remove numpy_helper and some unneeded util functions

[jbrockmendel]

• closes #xxxx
• tests added / passed
• passes git diff upstream/master -u -- "*.py" | flake8 --diff
• whatsnew entry

[jbrockmendel]

I'm pretty sure this will be unnecessary after #22325.

[codecov]

Codecov Report

❗ No coverage uploaded for pull request base (master@2be2ba5). Click here to learn what that means.
The diff coverage is 100%.

@@            Coverage Diff            @@
##             master   #22469   +/-   ##
=========================================
  Coverage          ?   92.04%           
=========================================
  Files             ?      169           
  Lines             ?    50740           
  Branches          ?        0           
=========================================
  Hits              ?    46705           
  Misses            ?     4035           
  Partials          ?        0

Flag	Coverage Δ
#multiple	90.45% <100%> (?)
#single	42.24% <0%> (?)

Impacted Files	Coverage Δ
pandas/core/sparse/array.py	91.38% <100%> (ø)

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[jreback]

lgtm. any perf impact?

[jbrockmendel]

any perf impact?

It tentatively looks like the direct indexing is an improvement.

In [4]: arr = np.arange(100000)

In [5]: o = arr.astype('O')

In [6]: %timeit out = lib.astype_intsafe(o, 'i8')

Master:
100 loops, best of 3: 9.47 ms per loop
100 loops, best of 3: 16.3 ms per loop
100 loops, best of 3: 13.8 ms per loop

PR:
100 loops, best of 3: 8.65 ms per loop
100 loops, best of 3: 13.4 ms per loop
100 loops, best of 3: 7.6 ms per loop

In [14]: %timeit out = lib.astype_unicode(o)

Master:
10 loops, best of 3: 43.4 ms per loop
10 loops, best of 3: 63.1 ms per loop
10 loops, best of 3: 70.1 ms per loop
10 loops, best of 3: 68.2 ms per loop

PR:
10 loops, best of 3: 23.1 ms per loop
10 loops, best of 3: 41.4 ms per loop
10 loops, best of 3: 62.9 ms per loop
10 loops, best of 3: 60.4 ms per loop

[jreback]

thanks!