json_normalize raises TypeError exception
#### Code Sample, a copy-pastable example if possible

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

d = {
    'name': 'alan smith',    
    'info': {
        'phones': [{
            'area': 111,
            'number': 2222
        }, {
            'area': 333,
            'number': 4444
        }]
    }
}
json_normalize(d, record_path=["info", "phones"])
```
#### Problem description

The above code throws `TypeError` exception:
```
Traceback (most recent call last):
  File ".\test.py", line 15, in <module>
    json_normalize(d, record_path = ["info", "phones"])
  File "C:\Python36\lib\site-packages\pandas\io\json\normalize.py", line 262, in json_normalize
    _recursive_extract(data, record_path, {}, level=0)
  File "C:\Python36\lib\site-packages\pandas\io\json\normalize.py", line 235, in _recursive_extract
    seen_meta, level=level + 1)
  File "C:\Python36\lib\site-packages\pandas\io\json\normalize.py", line 238, in _recursive_extract
    recs = _pull_field(obj, path[0])
  File "C:\Python36\lib\site-packages\pandas\io\json\normalize.py", line 185, in _pull_field
    result = result[spec]
TypeError: string indices must be integers
```

#### Expected Output
| |area|number|
|-|-|-|
|0|111|2222|
|1|333|4444|
#### 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: 0.23.4
pytest: 3.6.2
pip: 18.0
setuptools: 40.2.0
Cython: None
numpy: 1.14.5
scipy: None
pyarrow: None
xarray: None
IPython: 6.3.1
sphinx: 1.5.5
patsy: None
dateutil: 2.7.3
pytz: 2018.5
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>
