Wrong result for float32 Series when using bottleneck
#### Minimal example

Requires bottleneck, numpy and pandas to be installed:

```python
>>> import numpy as np
>>> import pandas as pd
>>> import bottleneck as bn
>>> data = np.ones(2**25, dtype=np.float32)
>>> pd.Series(data).mean()  # wrong
0.5
>>> bn.nanmean(data)  # wrong
0.5
>>> data.mean()  # correct
1.0
```

#### Problem description

The `mean()` of large float32 Series is wrong when [bottleneck](https://github.com/kwgoodman/bottleneck/) is used. Uninstalling bottleneck or using float64 is a valid workaround. xarray is or has been affected too, see pydata/xarray#1346. 

<s>Bottleneck's documentation explicitly mentions that [no error is raised in case of an overflow](https://kwgoodman.github.io/bottleneck-doc/reference.html?highlight=overflow#bottleneck.nanmean), not sure if this is still to be considered as bug in bottleneck.</s> Anyhow since it seems quite severe, I want to raise attention here too.

**Update:** This is not an overflow, it's a numerical error (which is very high because bottleneck does not use [pairwise summation](https://en.wikipedia.org/wiki/Pairwise_summation)).

[Bottleneck's implementation of mean()](https://github.com/kwgoodman/bottleneck/blob/master/bottleneck/src/reduce_template.c#L162).

#### Related issues

* same thing in xarray: pydata/xarray#1346
* same thing in aospy: spencerahill/aospy#217
* similar bug in pandas with bottleneck, but related to int not float: pandas-dev/pandas#15453  and kwgoodman/bottleneck#163
* another very similar but older bug in pandas with bottleneck but related to int not float: pandas-dev/pandas#6915 kwgoodman/bottleneck#83
* something different, not to be confused - race conditions when reading netcdf files: dask/dask#2095
* probably not related, but who knows: kwgoodman/bottleneck#164


#### Expected Output

```python
>>> data = np.ones(2**25, dtype=np.float32)
>>> pd.Series(data).mean()
1.0
```

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

<details>

```bash
$ pip3 freeze 
Bottleneck==1.2.1
numpy==1.16.1
pandas==0.24.1
...
```

```python
>>> pd.show_versions()                                                                                           
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.7.final.0
python-bits: 64
OS: Linux
OS-release: 4.18.0-13-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.1
pytest: None
pip: 19.0.2
setuptools: 40.8.0
Cython: None
numpy: 1.16.1
scipy: None
pyarrow: None
xarray: 0.11.3
IPython: 7.2.0
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2018.9
blosc: None
bottleneck: 1.2.1
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
```
</details>
