Description
Code Sample, a copy-pastable example if possible
import pandas as pd
index = pd.date_range(start='2020', periods=5)
df = pd.DataFrame([[1, 2, 3]] * 5, columns=['a', 'b', 'c'], index=index)
series = pd.Series([10, 20, 30, 40, 50], index=index)
print(df + series)| 2020-01-01 00:00:00 | 2020-01 02 00:00:00 | 2020-01-03 00:00:00 | 2020-01-04 00:00:00 | 2020-01-05 00:00:00 | a | b | c | |
|---|---|---|---|---|---|---|---|---|
| 2020-01-01 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 2020-01-02 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 2020-01-03 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 2020-01-04 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
| 2020-01-05 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN |
Problem description
According to the docs (https://pandas.pydata.org/pandas-docs/stable/getting_started/dsintro.html#data-alignment-and-arithmetic):
When doing an operation between DataFrame and Series, the default behavior is to align the Series index on the DataFrame columns, thus broadcasting row-wise
In the special case of working with time series data, if the DataFrame index contains dates, the broadcasting will be column-wise
It seems to me that in both cases now the broadcasting is row-wise.
Is this an expected change for pandas 1.0.0 (I hope not - I never saw any FutureWarnings about it)? If so, the docs (and the examples) must be updated.
The same happens for the operators -, /, *, %
Expected Output
Not sure if this is the expected output anymore, but it used to be equivalent to:
df.add(series, axis=0)| a | b | c | |
|---|---|---|---|
| 2020-01-01 | 11 | 12 | 13 |
| 2020-01-02 | 21 | 22 | 23 |
| 2020-01-03 | 31 | 32 | 33 |
| 2020-01-04 | 41 | 42 | 43 |
| 2020-01-05 | 51 | 52 | 53 |
Although I can't replicate it, I'm pretty sure this was the behaviour until pandas 0.25.3
Output of pd.show_versions()
INSTALLED VERSIONS
commit : None
python : 3.7.6.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 1.0.0
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 45.1.0.post20200127
Cython : 0.29.14
pytest : 5.3.4
hypothesis : 4.54.2
sphinx : 2.3.1
blosc : None
feather : None
xlsxwriter : 1.2.7
lxml.etree : 4.4.2
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.11.1
pandas_datareader: None
bs4 : 4.8.2
bottleneck : 1.3.1
fastparquet : None
gcsfs : None
lxml.etree : 4.4.2
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : None
pytables : None
pytest : 5.3.4
pyxlsb : None
s3fs : 0.4.0
scipy : 1.3.2
sqlalchemy : 1.3.13
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.7
numba : 0.47.0