pandas 将具有多个参数的函数传递给 DataFrame.apply
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Passing a function with multiple arguments to DataFrame.apply
提问by Michael Henry
Suppose I have a dataframe like this:
假设我有一个这样的数据框：
df = pd.DataFrame([['foo', 'x'], ['bar', 'y']], columns=['A', 'B'])
A B
0 foo x
1 bar y
I know how to use a single argument function with Apply when it comes to dataframes, like this:
当涉及到数据帧时，我知道如何将单参数函数与 Apply 一起使用，如下所示：
def some_func(row):
return '{0}-{1}'.format(row['A'], row['B'])
df['C'] = df.apply(some_func, axis=1)
df
A B C
0 foo x foo-x
1 bar y bar-y
How can I use apply on dataframes when they involve multiple input arguments? Here's an example of what I want:
当数据帧涉及多个输入参数时，如何在数据帧上使用应用程序？这是我想要的一个例子：
def some_func(row, var1):
return '{0}-{1}-{2}'.format(row['A'], row['B'], var1)
df['C'] = df.apply(some_func(row, var1='DOG'), axis=1)
df
A B C
0 foo x foo-x-DOG
1 bar y bar-y-DOG
I'm not looking for work-arounds to solve this one particular example, just how to do something like this in general. Any advice would be well appreciated, thanks.
我不是在寻找解决这个特定示例的变通方法，而是在一般情况下如何做这样的事情。任何建议将不胜感激，谢谢。
采纳答案by cs95
It's just the way you think it would be, applyaccepts argsand kwargsand passes them directly to some_func.
这是现在的样子，你认为这将是，apply接受args并kwargs直接传递它们some_func。
df.apply(some_func, var1='DOG', axis=1)
Or,
或者，
df.apply(some_func, args=('DOG', ), axis=1)
0 foo-x-DOG
1 bar-y-DOG
dtype: object
回答by jpp
You should use vectorized logic:
您应该使用矢量化逻辑：
df['C'] = df['A'] + '-' + df['B'] + '-DOG'
If you really want to use df.apply, which is just a thinly veiled loop, you can simply feed your arguments as additional parameters:
如果您真的想使用df.apply，这只是一个隐蔽的循环，您可以简单地将您的参数作为附加参数提供：
def some_func(row, var1):
return '{0}-{1}-{2}'.format(row['A'], row['B'], var1)
df['C'] = df.apply(some_func, var1='DOG', axis=1)
As per the docs, df.applyaccepts both positional and keyword arguments.
根据docs，df.apply接受位置参数和关键字参数。
回答by YOBEN_S
I think it can be
我认为可以
df.apply('-'.join,1)+'-DOG'
Out[157]:
0 foo-x-DOG
1 bar-y-DOG
dtype: object
