DataFrame.from_dict(OrderedDict(items),...) not a proper replacement for from_items(items,...)

[PatrickDRusk]

Code Sample

import pandas
from collections import OrderedDict
def test_from_dict_replacing_from_items_with_duplicates():
    rows = [(1, (2,)), (1, (2,))]
    df1 = pandas.DataFrame.from_items(rows, columns=('a', ), orient='index')
    df2 = pandas.DataFrame.from_dict(OrderedDict(rows), columns=('a', ), orient='index')
    pandas.testing.assert_frame_equal(df1, df2)

Problem description

The deprecation warning in 0.23.4 indicates that from_items(items,...) should be changed to from_dict(OrderedDict(items).... But that doesn't work in cases where there would be duplicates in the index. The above is a test that would fail.

This would make it burdensome for developers to test all the scenarios in which they have used from_items() to change them to from_dict.

It might be worth noting that the columns parameter was not allowed on from_dict() prior to 0.23, and that would further complicate adapting code away from from_items().

I recommend against this deprecation.

Expected Output

The above test would be expected to succeed.

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.7.0.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: en_US.UTF-8

pandas: 0.23.4
pytest: 3.8.0
pip: 18.0
setuptools: 40.2.0
Cython: 0.28.5
numpy: 1.14.5
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.5.0
sphinx: None
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 2.2.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: 1.2.11
pymysql: 0.9.2
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[PatrickDRusk]

If this deprecation is going to happen, the warning message should probably change its recommendation to something more reliable. I believe this would work:

pandas.DataFrame([i[1] for i in items], index=[i[0] for i in items], columns=columns)

[mroeschke]

Looks like from_items has already been removed. Not sure if there is any additional tasks to be done here. Closing