Description
-
I have checked that this issue has not already been reported.
- I think so, it's a bit hard to search for though. Nothing under concat and setindex
-
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.
Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.
Code Sample, a copy-pastable example
import pandas as pd, numpy as np
from string import ascii_lowercase
def setitem(x, x_cols, df):
new = pd.DataFrame(index=df.index)
new[x_cols] = x
new[df.columns] = df
return new
def concat(x, x_cols, df):
return pd.concat(
[
pd.DataFrame(x, columns=x_cols, index=df.index),
df,
],
axis=1,
)
x = np.ones((1000, 10))
x_col = list(ascii_lowercase[:10])
df = pd.DataFrame(
{
"str": np.random.choice(np.array(list(ascii_lowercase)), size=1000),
"int": np.arange(1000, dtype=int),
}
)
%timeit setitem(x, x_col, df)
# 3.78 ms ± 193 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
%timeit concat(x, x_col, df)
# 306 µs ± 9.29 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)Problem description
This seems unintuitive from a performance perspective. I would assume that these would be close to equivalent. The setitem implementation might even be expected to have better performance due to less allocation.
While this is a stripped down example, the use case is building a dataframe to return from a function. Making a dataframe, then adding columns seemed like the natural idiom here.
Output of pd.show_versions()
INSTALLED VERSIONS
------------------
commit : 67a3d4241ab84419856b84fc3ebc9abcbe66c6b3
python : 3.8.5.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Thu Oct 29 22:56:45 PDT 2020; root:xnu-6153.141.2.2~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.4
numpy : 1.19.4
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.4
setuptools : 50.3.2
Cython : 0.29.21
pytest : 6.1.2
hypothesis : None
sphinx : 3.2.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.19.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.4
fastparquet : None
gcsfs : None
matplotlib : 3.3.3
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 2.0.0
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.5.4
sqlalchemy : 1.3.18
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.16.1
xlrd : 1.2.0
xlwt : None
numba : 0.51.2