docs

docs/getting/tutorial.rst

@@ -49,7 +49,7 @@ Operations with columns are units aware so behave as we would intuitively expect
 
    Notice that the units are not displayed in the cells of the DataFrame.
    If you ever see units in the cells of the DataFrame, something isn't right.
-   See :ref:`units_in_cells` for more information.
+   See :doc:`Units in Cells <../user/common>` for more information.
 
 We can see the columns' units in the dtypes attribute
 

docs/user/initializing.rst

@@ -54,3 +54,20 @@ To avoid this conversion, specify the subdtype (dtype of the magnitudes) in the
 .. note::
 
    ``"pint[unit]"`` or ``"pint[unit][subdtype]"`` must be used for the Series or DataFrame constuctor.
+
+Non-native pandas dtypes
+-------------------------
+
+``PintArray`` uses an ``ExtensionArray`` to hold its data inclluding those from other libraries that extend pandas.
+For example, an ``UncertaintyArray`` can be used.
+
+.. ipython:: python
+
+    from uncertainties_pandas import UncertaintyArray, UncertaintyDtype
+    from uncertainties import ufloat, umath, unumpy
+
+    ufloats = [ufloat(i, abs(i) / 100) for i in [4.0, np.nan, -5.0]]
+    uarr = UncertaintyArray(ufloats)
+    uarr
+    PintArray(uarr,"m")
+    pd.Series(PintArray(uarr,"m")*2)

docs/user/numpy.rst

@@ -17,10 +17,10 @@ Numpy functions that work on pint ``Quantity`` ``ndarray`` objects also work on
 
     PintArray = pint_pandas.PintArray
     ureg = pint_pandas.PintType.ureg
-    Q_ = ureg.Quantity
+    Quantity = ureg.Quantity
 
 .. ipython:: python
-    
+
     pa = PintArray([1, 2, np.nan, 4, 10], dtype="pint[m]")
     np.clip(pa, 3 * ureg.m, 5 * ureg.m)
 

requirements_docs.txt

@@ -20,3 +20,4 @@ sphinx-book-theme>=1.1.0
 sphinx_copybutton
 sphinx_design
 typing_extensions
+uncertainties-pandas