json_normalize skips an entry in a pymongo cursor
I am sorry for not being able to provide a reproducible example, but any attempt to reduce the problem to something limited makes the problem disappear.

```python
In [54]: res = client.events.api.longterm.find({'foo': 'bar'})

In [55]: res.count()
Out[55]: 76845

In [56]: len(pd.io.json.json_normalize(res))
Out[56]: 76844

In [57]: res = client.events.api.longterm.find({'foo': 'bar'})

In [58]: len(pd.io.json.json_normalize(list(res)))
Out[58]: 76845
```
#### Problem description

I have a pretty large collection of documents in MongoDB, which I am querying using pymongo. The resulting cursor is passed to `pd.io.json.json_normalize` to convert the resulting data into a data frame. In one example, which I am unfortunately unable to reduce to something reproducible, a single element of the 76845 entries in the cursor is not present in the resulting data frame. If I convert the cursor to a list before using `json_normalize`, all entries are present. The affected document itself looks completely sane and without anything suspicious. Moreover, the default for `json_normalize` should be to raise errors and not to swallow rows.

#### Expected Output

All 76845 rows are present in the result when passing the cursor directly to `json_normalize`.

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.0.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.3-arch1-1
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.3
numpy            : 1.17.4
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 42.0.2
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : 7.10.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : 3.0.2
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

</details>
