FIX: 'parser_trim_buffers' properly initializes word pointers
### Summary

The pull request:
- [x] closes #13703;
- [x] passes all tests in `test.sh` except one (see the output);
- [x] passes the code style test `git diff upstream/master | flake8 --diff`;
### Details

Basically the function [**parse_trim_buffers**](https://github.com/pydata/pandas/blob/master/pandas/src/parser/tokenizer.c#L1217) did not properly move word pointers in **parser->words** and related fields. This pull request aims at fixing that.

Changes in **parse_trim_buffers**:
- block **L1239 -- L1256** (**/&ast; trim stream &ast;/**) was augmented with **parser->words** update loop;
- blocks **L1224 -- L1237** (**/&ast; trim words, word_starts &ast;/**) and **L1239 -- L1256**(**/&ast; trim stream &ast;/**) were swapped to preserve pointer consistency;
### Output of `test.sh`:

```
======================================================================
FAIL: test_round_trip_frame_sep (pandas.io.tests.test_clipboard.TestClipboard)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/Users/ivannz/Github/pd_fork/pandas/pandas/io/tests/test_clipboard.py", line 73, in test_round_trip_frame_sep
    self.check_round_trip_frame(dt, sep=',')
  File "/Users/ivannz/Github/pd_fork/pandas/pandas/io/tests/test_clipboard.py", line 69, in check_round_trip_frame
    tm.assert_frame_equal(data, result, check_dtype=False)
  File "/Users/ivannz/Github/pd_fork/pandas/pandas/util/testing.py", line 1276, in assert_frame_equal
    right.columns))
  File "/Users/ivannz/Github/pd_fork/pandas/pandas/util/testing.py", line 1022, in raise_assert_detail
    raise AssertionError(msg)
AssertionError: DataFrame are different

DataFrame shape (number of columns) are different
[left]:  2, Index([u'en', u'es'], dtype='object')
[right]: 0, Index([], dtype='object')

----------------------------------------------------------------------
Ran 10377 tests in 1197.728s

FAILED (SKIP=363, failures=1)
```

Apart from this, there were a couple of _deprecation warnings_ in files other that _tokenizer.c_.

can you add a test that reproduces the segfault (and this PR fixes)
 this is going to need a run of the asv suite for the csv benchmarks to see if anything changed. see [here](http://pandas.pydata.org/pandas-docs/stable/contributing.html#running-the-performance-test-suite)
 ## [Current coverage](https://codecov.io/gh/pydata/pandas/pull/13788?src=pr) is 85.23% (diff: 100%)

> Merging [#13788](https://codecov.io/gh/pydata/pandas/pull/13788?src=pr) into [master](https://codecov.io/gh/pydata/pandas/branch/master?src=pr) will not change coverage

``` diff
@@             master     #13788   diff @@
==========================================
  Files           140        140          
  Lines         50415      50415          
  Methods           0          0          
  Messages          0          0          
  Branches          0          0          
==========================================
  Hits          42971      42971          
  Misses         7444       7444          
  Partials          0          0          
```

> Powered by [Codecov](https://codecov.io?src=pr). Last update [a3cddfa...d59624e](https://codecov.io/gh/pydata/pandas/compare/a3cddfa9c4302c13747509caef7a056159010adf...d59624eddf063c9da12f1f95227d8e9c9b00cf6e?src=pr)
 I ran the ASV benchmarks. It says

```
[ 12.88%] ··· Running gil.nogil_read_csv.time_nogil_read_csv                                                                                          327.76ms
[ 12.88%] ··· Running gil.nogil_read_csv.time_nogil_read_csv                                                                                          327.76ms
[ 12.94%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_datetime                                                                                 326.62ms
[ 13.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_object                                                                                    18.14ms
[ 30.96%] ··· Running io_bench.read_csv_from_s3.time_read_nrows                                                                                        n/a;...
[ 31.02%] ··· Running io_bench.read_csv_infer_datetime_format_custom.time_read_csv_infer_datetime_format_custom                                        11.53ms
[ 31.08%] ··· Running io_bench.read_csv_infer_datetime_format_iso8601.time_read_csv_infer_datetime_format_iso8601                                       2.07ms
[ 31.14%] ··· Running io_bench.read_csv_infer_datetime_format_ymd.time_read_csv_infer_datetime_format_ymd                                               2.13ms
[ 31.20%] ··· Running io_bench.read_csv_skiprows.time_read_csv_skiprows                                                                                12.84ms
[ 31.26%] ··· Running io_bench.read_csv_standard.time_read_csv_standard                                                                                11.19ms
[ 34.46%] ··· Running packers.packers_read_csv.time_packers_read_csv                                                                                  180.63ms
[ 36.88%] ··· Running parser_vb.read_csv_comment2.time_read_csv_comment2                                                                               25.18ms
[ 36.94%] ··· Running parser_vb.read_csv_default_converter.time_read_csv_default_converter                                                              1.94ms
[ 37.00%] ··· Running parser_vb.read_csv_default_converter_python_engine.time_read_csv_default_converter                                                3.26ms
[ 37.06%] ··· Running parser_vb.read_csv_default_converter_with_decimal.time_read_csv_default_converter_with_decimal                                    1.98ms
[ 37.12%] ··· Running parser_vb.read_csv_default_converter_with_decimal_python_engine.time_read_csv_default_converter_with_decimal                      9.93ms
[ 37.18%] ··· Running parser_vb.read_csv_precise_converter.time_read_csv_precise_converter                                                              1.91ms
[ 37.24%] ··· Running parser_vb.read_csv_roundtrip_converter.time_read_csv_roundtrip_converter                                                          2.61ms
[ 37.30%] ··· Running parser_vb.read_csv_thou_vb.time_read_csv_thou_vb                                                                                 25.74ms
[ 37.36%] ··· Running parser_vb.read_csv_vb.time_read_csv_vb                                                                                           21.59ms
[ 62.88%] ··· Running gil.nogil_read_csv.time_nogil_read_csv                                                                                          321.78ms
[ 62.94%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_datetime                                                                                 322.15ms
[ 63.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_object                                                                                    16.19ms
[ 80.96%] ··· Running io_bench.read_csv_from_s3.time_read_nrows                                                                                        n/a;...
[ 81.02%] ··· Running io_bench.read_csv_infer_datetime_format_custom.time_read_csv_infer_datetime_format_custom                                        11.52ms
[ 81.08%] ··· Running io_bench.read_csv_infer_datetime_format_iso8601.time_read_csv_infer_datetime_format_iso8601                                       2.03ms
[ 81.14%] ··· Running io_bench.read_csv_infer_datetime_format_ymd.time_read_csv_infer_datetime_format_ymd                                               2.10ms
[ 81.20%] ··· Running io_bench.read_csv_skiprows.time_read_csv_skiprows                                                                                12.41ms
[ 81.26%] ··· Running io_bench.read_csv_standard.time_read_csv_standard                                                                                10.81ms
[ 84.46%] ··· Running packers.packers_read_csv.time_packers_read_csv                                                                                  171.84ms
[ 86.88%] ··· Running parser_vb.read_csv_comment2.time_read_csv_comment2                                                                               25.49ms
[ 86.94%] ··· Running parser_vb.read_csv_default_converter.time_read_csv_default_converter                                                              1.87ms
[ 87.00%] ··· Running parser_vb.read_csv_default_converter_python_engine.time_read_csv_default_converter                                                3.26ms
[ 87.06%] ··· Running parser_vb.read_csv_default_converter_with_decimal.time_read_csv_default_converter_with_decimal                                    1.80ms
[ 87.12%] ··· Running parser_vb.read_csv_default_converter_with_decimal_python_engine.time_read_csv_default_converter_with_decimal                      9.94ms
[ 87.18%] ··· Running parser_vb.read_csv_precise_converter.time_read_csv_precise_converter                                                              1.74ms
[ 87.24%] ··· Running parser_vb.read_csv_roundtrip_converter.time_read_csv_roundtrip_converter                                                          2.42ms
[ 87.30%] ··· Running parser_vb.read_csv_thou_vb.time_read_csv_thou_vb                                                                                 25.13ms
[ 87.36%] ··· Running parser_vb.read_csv_vb.time_read_csv_vb                                                                                           20.23ms

...

BENCHMARKS NOT SIGNIFICANTLY CHANGED.
```

The full results are in the attached archive.
[results.tar.gz](https://github.com/pydata/pandas/files/383080/results.tar.gz)
 I added a [test](https://github.com/pydata/pandas/pull/13788/commits/0d0d66026ce231bca23cfe00c686edb4d386f332) that check for either segfault, or memory corruption during parsing.
 @ivannz You pulled in some changes from other PRs that have been merged recently. Can you rebase to fix this? Normally

```
git fetch upstream
git rebase upstream/master
git push -f origin parser_trim_fix
```

should do the trick
 For the asv benchmarks, you will need to compare to current master to see if anything changed. In fact, we just did merge a pull request to clarify how to do this (https://github.com/pydata/pandas/pull/13794):

```
asv continuous upstream/master HEAD -b csv
```
 tests are just like any other parser test
put in io/tests/parser/common.py
 I had to update the stressfulness of the test, because sometimes [**safe_realloc**](https://github.com/pydata/pandas/blob/master/pandas/src/parser/tokenizer.c#L47) just expands the **parser->stream** buffer, which does not corrupt the pointers in **parser->words**.
 Here are the results of **asv continuous -E virtualenv upstream/master HEAD -b csv**:

```
Running 50 total benchmarks (2 commits * 1 environments * 25 benchmarks)
[  0.00%] · For pandas commit hash c092c2b0:
[  2.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv                                                                                                                                330.53ms
[  4.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_datetime                                                                                                                       331.21ms
[  6.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_object                                                                                                                          16.88ms
[  8.00%] ··· Running io_bench.frame_to_csv.time_frame_to_csv                                                                                                                                54.20ms
[ 10.00%] ··· Running io_bench.frame_to_csv2.time_frame_to_csv2                                                                                                                             107.84ms
[ 12.00%] ··· Running io_bench.frame_to_csv_date_formatting.time_frame_to_csv_date_formatting                                                                                                13.89ms
[ 14.00%] ··· Running io_bench.frame_to_csv_mixed.time_frame_to_csv_mixed                                                                                                                   180.47ms
[ 16.00%] ··· Running io_bench.read_csv_from_s3.time_read_nrows                                                                                                                              n/a;...
[ 18.00%] ··· Running io_bench.read_csv_infer_datetime_format_custom.time_read_csv_infer_datetime_format_custom                                                                              11.98ms
[ 20.00%] ··· Running io_bench.read_csv_infer_datetime_format_iso8601.time_read_csv_infer_datetime_format_iso8601                                                                             2.15ms
[ 22.00%] ··· Running io_bench.read_csv_infer_datetime_format_ymd.time_read_csv_infer_datetime_format_ymd                                                                                     2.15ms
[ 24.00%] ··· Running io_bench.read_csv_skiprows.time_read_csv_skiprows                                                                                                                      13.10ms
[ 26.00%] ··· Running io_bench.read_csv_standard.time_read_csv_standard                                                                                                                      11.36ms
[ 28.00%] ··· Running io_bench.write_csv_standard.time_write_csv_standard                                                                                                                    22.73ms
[ 30.00%] ··· Running packers.packers_read_csv.time_packers_read_csv                                                                                                                        187.62ms
[ 32.00%] ··· Running packers.packers_write_csv.time_packers_write_csv                                                                                                                      625.05ms
[ 34.00%] ··· Running parser_vb.read_csv_comment2.time_read_csv_comment2                                                                                                                     26.11ms
[ 36.00%] ··· Running parser_vb.read_csv_default_converter.time_read_csv_default_converter                                                                                                    1.97ms
[ 38.00%] ··· Running parser_vb.read_csv_default_converter_python_engine.time_read_csv_default_converter                                                                                      3.33ms
[ 40.00%] ··· Running parser_vb.read_csv_default_converter_with_decimal.time_read_csv_default_converter_with_decimal                                                                          1.98ms
[ 42.00%] ··· Running parser_vb.read_csv_default_converter_with_decimal_python_engine.time_read_csv_default_converter_with_decimal                                                           10.16ms
[ 44.00%] ··· Running parser_vb.read_csv_precise_converter.time_read_csv_precise_converter                                                                                                    1.91ms
[ 46.00%] ··· Running parser_vb.read_csv_roundtrip_converter.time_read_csv_roundtrip_converter                                                                                                2.67ms
[ 48.00%] ··· Running parser_vb.read_csv_thou_vb.time_read_csv_thou_vb                                                                                                                       23.23ms
[ 50.00%] ··· Running parser_vb.read_csv_vb.time_read_csv_vb                                                                                                                                 22.11ms

[ 50.00%] · For pandas commit hash 690d52cf:
[ 52.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv                                                                                                                                321.53ms
[ 54.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_datetime                                                                                                                       323.61ms
[ 56.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_object                                                                                                                          20.18ms
[ 58.00%] ··· Running io_bench.frame_to_csv.time_frame_to_csv                                                                                                                                53.05ms
[ 60.00%] ··· Running io_bench.frame_to_csv2.time_frame_to_csv2                                                                                                                             110.65ms
[ 62.00%] ··· Running io_bench.frame_to_csv_date_formatting.time_frame_to_csv_date_formatting                                                                                                13.39ms
[ 64.00%] ··· Running io_bench.frame_to_csv_mixed.time_frame_to_csv_mixed                                                                                                                   182.09ms
[ 66.00%] ··· Running io_bench.read_csv_from_s3.time_read_nrows                                                                                                                              n/a;...
[ 68.00%] ··· Running io_bench.read_csv_infer_datetime_format_custom.time_read_csv_infer_datetime_format_custom                                                                              12.03ms
[ 70.00%] ··· Running io_bench.read_csv_infer_datetime_format_iso8601.time_read_csv_infer_datetime_format_iso8601                                                                             2.11ms
[ 72.00%] ··· Running io_bench.read_csv_infer_datetime_format_ymd.time_read_csv_infer_datetime_format_ymd                                                                                     2.19ms
[ 74.00%] ··· Running io_bench.read_csv_skiprows.time_read_csv_skiprows                                                                                                                      13.24ms
[ 76.00%] ··· Running io_bench.read_csv_standard.time_read_csv_standard                                                                                                                      11.19ms
[ 78.00%] ··· Running io_bench.write_csv_standard.time_write_csv_standard                                                                                                                    22.07ms
[ 80.00%] ··· Running packers.packers_read_csv.time_packers_read_csv                                                                                                                        175.88ms
[ 82.00%] ··· Running packers.packers_write_csv.time_packers_write_csv                                                                                                                      638.85ms
[ 84.00%] ··· Running parser_vb.read_csv_comment2.time_read_csv_comment2                                                                                                                     27.93ms
[ 86.00%] ··· Running parser_vb.read_csv_default_converter.time_read_csv_default_converter                                                                                                    1.85ms
[ 88.00%] ··· Running parser_vb.read_csv_default_converter_python_engine.time_read_csv_default_converter                                                                                      3.38ms
[ 90.00%] ··· Running parser_vb.read_csv_default_converter_with_decimal.time_read_csv_default_converter_with_decimal                                                                          1.91ms
[ 92.00%] ··· Running parser_vb.read_csv_default_converter_with_decimal_python_engine.time_read_csv_default_converter_with_decimal                                                           10.13ms
[ 94.00%] ··· Running parser_vb.read_csv_precise_converter.time_read_csv_precise_converter                                                                                                    1.77ms
[ 96.00%] ··· Running parser_vb.read_csv_roundtrip_converter.time_read_csv_roundtrip_converter                                                                                                2.52ms
[ 98.00%] ··· Running parser_vb.read_csv_thou_vb.time_read_csv_thou_vb                                                                                                                       24.98ms
[100.00%] ··· Running parser_vb.read_csv_vb.time_read_csv_vb                                                                                                                                 24.66ms
BENCHMARKS NOT SIGNIFICANTLY CHANGED.
```

Complete results are in this archive:
[results.tar.gz](https://github.com/pydata/pandas/files/383609/results.tar.gz)
 pls add a note in whatsnew / bug fix section
 @jreback , I rewrote the test as you suggested. It is a problem if `nosetests` does not recover from `segfault` when run on it?
 @ivannz the whole point is for it NOT to recover. A segfault is as noticiable as any other error. If you have a test that segfaults, and it is fixed, it will pass.
 I added a note in whatsnew / bug fix section of **`v0.19.0.txt`**.

Here are the latest results of asv continuous -E virtualenv upstream/master HEAD -b csv

```
· Running 50 total benchmarks (2 commits * 1 environments * 25 benchmarks)
[  0.00%] · For pandas commit hash c715ec76:
[  2.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv                                                                                                                                332.52ms
[  4.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_datetime                                                                                                                       336.29ms
[  6.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_object                                                                                                                          17.21ms
[  8.00%] ··· Running io_bench.frame_to_csv.time_frame_to_csv                                                                                                                                53.66ms
[ 10.00%] ··· Running io_bench.frame_to_csv2.time_frame_to_csv2                                                                                                                             107.95ms
[ 12.00%] ··· Running io_bench.frame_to_csv_date_formatting.time_frame_to_csv_date_formatting                                                                                                14.02ms
[ 14.00%] ··· Running io_bench.frame_to_csv_mixed.time_frame_to_csv_mixed                                                                                                                   185.26ms
[ 16.00%] ··· Running io_bench.read_csv_from_s3.time_read_nrows                                                                                                                              n/a;...
[ 18.00%] ··· Running io_bench.read_csv_infer_datetime_format_custom.time_read_csv_infer_datetime_format_custom                                                                              11.95ms
[ 20.00%] ··· Running io_bench.read_csv_infer_datetime_format_iso8601.time_read_csv_infer_datetime_format_iso8601                                                                             2.14ms
[ 22.00%] ··· Running io_bench.read_csv_infer_datetime_format_ymd.time_read_csv_infer_datetime_format_ymd                                                                                     2.17ms
[ 24.00%] ··· Running io_bench.read_csv_skiprows.time_read_csv_skiprows                                                                                                                      13.40ms
[ 26.00%] ··· Running io_bench.read_csv_standard.time_read_csv_standard                                                                                                                      11.43ms
[ 28.00%] ··· Running io_bench.write_csv_standard.time_write_csv_standard                                                                                                                    25.87ms
[ 30.00%] ··· Running packers.packers_read_csv.time_packers_read_csv                                                                                                                        178.49ms
[ 32.00%] ··· Running packers.packers_write_csv.time_packers_write_csv                                                                                                                      629.38ms
[ 34.00%] ··· Running parser_vb.read_csv_comment2.time_read_csv_comment2                                                                                                                     26.11ms
[ 36.00%] ··· Running parser_vb.read_csv_default_converter.time_read_csv_default_converter                                                                                                    1.98ms
[ 38.00%] ··· Running parser_vb.read_csv_default_converter_python_engine.time_read_csv_default_converter                                                                                      3.35ms
[ 40.00%] ··· Running parser_vb.read_csv_default_converter_with_decimal.time_read_csv_default_converter_with_decimal                                                                          2.01ms
[ 42.00%] ··· Running parser_vb.read_csv_default_converter_with_decimal_python_engine.time_read_csv_default_converter_with_decimal                                                           10.10ms
[ 44.00%] ··· Running parser_vb.read_csv_precise_converter.time_read_csv_precise_converter                                                                                                    1.88ms
[ 46.00%] ··· Running parser_vb.read_csv_roundtrip_converter.time_read_csv_roundtrip_converter                                                                                                2.69ms
[ 48.00%] ··· Running parser_vb.read_csv_thou_vb.time_read_csv_thou_vb                                                                                                                       22.01ms
[ 50.00%] ··· Running parser_vb.read_csv_vb.time_read_csv_vb                                                                                                                                 25.23ms

[ 50.00%] · For pandas commit hash 98c5b88d:
[ 52.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv                                                                                                                                319.35ms
[ 54.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_datetime                                                                                                                       318.53ms
[ 56.00%] ··· Running gil.nogil_read_csv.time_nogil_read_csv_object                                                                                                                          18.57ms
[ 58.00%] ··· Running io_bench.frame_to_csv.time_frame_to_csv                                                                                                                                55.03ms
[ 60.00%] ··· Running io_bench.frame_to_csv2.time_frame_to_csv2                                                                                                                             103.54ms
[ 62.00%] ··· Running io_bench.frame_to_csv_date_formatting.time_frame_to_csv_date_formatting                                                                                                13.35ms
[ 64.00%] ··· Running io_bench.frame_to_csv_mixed.time_frame_to_csv_mixed                                                                                                                   180.89ms
[ 66.00%] ··· Running io_bench.read_csv_from_s3.time_read_nrows                                                                                                                              n/a;...
[ 68.00%] ··· Running io_bench.read_csv_infer_datetime_format_custom.time_read_csv_infer_datetime_format_custom                                                                              11.53ms
[ 70.00%] ··· Running io_bench.read_csv_infer_datetime_format_iso8601.time_read_csv_infer_datetime_format_iso8601                                                                             2.05ms
[ 72.00%] ··· Running io_bench.read_csv_infer_datetime_format_ymd.time_read_csv_infer_datetime_format_ymd                                                                                     2.09ms
[ 74.00%] ··· Running io_bench.read_csv_skiprows.time_read_csv_skiprows                                                                                                                      12.41ms
[ 76.00%] ··· Running io_bench.read_csv_standard.time_read_csv_standard                                                                                                                      11.40ms
[ 78.00%] ··· Running io_bench.write_csv_standard.time_write_csv_standard                                                                                                                    22.19ms
[ 80.00%] ··· Running packers.packers_read_csv.time_packers_read_csv                                                                                                                        175.62ms
[ 82.00%] ··· Running packers.packers_write_csv.time_packers_write_csv                                                                                                                      603.39ms
[ 84.00%] ··· Running parser_vb.read_csv_comment2.time_read_csv_comment2                                                                                                                     25.62ms
[ 86.00%] ··· Running parser_vb.read_csv_default_converter.time_read_csv_default_converter                                                                                                    1.79ms
[ 88.00%] ··· Running parser_vb.read_csv_default_converter_python_engine.time_read_csv_default_converter                                                                                      3.26ms
[ 90.00%] ··· Running parser_vb.read_csv_default_converter_with_decimal.time_read_csv_default_converter_with_decimal                                                                          1.83ms
[ 92.00%] ··· Running parser_vb.read_csv_default_converter_with_decimal_python_engine.time_read_csv_default_converter_with_decimal                                                           10.13ms
[ 94.00%] ··· Running parser_vb.read_csv_precise_converter.time_read_csv_precise_converter                                                                                                    1.74ms
[ 96.00%] ··· Running parser_vb.read_csv_roundtrip_converter.time_read_csv_roundtrip_converter                                                                                                2.44ms
[ 98.00%] ··· Running parser_vb.read_csv_thou_vb.time_read_csv_thou_vb                                                                                                                       21.64ms
[100.00%] ··· Running parser_vb.read_csv_vb.time_read_csv_vb                                                                                                                                 24.61ms

BENCHMARKS NOT SIGNIFICANTLY CHANGED.
```
 I am not sure how to concisely put it for a general user, but whether the bug occurs, and its severity (a segfault or memory corruption) depends on the state of the system memory allocator. Specifically it is the result of the interplay between the inner logics of **realloc** implementation and the availability of memory regions adjacent to the **realloced** buffer:
- sometimes **realloc** just expands the buffer, leaving its starting address intact -- in this case **no bug takes place**;
- other times **realloc** moves a buffer to a new location, and in this case there are two alternatives:
  1. the old block is invalidated, but is still accessible to the parser, in which case the tokenized strings in **parser->words** (which is a char\* array) become **corrupted**;
  2. the old block is invalidated and reclaimed by the OS, in which case the process **crashes with a segfault**.

The first alternative manifests itself in **NaNs**, or otherwise unacceptable **ASCII** characters (beyond 128) in fields where no such thing is possible by design (BCD or textual decimal fields).

Every time the unpatched `parser_trim_buffers` is invoked by either [parser.pyx:_read_low_memory()](https://github.com/pydata/pandas/blob/master/pandas/parser.pyx#L851) or [parser.pyx:_read_rows()](https://github.com/pydata/pandas/blob/master/pandas/parser.pyx#L902) there is a risk of this undefined behaviour.
 ok @ivannz just say that on large chunking _may_ segfault then.
 Is there a way to cancel all but the most recent Travis job related to this PR (13788)?

The most recent is this one: **`job # 21105`**
 @ivannz I canceled some builds (but there are some other PRs in the queue as well, so will take some time anyway). Only solution is to not push a minor commit yet if you know you are going to push another one (or to put 'ci skip').  
BTW, you can set up travis for your own fork, which often gives you much quicker feedback, and there you yourself have control over the builds (eg to cancel them).
 Thank you, @jorisvandenbossche !
 I significantly improved the clarity and logic of the segfault/corruption test: now it is a bit more clear why and in what case the bug occurs.
 @jorisvandenbossche , could you cancel Travis CI job #21105, please.
 thanks!
 I tried to compile master branch on Windows VS2015 and it failed with the errors:

```
pandas/src/parser/tokenizer.c(1260): error C2036: 'void *': unknown size
pandas/src/parser/tokenizer.c(1264): error C2036: 'void *': unknown size
```

So I guess `newptr` in these two lines should be cast to `char *`.
 can u make a new issue? and fix if u can
 OK. I'll later submit the fix.
