DataFrame.reset_index(inplace=True) with column names collision brakes dataframe

[s-wakaba]

Code Sample, a copy-pastable example if possible

import pandas as pd
import numpy as np

a = pd.DataFrame(
    np.random.random(12).reshape([4,3]),
    columns = ['A', 'B', 'C'],
    index = pd.MultiIndex.from_product([['p','q'],['x','y']], names=['A','D']),
)

print(a)
#             A         B         C
# A D                              
# p x  0.809155  0.181919  0.957133
#   y  0.625364  0.802854  0.065737
# q x  0.288116  0.570645  0.944983
#   y  0.926358  0.684897  0.724123

try:
    a.reset_index(inplace=True)
except ValueError as e:
    print(e) # cannot insert A, already exists

print(a)
#      D         A         B         C
# A D                                 
# p x  x  0.809155  0.181919  0.957133
#   y  y  0.625364  0.802854  0.065737
# q x  x  0.288116  0.570645  0.944983
#   y  y  0.926358  0.684897  0.724123

Problem description

when there are columns with the same name in data-body and multi-index on calling DataFrame.reset_index(), ValueError is thrown. however, if inplace=True option is specified, this operation is not atomic and leaves DataFrame itself incomplete.
I think keeping original data is better and consistent when such exceptions are occurred.

Output of pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.1.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-862.3.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.2
pytest: 4.0.2
pip: 10.0.1
setuptools: 39.0.1
Cython: 0.29.2
numpy: 1.15.4
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 7.2.0
sphinx: 1.8.2
patsy: 0.5.1
dateutil: 2.7.5
pytz: 2018.7
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 3.0.2
openpyxl: 2.5.12
xlrd: 1.2.0
xlwt: 1.3.0
xlsxwriter: 1.1.2
lxml.etree: 4.2.5
bs4: 4.6.3
html5lib: 1.0.1
sqlalchemy: 1.2.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

[WillAyd]

We are generally moving support away from inplace operations for reasons like this but you are welcome to take a look if you have an idea on how to fix