BUG: DataFrame creates an object-dtype array for extension type scalars in dictionaries
- [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.

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

---

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

```python
df = pd.DataFrame({
    'a': [pd.Period('2020-01')],
    'b': pd.Period('2020-01')
})

df.dtypes
```

#### Problem description

In the example above, column `a` will be correctly created as a `period[m]` column, but column `b` will be an `object` type. This is similar to an [issue 34832](https://github.com/pandas-dev/pandas/issues/34832), but for a different DF instantiation method.

#### Expected Output

These two columns should have identical types. They should both be type `period[m]`.

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

<details>

INSTALLED VERSIONS
------------------
commit           : c413df6d6a85eb411cba39b907fe7a74bdf4be1f
python           : 3.7.6.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
Version          : Darwin Kernel Version 18.7.0: Sun Dec  1 18:59:03 PST 2019; root:xnu-4903.278.19~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.0.dev0+173.gc413df6d6.dirty
numpy            : 1.18.5
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 47.3.1.post20200616
Cython           : 0.29.20
pytest           : 5.4.3
hypothesis       : 5.16.2
sphinx           : 3.1.1
blosc            : 1.9.1
feather          : None
xlsxwriter       : 1.2.9
lxml.etree       : 4.5.1
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.15.0
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : 1.3.2
fsspec           : 0.7.4
fastparquet      : 0.4.0
gcsfs            : None
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : 0.17.1
pytables         : None
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.4.1
sqlalchemy       : 1.3.17
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.15.1
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.50.0

</details>
