Adding shape to DataTable and DataColumn (#358)

* adding shape and testing

* release notes updated

* isinstance, api ref

* better/more testing

* linting

docs/source/api_reference.rst

@@ -10,6 +10,7 @@ DataTable
     :toctree: generated/
 
     DataTable
+    DataTable.shape
     DataTable.add_semantic_tags
     DataTable.remove_semantic_tags
     DataTable.reset_semantic_tags
@@ -35,6 +36,7 @@ DataColumn
     :toctree: generated/
 
     DataColumn
+    DataColumn.shape
     DataColumn.add_semantic_tags
     DataColumn.remove_semantic_tags
     DataColumn.reset_semantic_tags

docs/source/release_notes.rst

@@ -8,6 +8,7 @@ Release Notes
         * Add ``__eq__`` to DataTable and DataColumn and update LogicalType equality (:pr:`318`)
         * Add ``value_counts()`` method to DataTable (:pr:`342`)
         * Support serialization and deserialization of DataTables via csv, pickle, or parquet (:pr:`293`)
+        * Add ``shape`` property to DataTable and DataColumn (:pr:`358`)
     * Fixes
         * Catch non numeric time index at validation (:pr:`332`)
     * Changes

woodwork/data_column.py

@@ -280,6 +280,12 @@ def to_series(self):
         """
         return self._series
 
+    @property
+    def shape(self):
+        """Returns a tuple representing the dimensionality of the DataTable. If Dask DataFrame, returns
+            a Dask `Delayed` object for the number of rows."""
+        return self._series.shape
+
     @property
     def logical_type(self):
         """The logical type for the column"""

woodwork/data_table.py

@@ -205,6 +205,12 @@ def semantic_tags(self):
         """A dictionary containing semantic tags for each column"""
         return {dc.name: dc.semantic_tags for dc in self.columns.values()}
 
+    @property
+    def shape(self):
+        """Returns a tuple representing the dimensionality of the DataTable. If Dask DataFrame, returns
+            a Dask `Delayed` object for the number of rows."""
+        return self._dataframe.shape
+
     @property
     def index(self):
         """The index column for the table"""

woodwork/tests/data_column/test_data_column.py

@@ -436,6 +436,17 @@ def test_to_series(sample_series):
     pd.testing.assert_series_equal(to_pandas(series), to_pandas(data_col._series))
 
 
+def test_shape(categorical_df):
+    col = DataColumn(categorical_df['ints'])
+    assert col.shape == (9,)
+    assert col.shape == col.to_series().shape
+
+
+def test_shape_dask(categorical_dd):
+    col = DataColumn(categorical_dd['ints'])
+    assert col.to_series().compute().shape == col.shape[0].compute()
+
+
 def test_dtype_update_on_init(datetime_series):
     dc = DataColumn(datetime_series,
                     logical_type='DateTime')

woodwork/tests/data_table/test_datatable.py

@@ -4,6 +4,7 @@
 import numpy as np
 import pandas as pd
 import pytest
+from dask.delayed import Delayed
 
 import woodwork as ww
 from woodwork import DataColumn, DataTable
@@ -1557,6 +1558,27 @@ def test_datatable_clear_time_index(sample_df):
     assert all(['time_index' not in col.semantic_tags for col in dt.columns.values()])
 
 
+def test_shape(categorical_df, categorical_log_types):
+    dt = ww.DataTable(categorical_df, logical_types=categorical_log_types)
+    assert dt.shape == (9, 5)
+    assert dt.shape == dt.to_dataframe().shape
+
+    dt.pop('ints')
+    assert dt.shape == (9, 4)
+
+
+def test_shape_dask(categorical_dd, categorical_log_types):
+    dt = ww.DataTable(categorical_dd, logical_types=categorical_log_types)
+    assert isinstance(dt.shape[0], Delayed)
+    assert dt.shape[1] == 5
+
+    dt.pop('bools')
+    assert isinstance(dt.shape[0], Delayed)
+    assert dt.shape[1] == 4
+
+    assert (dt.shape[0].compute(), dt.shape[1]) == (len(dt.to_dataframe()), len(dt.columns))
+
+
 def test_select_invalid_inputs(sample_df):
     dt = DataTable(sample_df, time_index='signup_date', index='id', name='dt_name')
     dt = dt.set_logical_types({