df.index.is_unique inflates index memory 
calling is_unique on an Int64Index seems to inflate the index memory.

```python
l = np.arange(9)
df = pd.DataFrame({'a':l, 'b':l, 'c':l})
print('shape', df.shape)

display(df.memory_usage(deep=True, index=True))
print()

print('drop one row')
df.drop(index=[1], inplace=True)
display(df.memory_usage(deep=True, index=True))
print()

print('is_unique: ', df.index.is_unique)
display(df.memory_usage(deep=True, index=True))
print()

print('drop another row')
df.drop(index=[3], inplace=True)
display(df.memory_usage(deep=True, index=True))
print()

print('is_unique: ', df.index.is_unique)
display(df.memory_usage(deep=True, index=True))
```

output:
```
shape (9, 3)
Index    80
a        36
b        36
c        36
dtype: int64

drop one row
Index    64
a        32
b        32
c        32
dtype: int64

is_unique:  True
Index    384
a         32
b         32
c         32
dtype: int64

drop another row
Index    56
a        28
b        28
c        28
dtype: int64

is_unique:  True
Index    376
a         28
b         28
c         28
dtype: int64
```

#### Problem description

any explanation why the index size grows after the call to index.is_unique?

#### Expected Output

no change in index size is expected

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.9.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.2
pytest: None
pip: 19.1.1
setuptools: 39.1.0
Cython: None
numpy: 1.17.0
scipy: None
pyarrow: None
xarray: None
IPython: 7.7.0
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.1.0
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: 4.3.4
bs4: None
html5lib: None
sqlalchemy: 1.3.12
pymysql: 0.9.3
psycopg2: None
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
