BUG: json_normalize() upcasts column with missing values
- [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.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

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

```python
import pandas as pd

data = [
  { "c1": 1, "c2": 1, "c3": 1.01 },
  { "c1": 2, "c3": 2.02 },
  { "c1": 3, "c2": 3, "c3": 3.03 }
]

df = pd.json_normalize(data)
print(df, "\n\n", df.dtypes)
```

#### Problem description

When creating a dataframe via `pd.json_normalize()` integer columns are upcast to float if column values are missing for some records even when all other values are consistently integer.

Output:
```
   c1   c2    c3
0   1  1.0  1.01
1   2  NaN  2.02
2   3  3.0  3.03 

c1      int64
c2    float64
c3    float64
```

#### Expected Output

```
   c1   c2    c3
0   1    1  1.01
1   2  NaN  2.02
2   3    3  3.03 

c1      int64
c2      int64
c3    float64
```

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

<details>

INSTALLED VERSIONS

commit : 67a3d42
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-1019-gcp
Version : #19-Ubuntu SMP Tue Jun 23 15:46:40 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.1.4
numpy : 1.19.4
pytz : 2020.4
dateutil : 2.8.1
pip : 20.1.1
setuptools : 47.1.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.19
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None

</details>
