Add es_dtypes property to DataFrame and Series

docs/source/reference/api/eland.DataFrame.es_dtypes.rst

@@ -0,0 +1,6 @@
+eland.DataFrame.es_dtypes
+=========================
+
+.. currentmodule:: eland
+
+.. autoattribute:: DataFrame.es_dtypes

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

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

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

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

docs/source/reference/api/eland.ml.MLModel.rst

@@ -0,0 +1,15 @@
+eland.ml.MLModel
+================
+
+.. currentmodule:: eland.ml
+
+.. autoclass:: MLModel
+
+
+..
+   HACK -- the point here is that we don't want this to appear in the output, but the autosummary should still generate the pages.
+   .. autosummary::
+      :toctree:
+
+      DataFrame.abs
+      DataFrame.add

docs/source/reference/dataframe.rst

@@ -12,7 +12,7 @@ Constructor
 
    DataFrame
 
-Attributes and underlying data
+Attributes and Underlying Data
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -27,7 +27,7 @@ Attributes and underlying data
    DataFrame.ndim
    DataFrame.size
 
-Indexing, iteration
+Indexing, Iteration
 ~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -39,7 +39,7 @@ Indexing, iteration
    DataFrame.query
    DataFrame.sample
 
-Function application, GroupBy & window
+Function Application, GroupBy & Window
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -49,7 +49,7 @@ Function application, GroupBy & window
 
 .. _api.dataframe.stats:
 
-Computations / descriptive stats
+Computations / Descriptive Stats
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -67,7 +67,7 @@ Computations / descriptive stats
    DataFrame.sum
    DataFrame.nunique
 
-Reindexing / selection / label manipulation
+Reindexing / Selection / Label Manipulation
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -89,8 +89,9 @@ Elasticsearch Functions
 
    DataFrame.es_info
    DataFrame.es_query
+   DataFrame.es_dtypes
 
-Serialization / IO / conversion
+Serialization / IO / Conversion
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/

docs/source/reference/ml.rst

@@ -18,8 +18,8 @@ The fastest way to get started with machine learning features is to
 
 See `Elasticsearch Machine Learning documentation <https://www.elastic.co/guide/en/machine-learning/current/setup.html>`_ more details.
 
-ImportedMLModel
-~~~~~~~~~~~~~~~
+MLModel
+~~~~~~~
 .. currentmodule:: eland.ml
 
 Constructor

docs/source/reference/series.rst

@@ -1,8 +1,8 @@
 .. _api.series:
 
-=========
+======
 Series
-=========
+======
 .. currentmodule:: eland
 
 Constructor
@@ -12,7 +12,7 @@ Constructor
 
    Series
 
-Attributes and underlying data
+Attributes and Underlying Data
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -26,7 +26,7 @@ Attributes and underlying data
    Series.ndim
    Series.size
 
-Indexing, iteration
+Indexing, Iteration
 ~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -35,7 +35,7 @@ Indexing, iteration
    Series.tail
    Series.sample
 
-Binary operator functions
+Binary Operator Functions
 ~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -63,7 +63,7 @@ Binary operator functions
    Series.rmod
    Series.rpow
 
-Computations / descriptive stats
+Computations / Descriptive Stats
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -80,7 +80,7 @@ Computations / descriptive stats
    Series.nunique
    Series.value_counts
 
-Reindexing / selection / label manipulation
+Reindexing / Selection / Label Manipulation
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -100,7 +100,7 @@ Plotting
 
    Series.hist
 
-Serialization / IO / conversion
+Serialization / IO / Conversion
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autosummary::
    :toctree: api/
@@ -115,3 +115,5 @@ Elasticsearch Functions
    :toctree: api/
 
    Series.es_info
+   Series.es_dtype
+   Series.es_dtypes

eland/field_mappings.py

@@ -780,6 +780,20 @@ class FieldMappings:
         # Convert return from 'str' to 'np.dtype'
         return pd_dtypes.apply(lambda x: np.dtype(x))
 
+    def es_dtypes(self):
+        """
+        Returns
+        -------
+        dtypes: pd.Series
+            Index: Display name
+            Values: es_dtype as a string
+        """
+        es_dtypes = self._mappings_capabilities["es_dtype"]
+
+        # Set name of the returned series as None
+        es_dtypes.name = None
+        return es_dtypes
+
     def es_info(self, buf):
         buf.write("Mappings:\n")
         buf.write(f" capabilities:\n{self._mappings_capabilities.to_string()}\n")

eland/ndframe.py

@@ -132,6 +132,28 @@ class NDFrame(ABC):
         """
         return self._query_compiler.dtypes
 
+    @property
+    def es_dtypes(self):
+        """
+        Return the Elasticsearch dtypes in the index
+
+        Returns
+        -------
+        pandas.Series
+            The data type of each column.
+
+        Examples
+        --------
+        >>> df = ed.DataFrame('localhost', 'flights', columns=['Origin', 'AvgTicketPrice', 'timestamp', 'dayOfWeek'])
+        >>> df.es_dtypes
+        Origin            keyword
+        AvgTicketPrice      float
+        timestamp            date
+        dayOfWeek            byte
+        dtype: object
+        """
+        return self._query_compiler.es_dtypes
+
     def _build_repr(self, num_rows) -> pd.DataFrame:
         # self could be Series or DataFrame
         if len(self.index) <= num_rows:

eland/query_compiler.py

@@ -123,6 +123,10 @@ class QueryCompiler:
     def dtypes(self):
         return self._mappings.dtypes()
 
+    @property
+    def es_dtypes(self):
+        return self._mappings.es_dtypes()
+
     # END Index, columns, and dtypes objects
 
     def _es_results_to_pandas(self, results, batch_size=None, show_progress=False):

eland/series.py

@@ -435,6 +435,13 @@ class Series(NDFrame):
         """
         return self._query_compiler.dtypes[0]
 
+    @property
+    def es_dtype(self) -> str:
+        """
+        Return the Elasticsearch type of the underlying data.
+        """
+        return self._query_compiler.es_dtypes[0]
+
     def __gt__(self, other: Union[int, float, "Series"]) -> BooleanFilter:
         if isinstance(other, Series):
             # Need to use scripted query to compare to values

eland/tests/conftest.py

@@ -29,6 +29,7 @@ from .common import (
     _pd_ecommerce,
     _ed_flights_small,
     _pd_flights_small,
+    TestData,
 )
 import eland as ed
 
@@ -146,3 +147,8 @@ def df():
     return SymmetricAPIChecker(
         ed_obj=_ed_flights_small, pd_obj=_pd_flights_small.copy()
     )
+
+
+@pytest.fixture(scope="session")
+def testdata():
+    return TestData()

eland/tests/dataframe/test_dtypes_pytest.py

@@ -18,12 +18,12 @@
 # File called _pytest for PyCharm compatability
 
 import numpy as np
+import pandas as pd
+from eland.tests.common import assert_series_equal
 
 
 class TestDataFrameDtypes:
     def test_dtypes(self, df):
-        print(df.dtypes)
-
         for i in range(0, len(df.dtypes) - 1):
             assert isinstance(df.dtypes[i], type(df.dtypes[i]))
 
@@ -32,3 +32,40 @@ class TestDataFrameDtypes:
         df.select_dtypes(exclude=np.number)
         df.select_dtypes(include=np.float64)
         df.select_dtypes(exclude=np.float64)
+
+    def test_es_dtypes(self, testdata):
+        df = testdata.ed_flights_small()
+        assert_series_equal(
+            df.es_dtypes,
+            pd.Series(
+                {
+                    "AvgTicketPrice": "float",
+                    "Cancelled": "boolean",
+                    "Carrier": "keyword",
+                    "Dest": "keyword",
+                    "DestAirportID": "keyword",
+                    "DestCityName": "keyword",
+                    "DestCountry": "keyword",
+                    "DestLocation": "geo_point",
+                    "DestRegion": "keyword",
+                    "DestWeather": "keyword",
+                    "DistanceKilometers": "float",
+                    "DistanceMiles": "float",
+                    "FlightDelay": "boolean",
+                    "FlightDelayMin": "integer",
+                    "FlightDelayType": "keyword",
+                    "FlightNum": "keyword",
+                    "FlightTimeHour": "float",
+                    "FlightTimeMin": "float",
+                    "Origin": "keyword",
+                    "OriginAirportID": "keyword",
+                    "OriginCityName": "keyword",
+                    "OriginCountry": "keyword",
+                    "OriginLocation": "geo_point",
+                    "OriginRegion": "keyword",
+                    "OriginWeather": "keyword",
+                    "dayOfWeek": "byte",
+                    "timestamp": "date",
+                }
+            ),
+        )

eland/tests/series/test_dtype_pytest.py

@@ -16,8 +16,10 @@
 #  under the License.
 
 import numpy as np
+import pandas as pd
 import warnings
 from eland.common import build_pd_series, EMPTY_SERIES_DTYPE
+from eland.tests.common import assert_series_equal
 
 
 def test_empty_series_dtypes():
@@ -33,3 +35,9 @@ def test_empty_series_dtypes():
     assert np.int32 != EMPTY_SERIES_DTYPE
     assert s.dtype == np.int32
     assert w == []
+
+
+def test_series_es_dtypes(testdata):
+    series = testdata.ed_flights_small().AvgTicketPrice
+    assert_series_equal(series.es_dtypes, pd.Series(data={"AvgTicketPrice": "float"}))
+    assert series.es_dtype == "float"