我正在尝试创建一个函数,该函数可以在不更改原始数据帧的情况下更改数据帧副本的值。这是我目前所拥有的:
def home_undervalued(df):
local_df = df
local_df['total_games'] = 0
local_df['total_wins'] = 0
cond_1 = local_df['predicted_spread'] > local_df['vegas_spread']
cond_2 = local_df['actual_spread'] > local_df['vegas_spread']
cond_3 = local_df['predicted_spread'] - local_df['vegas_spread'] >= 3
local_df.loc[cond_1 & cond_3 , 'total_games'] = 1
local_df.loc[cond_1 & cond_2 & cond_3 , 'total_wins'] = 1
total_games = sum(local_df.total_games)
total_wins = sum(local_df.total_wins)
return float(total_wins) / float(total_games)
然后我调用这个函数
home_undervalued(df)
它似乎有效,但后来我意识到 df['total_games'] 和 df['total_wins'] 的值已经改变。我正在尝试更改 local_df 的值,但保留值 df。关于如何解决此问题的任何想法?
最佳答案
local_df = df
只是创建一个对名为 local_df
的 df
的引用。如果你想创建一个完整的其他数据帧(顺便说一下,我不推荐)你可以创建一个新的数据帧作为 df.copy(deep=True)
关于python - 在不更改原始数据的情况下复制函数内部的数据框,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/40661930/