Add Int64Index, Float64Index, DatetimeIndex.

[ueshin]

Adds Int64Index, Float64Index, and DatetimeIndex as a placeholder.
We should still add specific attributes and methods in the following PRs.

Before:

>>> kdf = ks.DataFrame([1,2,3])
>>> type(kdf.index)
<class 'databricks.koalas.indexes.Index'>

After:

>>> type(kdf.index)
<class 'databricks.koalas.indexes.numeric.Int64Index'>

[codecov-io]

Codecov Report

Merging #2025 (fa7c5cb) into master (885fdfc) will increase coverage by 0.03%.
The diff coverage is 96.47%.

@@            Coverage Diff             @@
##           master    #2025      +/-   ##
==========================================
+ Coverage   94.61%   94.64%   +0.03%     
==========================================
  Files          50       54       +4     
  Lines       11263    11393     +130     
==========================================
+ Hits        10656    10783     +127     
- Misses        607      610       +3     

Impacted Files	Coverage Δ
databricks/koalas/internal.py	96.09% <87.50%> (-0.51%)	⬇️
databricks/koalas/namespace.py	84.41% <92.30%> (+0.21%)	⬆️
databricks/koalas/indexes/multi.py	95.80% <95.80%> (ø)
databricks/koalas/__init__.py	91.04% <100.00%> (+0.41%)	⬆️
databricks/koalas/frame.py	96.61% <100.00%> (-0.01%)	⬇️
databricks/koalas/indexes/__init__.py	100.00% <100.00%> (ø)
databricks/koalas/indexes/base.py	97.43% <100.00%> (ø)
databricks/koalas/indexes/datetimes.py	100.00% <100.00%> (ø)
databricks/koalas/indexes/numeric.py	100.00% <100.00%> (ø)
databricks/koalas/missing/indexes.py	100.00% <100.00%> (ø)
... and 5 more

---

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[xinrong-meng]

May I ask for the reason why we don't support UInt64Index as https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.UInt64Index.html?

[ueshin]

Because Koalas doesn't support unsigned types.

[xinrong-meng]

Got it! Thanks!

[xinrong-meng]

Nice refactoring!

[xinrong-meng]

It might be helpful we add some code examples in the PR description to explain what changes are introduced by this PR, for example,

Before:

>>> kdf = ks.DataFrame([1,2,3])
>>> type(kdf.index)
<class 'databricks.koalas.indexes.Index'>

After:

>>> type(kdf.index)
<class 'databricks.koalas.indexes.numeric.Int64Index'>

[xinrong-meng]

LGTM! Thank you for doing this!