ENH: Explode multiple columns of DataFrame

pandas/core/frame.py

@@ -6205,16 +6205,16 @@ def stack(self, level=-1, dropna=True):
         else:
             return stack(self, level, dropna=dropna)
 
-    def explode(self, column: Union[str, Tuple]) -> "DataFrame":
+    def explode(self, columns: Union[str, List[str]]) -> "DataFrame":
         """
         Transform each element of a list-like to a row, replicating index values.
 
         .. versionadded:: 0.25.0
 
         Parameters
         ----------
-        column : str or tuple
-            Column to explode.
+        columns : str or list
+            the column(s) to be exploded
 
         Returns
         -------
@@ -6260,19 +6260,63 @@ def explode(self, column: Union[str, Tuple]) -> "DataFrame":
         2  NaN  1
         3    3  1
         3    4  1
-        """
 
-        if not (is_scalar(column) or isinstance(column, tuple)):
-            raise ValueError("column must be a scalar")
+        >>> df = pd.DataFrame({'A': [[1, 2, 3], 'foo', [], [3, 4]],
+                               'B': 1,
+                               'C': [[7,8,9],'bar',[],[8,7]]})
+        >>> df
+                   A  B          C
+        0  [1, 2, 3]  1  [7, 8, 9]
+        1        foo  1        bar
+        2         []  1         []
+        3     [3, 4]  1     [8, 7]
+
+        >>> df.explode(['A','C'])
+           B    A    C
+        0  1    1    7
+        0  1    2    8
+        0  1    3    9
+        1  1  foo  bar
+        2  1  NaN  NaN
+        3  1    3    8
+        3  1    4    7
+        """
+
+        # Validate data
         if not self.columns.is_unique:
             raise ValueError("columns must be unique")
 
-        result = self[column].explode()
-        return (
-            self.drop([column], axis=1)
-            .join(result)
-            .reindex(columns=self.columns, copy=False)
-        )
+        if isinstance(columns, str):
+            columns = [columns]
+
+        if not isinstance(columns, list):
+            raise TypeError("columns value not list or sting")
+
+        if not all([c in self.columns for c in columns]):
+            raise ValueError("column name(s) not in index")
+
+        tmp = self.iloc[0:0, 0:0].copy()  # creates empty temp df
+        lengths_equal = []
+
+        for row in self[columns].iterrows():
+            # converts non-lists into 1 element lists so len() is valid
+            r = row[1].apply(lambda x: x if type(x) in (list, tuple) else [x])
+
+            # make sure all lists in the same record are the same length
+            row_is_ok = len(set([len(r[c]) for c in columns])) == 1
+            lengths_equal.append(row_is_ok)
+
+        # Explode all columns if lengths match
+        if all(lengths_equal):
+            for c in columns:
+                tmp[c] = self[c].explode()
+        else:
+            e = "Elements in `columns` do not have equal length in the same row"
+            raise ValueError(e)
+
+        # join in exploded columns
+        results = self.drop(columns, axis=1).join(tmp)
+        return(results)
 
     def unstack(self, level=-1, fill_value=None):
         """