Closed
Description
- :meth:`DataFrame.apply` and :meth:`DataFrame.applymap` now evaluates first row/column only once (:issue:`31620`, :issue:`30815`, :issue:`33879`).
.. ipython:: python
df = pd.DataFrame({'a': [1, 2], 'b': [3, 6]})
def func(row):
print(row)
return row
*Previous behavior*:
.. code-block:: ipython
In [4]: df.apply(func, axis=1)
a 1
b 3
Name: 0, dtype: int64
a 1
b 3
Name: 0, dtype: int64
a 2
b 6
Name: 1, dtype: int64
Out[4]:
a b
0 1 3
1 2 6
*New behavior*:
.. ipython:: python
df.apply(func, axis=1)
some example....
def foo(row):
status = row.get("status")
print(status)
status = True if status==1 else False
row["status"] = status
return row
df = pd.DataFrame([{"name":"bob", "status":1}])
df.apply(foo, axis=1)
>>>>>>>> output:
1
TrueProblem description
today, I have a problem that df.apply(foo) will run twice at the first row like old issue #2936.
I read a lot of explanations, but still can't find some help. As I wrote above, when df just have 1 row and then apply function will run twice at this row lead to print diffierent values.
(It just modified my original value "1" to "True", but it confused me a lot...)
I am wandering how to handle this issue, and is this a pandas bug?
thanks a lot~~