熊猫尝试使用.loc[row_indexer，col_indexer] = value

Question

下面是我的例子

data = {'Team': ['Riders', 'Riders', 'Devils', 'Devils', 'Kings',
         'kings', 'Kings', 'Kings', 'Riders', 'Royals', 'Royals', 'Riders'],
         'Rank': [1, 2, 2, 3, 3,4 ,1 ,1,2 , 4,1,2],
         'Year': [2014,2015,2014,2015,2014,2015,2016,2017,2016,2014,2015,2017],
         'Points':[876,789,863,673,741,812,756,788,694,701,804,690]}
data = pd.DataFrame(data)
data.head()

当我这样做的时候，我收到了熊猫图书馆的警告

from sklearn.model_selection import train_test_split
train_new, val_new = train_test_split(data, test_size=0.2)

col = 'Team'
means = data.groupby(col)['Points'].mean()
train_new[col + '_mean_target'] = train_new[col].map(means)
train_new.head()

这是警告

SettingWithCopyWarning:一个值试图在来自DataFrame的片的副本上设置。尝试使用.locrow_indexer，col_indexer =代替

当我使用.loc时

col = 'Team'
means = data.groupby(col)['Points'].mean()
train_new.loc[:,col + '_mean_target'] = train_new.loc[:,col].map(means)
train_new.head()

它显示了同样的警告，那么代码有什么问题呢？

Answer 1

另一种方法是禁用链式赋值，它适用于代码，而不需要创建副本：。

# disable chained assignments
pd.options.mode.chained_assignment = None

这是这个相关问题的答案(不会说是一个重复的问题)- Pandas DataFrame: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame