CLN: ASV FromDictwithTimestamp

[mroeschke]

• closes BENCH: FromDictwithTimestampOffset benchmark is not useful #18511

Also removed unnecessary selfs and simplified method names

$ asv run -q -b ^frame_ctor
[  0.00%] ·· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 16.67%] ··· Running frame_ctor.FromDicts.time_dict                                              6.66ms
[ 33.33%] ··· Running frame_ctor.FromDicts.time_list_of_dict                                       114ms
[ 50.00%] ··· Running frame_ctor.FromDicts.time_nested_dict                                       94.1ms
[ 66.67%] ··· Running frame_ctor.FromDicts.time_nested_dict_int64                                  240ms
[ 83.33%] ··· Running frame_ctor.FromDictwithTimestamp.time_dict_with_timestamp_offsets       76.5ms;...
[100.00%] ··· Running frame_ctor.FromSeries.time_mi_series                                         328μs

[codecov]

Codecov Report

Merging #18527 into master will increase coverage by 0.13%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master   #18527      +/-   ##
==========================================
+ Coverage   91.44%   91.58%   +0.13%     
==========================================
  Files         157      153       -4     
  Lines       51378    51273     -105     
==========================================
- Hits        46985    46960      -25     
+ Misses       4393     4313      -80

Flag	Coverage Δ
#multiple	89.45% <ø> (+0.15%)	⬆️
#single	40.68% <ø> (ø)	⬆️

Impacted Files	Coverage Δ
pandas/io/gbq.py	25% <0%> (-58.34%)	⬇️
pandas/util/_test_decorators.py	93.33% <0%> (-1.91%)	⬇️
pandas/stats/moments.py	70.81% <0%> (-0.39%)	⬇️
pandas/core/indexes/multi.py	96.28% <0%> (-0.16%)	⬇️
pandas/core/indexes/datetimes.py	95.59% <0%> (-0.13%)	⬇️
pandas/plotting/_core.py	82.37% <0%> (-0.13%)	⬇️
pandas/core/frame.py	97.81% <0%> (-0.1%)	⬇️
pandas/tseries/frequencies.py	94.02% <0%> (-0.08%)	⬇️
pandas/io/json/normalize.py	96.87% <0%> (-0.07%)	⬇️
pandas/core/window.py	96.31% <0%> (-0.07%)	⬇️
... and 31 more

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[jreback]

cc @jbrockmendel we cover offsets already I believe, so this is superflous.

[mroeschke]

@jorisvandenbossche Much appreciated if you could have a look.

[jorisvandenbossche]

@mroeschke Thanks!