Still getting ignored error after upgrading to panda 0.22.0
#### Code Sample, a copy-pastable example if possible

```python
        # create grouped Pandas DataFrame
        gpdf = pdf.groupby('bins', as_index=False)
        # create difference table statistics from gpdf in a new DataFrame
        diffs_without_sums = stat_dataframe(gpdf)
        # calculate sums row
        row = get_sums(diffs_without_sums)[diffs_without_sums.columns]
        row['mean'] = 0
        if row['count'] > 0:
            row['mean'] = row['tot_change'] / row['count']
        row['perc_cut'] = sums_perc_cut
        row['perc_inc'] = sums_perc_inc
        row['share_of_change'] = 1.0  # avoid rounding error
        diffs = diffs_without_sums.append(row)
        # append top-decile-detail rows
        if groupby == 'weighted_deciles':
            pdf = gpdf.get_group(10)  # top decile as its own DataFrame
            pdf = add_quantile_bins(copy.deepcopy(pdf), income_measure, 10)
            # TODO: following statement generates this IGNORED error:
            # ValueError: Buffer dtype mismatch,
            #             expected 'Python object' but got 'long'
            # Exception ValueError: "Buffer dtype mismatch,
            #              expected 'Python object' but got 'long'"
            #              in 'pandas._libs.lib.is_bool_array' ignored
            #                                                  ^^^^^^^
            # It is hoped that Pandas PR#17841, which is scheduled for <================
            # inclusion in Pandas version 0.22.0 (Jan 2018), will fix this. <===========
            pdf['bins'].replace(to_replace=[1, 2, 3, 4, 5],
                                value=[0, 0, 0, 0, 0], inplace=True)
            pdf['bins'].replace(to_replace=[6, 7, 8, 9],
                                value=[1, 1, 1, 1], inplace=True)
            pdf['bins'].replace(to_replace=[10], value=[2], inplace=True)
            gpdf = pdf.groupby('bins', as_index=False)
            sdf = stat_dataframe(gpdf)
            diffs = diffs.append(sdf, ignore_index=True)
        return diffs
```
#### Problem description

Get **ignored** error message described in code fragment above, which is causing Tax-Calculator users confusion (see, for example, [Tax-Calculator issue 1799](https://github.com/open-source-economics/Tax-Calculator/issues/1799)).   If there is an error, why does Pandas ignore it?  If there is not an error, why does Pandas print an error message and then ignore it?  Based on the conversation in #18252, we had expected this error message to go away after we upgraded to 0.22.0, but that doesn't seem to be the case.

#### Expected Output

I would expect a **non-ignored** error message that stops program execution if I am using pandas incorrectly.  
Or I would expect no error message if I am using pandas correctly.
But I get neither.

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

iMac2:tax-calculator mrh$ python 
Python 2.7.14 |Anaconda custom (64-bit)| (default, Oct  5 2017, 02:28:52) 
[GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
`>>>` import pandas as pd
`>>>` pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.14.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.22.0
pytest: 3.2.1
pip: 9.0.1
setuptools: 36.5.0.post20170921
Cython: 0.26.1
numpy: 1.13.3
scipy: 0.19.1
pyarrow: None
xarray: None
IPython: 5.4.1
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.1.0
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.2.0
xlsxwriter: 1.0.2
lxml: 4.1.0
bs4: 4.6.0
html5lib: 0.999999999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
`>>>`
