grouped.grouped_count

grouped.grouped_count(ind: Array, v: Array, filtered: bool = True, chunks: int | tuple[int, ...] | None = None, verbose: bool = False) → ndarray[tuple[int], uint64] | DataFrame

Compute the count of each index. NaN values in v are ignored

Parameters:

• ind (array-like) – index labels

• v (array-like) – data

• filtered (bool, optional) – Filter the output in a pandas dataframe, which is the default. If False, this function returns the raw output, where the index of the value corresponds to the index labels.

• chunks (int or tuple of ints, optional) – Optional chunking of the data, which can be run in parallel in a joblib context

• verbose (bool, optional) – Print timing

Returns:

counts – The count of each index.

Return type:

np.ndarray or pd.DataFrame