add usecase

Author: jreback

doc/source/user_guide/reshaping.rst

@@ -838,3 +838,19 @@ This routine will replace empty lists with ``np.nan`` and preserve scalar entrie
    s = pd.Series([[1, 2, 3], 'foo', [], ['a', 'b']])
    s
    s.explode()
+
+Here is a typical usecase. You have comma separated string in a column.
+
+.. ipython:: python
+
+    df = DataFrame([{'var1': 'a,b,c', 'var2': 1},
+                    {'var1': 'd,e,f', 'var2': 2}])
+    df
+
+Creating a long form DataFrame is now straightforward using chained operations
+
+.. ipython:: python
+
+   exploded = df.var1.str.split(',').explode()
+   exploded
+   df[['var2']].join(exploded)

doc/source/whatsnew/v0.25.0.rst

@@ -187,7 +187,7 @@ The repr now looks like this:
 Series.explode to split list-like values to rows
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-:class:`Series` has gained the :meth:`Series.explode` method to transform list-likes to individual rows. See :ref:`section on Exploding list-like column <reshaping.explode>` in docs for more information (:issue:`16538`)
+:class:`Series` has gained the :meth:`Series.explode` method to transform list-likes to individual rows. See :ref:`section on Exploding list-like column <reshaping.explode>` in docs for more information (:issue:`16538`, :issue:`10511`)
 
 
 .. ipython:: python
@@ -196,6 +196,22 @@ Series.explode to split list-like values to rows
     s
     s.explode()
 
+Here is a typical usecase. You have comma separated string in a column.
+
+.. ipython:: python
+
+    df = DataFrame([{'var1': 'a,b,c', 'var2': 1},
+                    {'var1': 'd,e,f', 'var2': 2}])
+    df
+
+Creating a long form DataFrame is now straightforward using chained operations
+
+.. ipython:: python
+
+   exploded = df.var1.str.split(',').explode()
+   exploded
+   df[['var2']].join(exploded)
+
 .. _whatsnew_0250.enhancements.other:
 
 Other enhancements

pandas/tests/series/test_explode.py

@@ -66,3 +66,15 @@ def test_invert_array():
     listify = df.apply(lambda x: x.array, axis=1)
     result = listify.explode()
     tm.assert_series_equal(result, df["a"].rename())
+
+
+def test_typical_usecase():
+
+    df = pd.DataFrame([{"var1": "a,b,c", "var2": 1}, {"var1": "d,e,f", "var2": 2}])
+    exploded = df.var1.str.split(",").explode()
+    exploded
+    result = df[["var2"]].join(exploded)
+    expected = pd.DataFrame(
+        {"var2": [1, 1, 1, 2, 2, 2], "var1": list("abcdef")}, index=[0, 0, 0, 1, 1, 1]
+    )
+    tm.assert_frame_equal(result, expected, check_like=True)