json_normalize throws `AttributeError` when calling with array of values
#### Code Sample, a copy-pastable example if possible

xref #21605

```python
from pandas.io.json import json_normalize

json_normalize([1, 2])

```
#### Problem description

The above code throws `AttributeError`:
```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Python36\lib\site-packages\pandas\io\json\normalize.py", line 193, in json_normalize
    for x in compat.itervalues(y)] for y in data]):
  File "C:\Python36\lib\site-packages\pandas\io\json\normalize.py", line 193, in <listcomp>
    for x in compat.itervalues(y)] for y in data]):
  File "C:\Python36\lib\site-packages\pandas\compat\__init__.py", line 211, in itervalues
    return iter(obj.values(**kw))
AttributeError: 'int' object has no attribute 'values'
```

#### Expected Output
| |0|
|-|-|
|0|1|
|1|2|
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 62 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.1
pytest: 3.6.1
pip: 10.0.1
setuptools: 28.8.0
Cython: None
numpy: 1.14.2
scipy: None
pyarrow: None
xarray: None
IPython: 6.3.1
sphinx: None
patsy: None
dateutil: 2.7.2
pytz: 2018.4
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
