BUG: Empty dataframe with .astype raises Exception

[eliasmistler]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

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Code Sample, a copy-pastable example

import pandas as pd

pd.DataFrame([]).astype({})

Problem description

I've got some generic code handling a large number of DataFrames, and among other things, forcing the data types of certain columns. Some of these DataFrames can be empty - however, that should not stop the calculations.

My expectation would be that I can run any operation that is conceptually a nop on a DataFrame without causing an issue. In this case, I can run .astype({}) on any DataFrame (empty or not) that has columns - so far, so good. However, on a DataFrame with 0 columns, the function fails with a ValueError: "No objects to concatenate"

Expected Output

Empty DataFrame

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None
python : 3.7.4.final.0
python-bits : 64
OS : Darwin
OS-release : 19.5.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_GB.UTF-8
pandas : 1.0.4
numpy : 1.18.5
pytz : 2020.1
dateutil : 2.8.1
pip : 19.3.1
setuptools : 42.0.2
Cython : None
pytest : 5.4.3
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 7.15.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pytest : 5.4.3
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 1.3.17
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
numba : None

[simonjayhawkins]

Thanks @eliasmistler for the report. I believe this is a duplicate of #33113 so closing. This is fixed in pandas 1.1.0 (released yesterday)

>>> pd.__version__
'1.2.0.dev0+5.g2c3fa22c0'
>>>
>>> pd.DataFrame([]).astype({})
Empty DataFrame
Columns: []
Index: []
>>>