BUG: memory_usage(deep=True) of dtype='string' is wrong
- [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
In [4]: s = pd.Series(['a','b','c'],dtype='object')
   ...: print(s.memory_usage())
   ...: print(s.memory_usage(deep=True))
152
326

In [5]: s = pd.Series(['a','b','c'],dtype='string')
   ...: print(s.memory_usage())
   ...: print(s.memory_usage(deep=True))
152
152
```

#### Problem description

memory_usage(deep=True) for new 'string' dtype is not 'deep' size.

#### Expected Output
In [3]: s = pd.Series(['a','b','c'],dtype='string')
   ...: print(s.memory_usage())
   ...: print(s.memory_usage(deep=True))
152
326

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

<details>
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.4.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.17.3
pytz             : 2019.3
dateutil         : 2.8.0
pip              : 20.1
setuptools       : 40.8.0
Cython           : 0.29.16
pytest           : 5.2.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.2.2
lxml.etree       : 4.4.2
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.8.0
pandas_datareader: None
bs4              : 4.9.0
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.4.2
matplotlib       : 3.1.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.0
pandas_gbq       : None
pyarrow          : 0.15.0
pytables         : None
pytest           : 5.2.1
pyxlsb           : None
s3fs             : 0.2.2
scipy            : 1.3.1
sqlalchemy       : None
tables           : None
tabulate         : 0.8.5
xarray           : None
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : 1.2.2
numba            : None
</details>
