add fix for from_flat

src/nested_pandas/nestedframe/core.py

@@ -211,7 +211,8 @@ def from_flat(cls, df, base_columns, nested_columns=None, index=None, name="nest
         out_df = df[base_columns][~df.index.duplicated(keep="first")]
 
         # add nested
-        nested_columns = [col for col in df.columns if col not in base_columns]
+        if nested_columns is None:
+            nested_columns = [col for col in df.columns if col not in base_columns]
         return out_df.add_nested(df[nested_columns], name=name)
 
     @classmethod

tests/nested_pandas/nestedframe/test_nestedframe.py

@@ -319,6 +319,20 @@ def test_recover_from_flat():
 
     assert nf2.equals(nf)
 
+def test_from_flat_omitting_columns():
+    """test that from_flat successfully produces subsets"""
+    flat = NestedFrame({"a":[1,1,1,2,2], "b":[2,2,2,4,4], "c":[1,2,3,4,5], 
+                     "d":[2,4,6,8,10]}, index=[0,0,0,1,1])
+
+    # omit a base column
+    nf = NestedFrame.from_flat(flat, base_columns=["b"], nested_columns=["c", "d"])
+    assert list(nf.columns) == ["b", "nested"]
+    assert list(nf.nested.nest.fields) == ["c", "d"]
+
+    # omit a nested column
+    nf = NestedFrame.from_flat(flat, base_columns=["a", "b"], nested_columns=["c"])
+    assert list(nf.columns) == ["a", "b", "nested"]
+    assert list(nf.nested.nest.fields) == ["c"]
 
 def test_from_lists():
     """Test NestedFrame.from_lists behavior"""