TypeError in pandas._libs.tslibs.period._ordinal_from_fields

[aabdullah-bos]

Using pandas 0.23.3 I receive a TypeErorr when running the following code:

import pandas
ts = pandas.date_range('2017-01-01', '2018-01-01', freq='B')
months = ts.map(lambda x: pandas.Period(year=x.year, month=x.month, freq='M'))
# Screen output even though operation succeeds.
# TypeError                                 Traceback (most recent call last)
# TypeError: an integer is required
# Exception TypeError: 'an integer is required' in 'pandas._libs.tslibs.period._ordinal_from_fields' ignored

Oddly, enough the operation succeeds, months has the correct data.

Expected Output

I would expect no output to stderr or stdout, just the correct assignment of the map operation. This is more of an annoyance than anything else.

Output of pd.show_versions()

pandas.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.15.final.0
python-bits: 64
OS: Darwin
OS-release: 17.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.23.3
pytest: None
pip: 18.0
setuptools: 40.0.0
Cython: None
numpy: 1.13.0
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 5.7.0
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: 3.4.4
numexpr: 2.6.6
feather: None
matplotlib: 2.2.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: 1.2.10
pymysql: 0.9.2
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[paste the output of pd.show_versions() here below this line]

[WillAyd]

Hmm strange indeed. Thanks for the report - investigation and PRs are always welcome!

[mosrosem]

I couldn't replicate the error. This error message doesn't appear when I run it.

[WillAyd]

@mosrosem just to be clear it's not actually throwing the error (at least for me) but rather printing to STDOUT and continuing along as planned. If it's not doing for you can you post your pd.show_versions?

[jbrockmendel]

It looks like you've stumbled on something genuinely weird. Period.__new__ is calling _ordinal_from_fields, and on the first call (but not in subsequent calls), the year and month arguments are both Int64Index objects. So it looks like DatetimeIndex.map is doing doing something "creative".

@WillAyd any idea who to CC on this?

Update Actually not such a mystery, just weird. DatetimeIndexOpsMixin.map:

    # Try to run function on index first, and then on elements of index
    # Especially important for group-by functionality
    def map(self, f):
        try:
            result = f(self)

            # Try to use this result if we can
            if isinstance(result, np.ndarray):
                result = Index(result)

            if not isinstance(result, Index):
                raise TypeError('The map function must return an Index object')
            return result
        except Exception:
            return self.astype(object).map(f)

[WillAyd]

@jbrockmendel I was thinking of CC'ing you :-) looks like you might be on to something