DOC: Mention Index.equals takes into account order of arguments
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#### Code Sample, a copy-pastable example

```python
import pandas as pd
pd.Index(['10607', '6574', '6621', '99917']).equals(pd.Index(['99917', '10607', '6574', '6621'])) # False
set(['10607', '6574', '6621', '99917']) == set(['99917', '10607', '6574', '6621']) # True
```

#### Problem description

I have seen #13708, but according to documentation:

> Determine if two Index objects contain the same elements.

Should it return `True`  instead?

Reading how the function is implemented:

https://github.com/pandas-dev/pandas/blob/3adf3340453d6704d4a2cb47058214cc697a7d29/pandas/core/indexes/base.py#L4072-L4074

It relies on:

https://github.com/pandas-dev/pandas/blob/3adf3340453d6704d4a2cb47058214cc697a7d29/pandas/core/dtypes/missing.py#L421-L431

Which is indeed strict and do take order into account.

#### Expected Output

As I understand the equality of index is about having the same elements. It is not required the elements having the same order. I have the feeling that once pandas worked this way (maybe before `v0.23`).

What is the intended way ? Maybe the documentation should be a bit more explicit about this comparison. If you indicate me where I can update the doc, I will be glad to edit it.

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

<details>

commit           : None
python           : 3.6.9.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-91-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 9.0.1
setuptools       : 46.1.3
Cython           : 0.29.14
pytest           : 5.3.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.1.8
lxml.etree       : 4.3.4
html5lib         : 0.999999999
pymysql          : None
psycopg2         : 2.8.4 (dt dec pq3 ext lo64)
jinja2           : 2.11.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : 4.7.1
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.3.4
matplotlib       : 3.2.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.13.0
pytables         : None
pytest           : 5.3.2
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.15
tables           : None
tabulate         : 0.8.3
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.1.8
numba            : None

</details>
