BUG: read_json() converts non-existent fields in text 'NaN'
- [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.

---


I am reading a big JSON file with json in lines:
`pandas.read_json("big_file.json", chunksize=20, lines=True)`

- There are some extra keys in some lines, so non-existent keys are converted to NaN.
- Dtype is object
- I discovered it when I was trying to save into database because it fails to convert 'NaN' to JSON_ARRAY()
- `dataframe.fillna('value')` is not working with that value
- NaN is considered non-null (text)

```
RangeIndex: 20 entries, 40 to 59
Data columns (total 6 columns):
 #   Column    Non-Null Count  Dtype 
---  ------    --------------  ----- 
 0   t_list    20 non-null     object
...
```


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

<details>

```
INSTALLED VERSIONS
------------------
commit           : 7d32926db8f7541c356066dcadabf854487738de
python           : 3.8.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-65-generic
Version          : #73-Ubuntu SMP Mon Jan 18 17:25:17 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.2
numpy            : 1.20.1
pytz             : 2021.1
dateutil         : 2.7.3
pip              : 21.0.1
setuptools       : 45.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : 1.0.2
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.20.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : 1.3.23
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None
```

</details>
