如何计算作为 df 中一列的嵌套列表中的频率？

Question

我想计算嵌套列表中某个项目的出现次数。 Pandas df的当前结构；每条记录按 match_id 和 possession_id 分组，然后将值第二个 action_name、player_name 传递到名为 action_seq.

的列表

我可以计算每次拥有的事件总数没问题，但我现在希望能够计算次数，例如玩家 A 参与过事件？他们在哪些事件中发生的频率更高？

#sample df
pass_goal = pd.DataFrame({'match_id': [1107073,1107073,1107073,1409630,1409630], 
'possession_number': [2,2,2,40,40], 'second': [10,15,20,250,260], 
'action_name': ['pass', 'pass', 'goal','pass','goal'], 
'player_name': ['a','b','c','a','b']})

#grouping by match and possession then adding a list
posses = pass_goal.groupby(['match_id','possession_number'])[['second', 'action_name','player_name']].apply(lambda action: action.values.tolist()).reset_index(name='action_seq')

首选输出

Player A B C
Pass   2 1 0
Goal   0 1 1

Answer 1

你可以试试：

(pass_goal[["action_name","player_name"]]
 .pivot_table(columns="player_name", index="action_name", aggfunc=len, fill_value=0)
 .rename_axis(index="", columns="player"))

player       a  b  c

goal         0  1  1
pass         2  1  0

如何计算作为 df 中一列的嵌套列表中的频率？

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