MemoryError, Python 32bit, Error when reading a large file 
#### Code Sample

```python
import pandas as pd

path = 'dataset.gz'
df = pd.read_csv(path, sep = ';', compression = 'gzip')
print(sys.getsizeof(df ) / 1024 / 1024, " Mb")
```

#### Code Output (Problem)

```
---------------------------------------------------------------------------
MemoryError                               Traceback (most recent call last)
<ipython-input-13-b36dac541c6a> in <module>
      2 
      3 path = 'dataset.gz'
----> 4 df = pd.read_csv(path, sep = ';', compression = 'gzip')
      5 print(sys.getsizeof(df) / 1024 / 1024, " Mb")

~\AppData\Local\Programs\Python\Python38-32\lib\site-packages\pandas\io\parsers.py in parser_f(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision)
    674         )
    675 
--> 676         return _read(filepath_or_buffer, kwds)
    677 
    678     parser_f.__name__ = name

~\AppData\Local\Programs\Python\Python38-32\lib\site-packages\pandas\io\parsers.py in _read(filepath_or_buffer, kwds)
    452 
    453     try:
--> 454         data = parser.read(nrows)
    455     finally:
    456         parser.close()

~\AppData\Local\Programs\Python\Python38-32\lib\site-packages\pandas\io\parsers.py in read(self, nrows)
   1131     def read(self, nrows=None):
   1132         nrows = _validate_integer("nrows", nrows)
-> 1133         ret = self._engine.read(nrows)
   1134 
   1135         # May alter columns / col_dict

~\AppData\Local\Programs\Python\Python38-32\lib\site-packages\pandas\io\parsers.py in read(self, nrows)
   2035     def read(self, nrows=None):
   2036         try:
-> 2037             data = self._reader.read(nrows)
   2038         except StopIteration:
   2039             if self._first_chunk:

pandas\_libs\parsers.pyx in pandas._libs.parsers.TextReader.read()

pandas\_libs\parsers.pyx in pandas._libs.parsers.TextReader._read_low_memory()

pandas\_libs\parsers.pyx in pandas._libs.parsers.TextReader._read_rows()

pandas\_libs\parsers.pyx in pandas._libs.parsers.TextReader._convert_column_data()

pandas\_libs\parsers.pyx in pandas._libs.parsers.TextReader._convert_tokens()

pandas\_libs\parsers.pyx in pandas._libs.parsers.TextReader._convert_with_dtype()

pandas\_libs\parsers.pyx in pandas._libs.parsers._try_int64()

MemoryError: Unable to allocate 1.00 MiB for an array with shape (131072,) and data type int64
```

#### Problem description

The pandas `read_csv` function got a memory error, this shouldn't happen (I have a 16 Gb RAM computer).
Meanwhile, I tried another python (conda) 3.7.4 which works fine but using pandas 0.25.1, it's currently my workaround.

#### Expected Output

From my workaround (Python 3.7.4, conda, pandas 0.25.1)

```
625.6165533065796  Mb
```

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.2.final.0
python-bits      : 32
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : fr_FR.cp1252

pandas           : 1.0.1
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 41.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : 0.4.0
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None
None
</details>
