Add new optional "separator" argument to json_normalize

doc/source/whatsnew/v0.20.0.txt

@@ -84,6 +84,7 @@ Other enhancements
 - ``pd.DataFrame.plot`` now prints a title above each subplot if ``suplots=True`` and ``title`` is a list of strings (:issue:`14753`)
 - ``pd.Series.interpolate`` now supports timedelta as an index type with ``method='time'`` (:issue:`6424`)
 - ``pandas.io.json.json_normalize()`` gained the option ``errors='ignore'|'raise'``; the default is ``errors='raise'`` which is backward compatible. (:issue:`14583`)
+- ``pandas.io.json.json_normalize()`` gained the option ``separator=string``; the default is ``separator='.'`` which is backward compatible. (:issue:`14883`)
 
 
 .. _whatsnew_0200.api_breaking:

pandas/io/json.py

@@ -24,8 +24,8 @@ def to_json(path_or_buf, obj, orient=None, date_format='epoch',
             default_handler=None, lines=False):
 
     if lines and orient != 'records':
-            raise ValueError(
-                "'lines' keyword only valid when 'orient' is records")
+        raise ValueError(
+            "'lines' keyword only valid when 'orient' is records")
 
     if isinstance(obj, Series):
         s = SeriesWriter(
@@ -726,8 +726,8 @@ def nested_to_record(ds, prefix="", level=0):
 def json_normalize(data, record_path=None, meta=None,
                    meta_prefix=None,
                    record_prefix=None,
+                   separator='.',
                    errors='raise'):
-
     """
     "Normalize" semi-structured JSON data into a flat table
 
@@ -744,6 +744,9 @@ def json_normalize(data, record_path=None, meta=None,
         If True, prefix records with dotted (?) path, e.g. foo.bar.field if
         path to records is ['foo', 'bar']
     meta_prefix : string, default None
+    separator : string, default '.'
+        Nested records will generate names separated by separator,
+        e.g., for separator='.', { 'foo' : { 'bar' : 0 } } -> foo.bar
     errors : {'raise', 'ignore'}, default 'raise'
         * ignore : will ignore KeyError if keys listed in meta are not
         always present
@@ -828,7 +831,7 @@ def _pull_field(js, spec):
     lengths = []
 
     meta_vals = defaultdict(list)
-    meta_keys = ['.'.join(val) for val in meta]
+    meta_keys = [separator.join(val) for val in meta]
 
     def _recursive_extract(data, path, seen_meta, level=0):
         if len(path) > 1:

pandas/io/tests/json/test_json_norm.py

@@ -133,6 +133,36 @@ def test_shallow_nested(self):
         expected = DataFrame(ex_data, columns=result.columns)
         tm.assert_frame_equal(result, expected)
 
+    def test_shallow_nested_with_separator(self):
+        data = [{'state': 'Florida',
+                 'shortname': 'FL',
+                 'info': {
+                     'governor': 'Rick Scott'
+                 },
+                 'counties': [{'name': 'Dade', 'population': 12345},
+                              {'name': 'Broward', 'population': 40000},
+                              {'name': 'Palm Beach', 'population': 60000}]},
+                {'state': 'Ohio',
+                 'shortname': 'OH',
+                 'info': {
+                     'governor': 'John Kasich'
+                 },
+                 'counties': [{'name': 'Summit', 'population': 1234},
+                              {'name': 'Cuyahoga', 'population': 1337}]}]
+
+        result = json_normalize(data, 'counties',
+                                ['state', 'shortname',
+                                 ['info', 'governor']],
+                                separator='_')
+        ex_data = {'name': ['Dade', 'Broward', 'Palm Beach', 'Summit',
+                            'Cuyahoga'],
+                   'state': ['Florida'] * 3 + ['Ohio'] * 2,
+                   'shortname': ['FL', 'FL', 'FL', 'OH', 'OH'],
+                   'info_governor': ['Rick Scott'] * 3 + ['John Kasich'] * 2,
+                   'population': [12345, 40000, 60000, 1234, 1337]}
+        expected = DataFrame(ex_data, columns=result.columns)
+        tm.assert_frame_equal(result, expected)
+
     def test_meta_name_conflict(self):
         data = [{'foo': 'hello',
                  'bar': 'there',