BUG: seemingly unexpected behavior with errrors='ignore' in json_normalize()
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

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#### Code Sample, a copy-pastable example

```python
# raises a KeyError due to the missing 'id' in the second element, even though errors='ignore' was passed
pd.json_normalize(
    data=[{"id": 1, "outer": {"inner": [{"field": 2}]}}, {"outer": {"inner": [{"field": 3}]}}],
    record_path=["outer", "inner"],
    meta=["id"],
    errors="ignore",
)

# no issues since both elements have an 'id', and shows that it is looking for 'id' at the right level
pd.json_normalize(
    data=[{"id": 1, "outer": {"inner": [{"field": 2}]}}, {"id": 4, "outer": {"inner": [{"field": 3}]}}],
    record_path=["outer", "inner"],
    meta=["id"],
    errors="ignore",
)

# no issues when record_path has length 1
pd.json_normalize(
    data=[{"id": 1, "outer": [{"field": 2}]}, {"outer": [{"field": 3}]}],
    record_path=["outer"],
    meta=["id"],
    errors="ignore",
)
```

#### Problem description

I would expect the first case above to return the same output as the third case (i.e., with missing ids filled with `np.nan`). Is the absence of a try...except around the [first _pull_field() call](https://github.com/pandas-dev/pandas/blob/1cad9e52ee1028db3bb4b9e86998104eb4d6b0ee/pandas/io/json/_normalize.py#L304) intentional?

#### Expected Output
```
    field    id
0       2     1
1       3   NaN
```

#### Output of ``pd.show_versions()``


<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.9.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.14.67-ts1
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : en_US.utf8
LOCALE           : en_US.UTF-8

pandas           : 1.0.5
numpy            : 1.16.6
pytz             : 2020.4
dateutil         : 2.8.0
pip              : 19.3.1
setuptools       : 42.0.2
Cython           : None
pytest           : 5.3.1
hypothesis       : 3.57.0
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.5.2
html5lib         : 1.0.1
pymysql          : None
psycopg2         : 2.8.5 (dt dec pq3 ext lo64)
jinja2           : 2.11.1
IPython          : 7.14.0
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : 1.2.1
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.2
matplotlib       : 3.0.3
numexpr          : 2.6.4
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pytables         : None
pytest           : 5.3.1
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.5.1
sqlalchemy       : 1.3.18
tables           : None
tabulate         : 0.8.3
xarray           : None
xlrd             : 1.1.0
xlwt             : None
xlsxwriter       : None
numba            : 0.50.1

</details>
