所以dask现在已经更新,以支持groupby的自定义聚合功能.(感谢开发团队和@chmp的工作!).我目前正在尝试构建一个模式函数和相应的计数函数.基本上我所设想的是,模式为每个分组返回特定列的最常见值的列表(即[4,1,2]).此外,还有一个相应的计数函数,它返回这些值的实例数,即.3.
现在我正在尝试在代码中实现它.根据groupby.py文件,自定义聚合的参数如下:
Parameters
----------
name : str
the name of the aggregation. It should be unique, since intermediate
result will be identified by this name.
chunk : callable
a function that will be called with the grouped column of each
partition. It can either return a single series or a tuple of series.
The index has to be equal to the groups.
agg : callable
a function that will be called to aggregate the results of each chunk.
Again the …我有一个奇怪的错误,说我的类正在重新定义,源于我的Node类中的朋友声明.这是我目前的代码:
template <class T>
class Node {
private:
T val;
Node<T> * next;
public:
friend class OList;
};
我的其他课程:
template <class T>
class OList { ------> Error here
private:
Node<T> * head;
int size;
public:
OList();
OList(const OList<T> &b);
~OList();
clear();
int size();
T tGet(int input);
int count(T input);
insert (T input);
remove (T input);
uniquify(T input);
Node<T> * returnHead();
};
// Constructs empty list
template <class T>
OList<T>::OList() { ---> Error here
head = NULL;
size = 0;
}