Question

我最近一直在研究项目，该项目预测幻想英超联赛中最优秀的球队。在成功分析了不同的特征和参数之后，由于以下“ TypeError：'Series'对象易变，因此无法进行哈希处理”，我陷入了困境

我已经完成了代码的第一部分的编写，但是收到了一个错误。我在网上搜索，但找不到解决方案。解决方案之一说您不能将序列附加到列表中。真的吗？以及相同的可能解决方案是什么。我现在走的太远了，我真的很想把它做好。

def my_team (budget = 100, star_player_limit = 3, gk = 2, df = 5, mid = 5, fwd = 3 ): # Pass constraints to function
    team = [ ]                          # List of team to be returned
    star_position = [ ]                 # list containing position of starplayer
    star_player_limit = star_player_limit
    budget = budget
    injured = dataset2.loc[(dataset2.loc[:,"Status"] == 'injured'),:] # Keeping a check of injury status
    positions = {"GKP":gk,"DEF":df,"MID":mid,"FWD":fwd}       # Dict accounting for no. of postions left to fill
    for ind in Top_points.index:       # Looping through the dataframe of players
        player = Top_points.loc[ind]   # Row of Dataframe one at a time
        star_position.append(player.Position)    # Checking position of star player
        if len(team) < star_player_limit and player not in injured and budget > player.Cost and positions[player.Position] > 0 and player.Position not in star_position:
            team.append(player)
            budget -= player.Cost
            positions[player.Position] -= 1

    return team

my_team（）

运行代码后，出现以下错误：TypeError: 'Series' objects are mutable, thus they cannot be hashed。

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-150-a7d781e901c6> in <module>()
----> 1 my_team()

<ipython-input-149-ec17dbd9b9ba> in my_team(budget, star_player_limit, gk, df, mid, fwd)
      9         player = Top_points.loc[ind]
     10         star_position.append(player.Position)
---> 11         if len(team) < star_player_limit and player not in injured and budget > player.Cost and positions[player.Position] > 0 and player.Position not in star_position:
     12             team.append(player)
     13             budget -= player.Cost

~\Anaconda3\lib\site-packages\pandas\core\generic.py in __contains__(self, key)
   1517     def __contains__(self, key):
   1518         """True if the key is in the info axis"""
-> 1519         return key in self._info_axis
   1520 
   1521     @property

~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in __contains__(self, key)
   2018     @Appender(_index_shared_docs['__contains__'] % _index_doc_kwargs)
   2019     def __contains__(self, key):
-> 2020         hash(key)
   2021         try:
   2022             return key in self._engine

~\Anaconda3\lib\site-packages\pandas\core\generic.py in __hash__(self)
   1487     def __hash__(self):
   1488         raise TypeError('{0!r} objects are mutable, thus they cannot be'
-> 1489                         ' hashed'.format(self.__class__.__name__))
   1490 
   1491     def __iter__(self):

TypeError: 'Series' objects are mutable, thus they cannot be hashed

Answer 1

熊猫框架是可变的。因此，它们不能用作字典的键或集合的元素。

查看第一个堆栈跟踪中的第11行。我已经将其重新设置格式以便于阅读。

if (len(team) < star_player_limit and
    player not in injured and
    budget > player.Cost and
    positions[player.Position] > 0 and
    player.Position not in star_position):

我们在这里有一个player not in injured子句。前者定义为

player = Top_points.loc[ind]

我想它的类型是Series。

现在，我们有了处理__contains__运算符的in方法的第二个堆栈跟踪。在其中，我假设self是injured，而key是player。实际上，它不能hash(player)。

（它不能是第二个in子句，因为start_position是一个普通的Python列表，而__contains__的堆栈跟踪来自熊猫。）

我将从player中提取名称或其他ID，并在injured中进行搜索；也许我会一路把injured变成一组名字。

是否可以将熊猫系列添加到列表中

1 个答案: