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martinholmer opened this issue Jan 2, 2018 · 2 comments
Closed

Still getting ignored error after upgrading to panda 0.22.0 #19037

martinholmer opened this issue Jan 2, 2018 · 2 comments
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@martinholmer
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martinholmer commented Jan 2, 2018

Code Sample, a copy-pastable example if possible

        # 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). 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
>>>

@jreback
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jreback commented Jan 2, 2018

this is pushed in 0.23.0. (was called 0.22.0 at some point, but we released a single change in 0.22.0).

@jreback jreback closed this as completed Jan 2, 2018
@jreback jreback added the Duplicate Report Duplicate issue or pull request label Jan 2, 2018
@jreback jreback added this to the No action milestone Jan 2, 2018
@martinholmer
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@jreback, Thanks for the quick update on pandas release plans.

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