向量化分布适合基于numpy的groupby

Question

我正在尝试为here所述的广播答案找到一个类似的解决方案，该解决方案适用于总和：

export default (state = initialState, action) => {
  switch (action.type) {
    case ON_VISITOR_RECORDS_FETCHED:
      return state.merge({
        visitorRecords: fromJS(action.visitorRecords),
      });
    case ON_RETURN_APPROVED:
      return state.merge({
        approvedBookingId: action.approvedBookingId,
      });
    case ON_VISITOR_RECORD_UPDATED:
      return {
      ...state,
      visitorRecords: state.visitorRecords.map((record) => {
          if(record.id == action.payload.id){
             return{
                ...record,
                ...action.payload
             }
          }
      })
      }
    default:
      return state;
  }
};

如何调整此示例以使其适合scipy.stats.norm中的匹配项？它没有轴arg。

所以我要对10个组中的每一个都使用mu和std，如下所示：

import numpy as np

n = 10000
observations = np.random.uniform(low=5, high=7, size=n).reshape(-1, 1)
groups = np.random.randint(low=1, high=10, size=n)
d = np.bincount(groups, observations.sum(axis=1), 10)