Series.combine() with a scalar only works if function is compatible with (vec, scalar) operation · Issue #21248 · pandas-dev/pandas (original) (raw)

Code Sample, a copy-pastable example if possible

In [1]: import pandas as pd

In [2]: s = pd.Series([i*10 for i in range(5)]) ...: s ...: Out[2]: 0 0 1 10 2 20 3 30 4 40 dtype: int64

In [3]: s.combine(3, lambda x,y: x + y) Out[3]: 0 3 1 13 2 23 3 33 4 43 dtype: int64

In [4]: s.combine(22, lambda x,y: min(x,y))

ValueError Traceback (most recent call last) in () ----> 1 s.combine(22, lambda x,y: min(x,y))

C:\Anaconda3\lib\site-packages\pandas\core\series.py in combine(self, other, func, fill_value) 2240 new_index = self.index 2241 with np.errstate(all='ignore'): -> 2242 new_values = func(self._values, other) 2243 new_name = self.name 2244 return self._constructor(new_values, index=new_index, name=new_name)

in (x, y) ----> 1 s.combine(22, lambda x,y: min(x,y))

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

In [5]: s.combine(pd.Series([22,22,22,22,22]), lambda x,y: min(x,y)) Out[5]: 0 0 1 10 2 20 3 22 4 22 dtype: int64

Problem description

In the case of using Series.combine() with a scalar argument, it only works if the corresponding function func supports func(Series, scalar). Implementation should always use an element-by-element implementation. The results of [3] and [5] are expected, but [4] should still work.

Expected Output

For [4], it should look like the output of [5] above.

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.4.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: 0.23.0
pytest: 3.3.2
pip: 9.0.1
setuptools: 38.4.0
Cython: 0.27.3
numpy: 1.14.0
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.6.6
patsy: 0.5.0
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.1.2
openpyxl: 2.4.10
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.1
pymysql: 0.7.11.None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None