Add Series.map

[HyukjinKwon]

This PR adds Series.map. If the function is given as an argument, seems we can just reuse apply.

>>> import pandas as pd
>>> pdf = pd.DataFrame({'a': [1,2,3,4,5,6]})
>>> pdf.a.apply(lambda x: x+  1)
0    2
1    3
2    4
3    5
4    6
5    7
Name: a, dtype: int64
>>> pdf.a.map(lambda x: x+  1)
0    2
1    3
2    4
3    5
4    6
5    7
Name: a, dtype: int64

[HyukjinKwon]

I will add this one soon.

[codecov-io]

Codecov Report

Merging #389 into master will increase coverage by 0.02%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master     #389      +/-   ##
==========================================
+ Coverage   94.75%   94.77%   +0.02%     
==========================================
  Files          42       42              
  Lines        4554     4577      +23     
==========================================
+ Hits         4315     4338      +23     
  Misses        239      239

Impacted Files	Coverage Δ
databricks/koalas/missing/series.py	100% <ø> (ø)	⬆️
databricks/koalas/series.py	93.95% <100%> (+0.36%)	⬆️
databricks/koalas/tests/test_series.py	100% <100%> (ø)	⬆️
databricks/koalas/generic.py	93.75% <0%> (-0.42%)	⬇️
databricks/koalas/frame.py	95.65% <0%> (+0.11%)	⬆️

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[HyukjinKwon]

It's a hack to mimic Pandas's behaviour with defaultdict... but I believe basically the behaviours are matched when the input is a dictionary

[thunterdb]

Super cool! My only concern is that you are mutating 'arg', but this strikes me as an edge case for now.

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