Pandas.items in Python2 vs Python3

[lewisacidic]

Inconsistency between python2 and 3 - python2 has no items method (but does have iteritems). Shouldn't items and iteritems be the same?

Code Sample, a copy-pastable example if possible

import pandas as pd
import string
ser = pd.Series(np.arange(10), index=list(string.ascii_letters[:10]))
print(ser.items())

Expected Output

<zip object at 0x11dc1f6c8>

python 2:
AttributeError: 'Series' object has no attribute 'items'

output of pd.show_versions() (python2)

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Darwin
OS-release: 15.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8

pandas: 0.18.1
nose: None
pip: 8.1.2
setuptools: 23.0.0
Cython: None
numpy: 1.10.4
scipy: 0.17.0
statsmodels: None
xarray: None
IPython: 5.0.0
sphinx: None
patsy: None
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: None
tables: 3.2.2
numexpr: 2.5.2
matplotlib: 1.5.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None

[jreback]

Series has never had an .items method IIRC, which by-definition is NOT lazy. So I suppose this could be added for compat (as PY3 DOES have an .items method).

[jreback]

if you want to submit a PR and see if anything breaks that would be great.

[lewisacidic]

I thought .items (at least for dict) was lazy in 3 and not in 2 (iteritems doesn't exist in 3).

The implementation is currently:

class Series(...
    def iteritems(self):
        """
        Lazily iterate over (index, value) tuples
        """
        return zip(iter(self.index), iter(self))

    if compat.PY3:  # pragma: no cover
        items = iteritems

I would simply propose removing the compat check (or not having it at all).

[jreback]

@richlewis42 as I said, you can try removing it and see what happens (you prob also need to fix a test)

[shoyer]

This seems like a good idea to me. Can we do the same for DataFrame.items as well?