)
             )
+
+    def max(self):
+        """
+        Return the maximum of the Series values
+
+        TODO - implement remainder of pandas arguments, currently non-numerics are not supported
+
+        Returns
+        -------
+        float
+            max value
+
+        See Also
+        --------
+        :pandas_api_docs:`pandas.Series.max`
+
+        Examples
+        --------
+        >>> s = ed.Series('localhost', 'flights', name='AvgTicketPrice')
+        >>> int(s.max())
+        1199
+        """
+        results = super().max()
+        return results.squeeze()
+
+    def mean(self):
+        """
+        Return the mean of the Series values
+
+        TODO - implement remainder of pandas arguments, currently non-numerics are not supported
+
+        Returns
+        -------
+        float
+            max value
+
+        See Also
+        --------
+        :pandas_api_docs:`pandas.Series.mean`
+
+        Examples
+        --------
+        >>> s = ed.Series('localhost', 'flights', name='AvgTicketPrice')
+        >>> int(s.mean())
+        628
+        """
+        results = super().mean()
+        return results.squeeze()
+
+    def min(self):
+        """
+        Return the minimum of the Series values
+
+        TODO - implement remainder of pandas arguments, currently non-numerics are not supported
+
+        Returns
+        -------
+        float
+            max value
+
+        See Also
+        --------
+        :pandas_api_docs:`pandas.Series.min`
+
+        Examples
+        --------
+        >>> s = ed.Series('localhost', 'flights', name='AvgTicketPrice')
+        >>> int(s.min())
+        100
+        """
+        results = super().min()
+        return results.squeeze()
+
+    def sum(self):
+        """
+        Return the sum of the Series values
+
+        TODO - implement remainder of pandas arguments, currently non-numerics are not supported
+
+        Returns
+        -------
+        float
+            max value
+
+        See Also
+        --------
+        :pandas_api_docs:`pandas.Series.sum`
+
+        Examples
+        --------
+        >>> s = ed.Series('localhost', 'flights', name='AvgTicketPrice')
+        >>> int(s.sum())
+        8204364
+        """
+        results = super().sum()
+        return results.squeeze()
+
+    def nunique(self):
+        """
+        Return the sum of the Series values
+
+        Returns
+        -------
+        float
+            max value
+
+        See Also
+        --------
+        :pandas_api_docs:`pandas.Series.sum`
+
+        Examples
+        --------
+        >>> s = ed.Series('localhost', 'flights', name='Carrier')
+        >>> s.nunique()
+        4
+        """
+        results = super().nunique()
+        return results.squeeze()

eland/tests/__init__.py

@@ -279,10 +279,10 @@ ECOMMERCE_MAPPING = {"mappings": {
             "type": "keyword"
         },
         "taxful_total_price": {
-            "type": "half_float"
+            "type": "float"
         },
         "taxless_total_price": {
-            "type": "half_float"
+            "type": "float"
         },
         "total_quantity": {
             "type": "integer"

eland/tests/series/test_arithmetics_pytest.py

@@ -4,6 +4,8 @@ from eland.tests.common import TestData, assert_pandas_eland_series_equal
 from pandas.util.testing import assert_series_equal
 import pytest
 
+import numpy as np
+
 
 class TestSeriesArithmetics(TestData):
 
@@ -15,29 +17,35 @@ class TestSeriesArithmetics(TestData):
         with pytest.raises(TypeError):
             ed_df['total_quantity'] / pd_df['taxful_total_price']
 
-    def test_ecommerce_series_div(self):
+    def test_ecommerce_series_basic_arithmetics(self):
-        pd_df = self.pd_ecommerce()
+        pd_df = self.pd_ecommerce().head(100)
-        ed_df = self.ed_ecommerce()
+        ed_df = self.ed_ecommerce().head(100)
 
-        pd_avg_price = pd_df['total_quantity'] / pd_df['taxful_total_price']
+        ops = ['__add__',
-        ed_avg_price = ed_df['total_quantity'] / ed_df['taxful_total_price']
+               '__truediv__',
+               '__floordiv__',
+               '__pow__',
+               '__mod__',
+               '__mul__',
+               '__sub__',
+               'add',
+               'truediv',
+               'floordiv',
+               'pow',
+               'mod',
+               'mul',
+               'sub']
 
-        assert_pandas_eland_series_equal(pd_avg_price, ed_avg_price, check_less_precise=True)
+        for op in ops:
+            pd_series = getattr(pd_df['taxful_total_price'], op)(pd_df['total_quantity'])
+            ed_series = getattr(ed_df['taxful_total_price'], op)(ed_df['total_quantity'])
+            assert_pandas_eland_series_equal(pd_series, ed_series, check_less_precise=True)
 
-    def test_ecommerce_series_div_float(self):
+            pd_series = getattr(pd_df['taxful_total_price'], op)(10.56)
-        pd_df = self.pd_ecommerce()
+            ed_series = getattr(ed_df['taxful_total_price'], op)(10.56)
-        ed_df = self.ed_ecommerce()
+            assert_pandas_eland_series_equal(pd_series, ed_series, check_less_precise=True)
 
-        pd_avg_price = pd_df['total_quantity'] / 10.0
+            pd_series = getattr(pd_df['taxful_total_price'], op)(int(8))
-        ed_avg_price = ed_df['total_quantity'] / 10.0
+            ed_series = getattr(ed_df['taxful_total_price'], op)(int(8))
+            assert_pandas_eland_series_equal(pd_series, ed_series, check_less_precise=True)
 
-        assert_pandas_eland_series_equal(pd_avg_price, ed_avg_price, check_less_precise=True)
-
-    def test_ecommerce_series_div_int(self):
-        pd_df = self.pd_ecommerce()
-        ed_df = self.ed_ecommerce()
-
-        pd_avg_price = pd_df['total_quantity'] / int(10)
-        ed_avg_price = ed_df['total_quantity'] / int(10)
-
-        assert_pandas_eland_series_equal(pd_avg_price, ed_avg_price, check_less_precise=True)

eland/tests/series/test_info_es_pytest.py

@@ -0,0 +1,17 @@
+# File called _pytest for PyCharm compatability
+
+from pandas.util.testing import assert_almost_equal
+
+from eland.tests.common import TestData
+
+import eland as ed
+
+
+class TestSeriesInfoEs(TestData):
+
+    def test_flights_info_es(self):
+        ed_flights = self.ed_flights()['AvgTicketPrice']
+
+        # No assertion, just test it can be called
+        info_es = ed_flights.info_es()
+

eland/tests/series/test_metrics_pytest.py

@@ -0,0 +1,44 @@
+# File called _pytest for PyCharm compatability
+
+from pandas.util.testing import assert_almost_equal
+
+from eland.tests.common import TestData
+
+import eland as ed
+
+
+class TestSeriesMetrics(TestData):
+
+    funcs = ['max', 'min', 'mean', 'sum']
+
+    def test_flights_metrics(self):
+        pd_flights = self.pd_flights()['AvgTicketPrice']
+        ed_flights = self.ed_flights()['AvgTicketPrice']
+
+        for func in self.funcs:
+            pd_metric = getattr(pd_flights, func)()
+            ed_metric = getattr(ed_flights, func)()
+            assert_almost_equal(pd_metric, ed_metric, check_less_precise=True)
+
+    def test_ecommerce_selected_non_numeric_source_fields(self):
+        # None of these are numeric
+        column = 'category'
+
+        ed_ecommerce = self.ed_ecommerce()[column]
+
+        for func in self.funcs:
+            ed_metric = getattr(ed_ecommerce, func)()
+            assert ed_metric.empty
+
+
+    def test_ecommerce_selected_all_numeric_source_fields(self):
+        # All of these are numeric
+        columns = ['total_quantity', 'taxful_total_price', 'taxless_total_price']
+
+        for column in columns:
+            pd_ecommerce = self.pd_ecommerce()[column]
+            ed_ecommerce = self.ed_ecommerce()[column]
+
+            for func in self.funcs:
+                assert_almost_equal(getattr(pd_ecommerce, func)(), getattr(ed_ecommerce, func)(),
+                                    check_less_precise=True)

eland/tests/series/test_repr_pytest.py

@@ -1,13 +1,14 @@
 # File called _pytest for PyCharm compatability
 import eland as ed
+import pandas as pd
 from eland.tests import ELASTICSEARCH_HOST
-from eland.tests import FLIGHTS_INDEX_NAME
+from eland.tests import FLIGHTS_INDEX_NAME, ECOMMERCE_INDEX_NAME
 from eland.tests.common import TestData
 
 
 class TestSeriesRepr(TestData):
 
-    def test_repr(self):
+    def test_repr_flights_carrier(self):
         pd_s = self.pd_flights()['Carrier']
         ed_s = ed.Series(ELASTICSEARCH_HOST, FLIGHTS_INDEX_NAME, 'Carrier')
 
@@ -15,3 +16,12 @@ class TestSeriesRepr(TestData):
         ed_repr = repr(ed_s)
 
         assert pd_repr == ed_repr
+
+    def test_repr_flights_carrier_5(self):
+        pd_s = self.pd_flights()['Carrier'].head(5)
+        ed_s = ed.Series(ELASTICSEARCH_HOST, FLIGHTS_INDEX_NAME, 'Carrier').head(5)
+
+        pd_repr = repr(pd_s)
+        ed_repr = repr(ed_s)
+
+        assert pd_repr == ed_repr