Closed
Description
Code Sample, a copy-pastable example if possible
Python 3.6.7 | packaged by conda-forge | (default, Nov 21 2018, 03:09:43)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.2.0 -- An enhanced Interactive Python. Type '?' for help.
In [1]: import pandas as pd
In [2]: df = pd.DataFrame({('A_%d' % i): [i] for i in range(5)})
In [3]: df
Out[3]:
A_0 A_1 A_2 A_3 A_4
0 0 1 2 3 4
In [4]: df.to_dict('records')
Out[4]: [{'A_0': 0, 'A_1': 1, 'A_2': 2, 'A_3': 3, 'A_4': 4}]
In [5]: df_bad = pd.DataFrame({str(i): [i] for i in range(5)})
In [6]: df_bad
Out[6]:
0 1 2 3 4
0 0 1 2 3 4
In [7]: df_bad.to_dict('records')
Out[7]: [{'_0': 0, '_1': 1, '_2': 2, '_3': 3, '_4': 4}]
Problem description
While looking into #24939 I noticed that an _ is added before the column name in the output of to_dict('records') when the column names are integer-strings. I believe this behavior is new with 0.24.0, but I'm not certain.
Conda info
(pandas-0.24) 15:04:03 ~
§ conda list
# packages in environment at /home/evan/.conda/envs/pandas-0.24:
#
# Name Version Build Channel
backcall 0.1.0 py_0 conda-forge
blas 1.0 mkl
ca-certificates 2018.11.29 ha4d7672_0 conda-forge
certifi 2018.11.29 py36_1000 conda-forge
decorator 4.3.0 py_0 conda-forge
intel-openmp 2019.1 144
ipython 7.2.0 py36h24bf2e0_1000 conda-forge
ipython_genutils 0.2.0 py_1 conda-forge
jedi 0.13.2 py36_1000 conda-forge
libffi 3.2.1 hf484d3e_1005 conda-forge
libgcc-ng 7.3.0 hdf63c60_0 conda-forge
libgfortran-ng 7.2.0 hdf63c60_3 conda-forge
libstdcxx-ng 7.3.0 hdf63c60_0 conda-forge
mkl 2019.1 144
mkl_fft 1.0.10 py36h14c3975_1 conda-forge
mkl_random 1.0.2 py36h637b7d7_2 conda-forge
ncurses 6.1 hf484d3e_1002 conda-forge
numpy 1.15.4 py36h7e9f1db_0
numpy-base 1.15.4 py36hde5b4d6_0
openssl 1.0.2p h14c3975_1002 conda-forge
pandas 0.24.0 py36hf484d3e_0 conda-forge
parso 0.3.1 py_0 conda-forge
pexpect 4.6.0 py36_1000 conda-forge
pickleshare 0.7.5 py36_1000 conda-forge
pip 18.1 py36_1000 conda-forge
prompt_toolkit 2.0.7 py_0 conda-forge
ptyprocess 0.6.0 py36_1000 conda-forge
pygments 2.3.1 py_0 conda-forge
python 3.6.7 hd21baee_1001 conda-forge
python-dateutil 2.7.5 py_0 conda-forge
pytz 2018.9 py_0 conda-forge
readline 7.0 hf8c457e_1001 conda-forge
setuptools 40.6.3 py36_0 conda-forge
six 1.12.0 py36_1000 conda-forge
sqlite 3.26.0 h67949de_1000 conda-forge
tk 8.6.9 h84994c4_1000 conda-forge
traitlets 4.3.2 py36_1000 conda-forge
wcwidth 0.1.7 py_1 conda-forge
wheel 0.32.3 py36_0 conda-forge
xz 5.2.4 h14c3975_1001 conda-forge
zlib 1.2.11 h14c3975_1004 conda-forge
(pandas-0.24) 15:04:04 ~
§ conda info
active environment : pandas-0.24
active env location : /home/evan/.conda/envs/pandas-0.24
shell level : 1
user config file : /home/evan/.condarc
populated config files :
conda version : 4.5.12
conda-build version : 3.17.6
python version : 3.7.2.final.0
base environment : /opt/Miniconda3 (read only)
channel URLs : https://repo.anaconda.com/pkgs/main/linux-64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/free/linux-64
https://repo.anaconda.com/pkgs/free/noarch
https://repo.anaconda.com/pkgs/r/linux-64
https://repo.anaconda.com/pkgs/r/noarch
https://repo.anaconda.com/pkgs/pro/linux-64
https://repo.anaconda.com/pkgs/pro/noarch
package cache : /opt/Miniconda3/pkgs
/home/evan/.conda/pkgs
envs directories : /home/evan/.conda/envs
/opt/Miniconda3/envs
platform : linux-64
user-agent : conda/4.5.12 requests/2.19.1 CPython/3.7.2 Linux/4.20.3-arch1-1-ARCH antergos/ glibc/2.28
UID:GID : 1000:985
netrc file : None
offline mode : False
Output of pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.7.final.0
python-bits: 64
OS: Linux
OS-release: 4.20.3-arch1-1-ARCH
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
pandas: 0.24.0
pytest: None
pip: 18.1
setuptools: 40.6.3
Cython: None
numpy: 1.15.4
scipy: None
pyarrow: None
xarray: None
IPython: 7.2.0
sphinx: None
patsy: None
dateutil: 2.7.5
pytz: 2018.9
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None