python - .loc[] = value 在 Pandas 中返回 SettingWithCopyWarning
问题描述
问题
我的代码收到以下错误消息。据说,问题是我首先用 .loc 对数据帧进行切片,然后尝试为该切片分配值。据我了解,Pandas 不能 100% 确定我是想只为切片分配值,还是让它一直传播回原始 df。我不知道如何解决这个问题。
错误信息
C:\blp\BQuant\environments\bqnt-1.25.2\lib\site-packages\pandas\core\indexing.py:140: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
请参阅文档中的注意事项:http: //pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
self._setitem_with_indexer(indexer, value)
完整代码
import numpy as np
import pandas as pd
import datetime as dt
import time
csv1 = pd.read_csv('stock_price.csv', delimiter = ',')
df = pd.DataFrame(csv1)
df['delta'] = df.PX_LAST.pct_change()
df.loc[df.index[0], 'avg_gain'] = 0
for x in range(1,len(df.index)):
if df["delta"].iloc[x] > 0:
df["avg_gain"].iloc[x] = ((df["avg_gain"].iloc[x - 1] * 13) + df["delta"].iloc[x]) / 14
else:
df["avg_gain"].iloc[x] = ((df["avg_gain"].iloc[x - 1] * 13) + 0) / 14
df
输入
Dates,PX_LAST
03/09/2018,157.512
04/09/2018,155.393
05/09/2018,154.069
06/09/2018,155.109
07/09/2018,156.301
10/09/2018,156.717
11/09/2018,157.19
12/09/2018,157.549
13/09/2018,159.157
14/09/2018,158.363
17/09/2018,158.968
输出
Dates,PX_LAST,delta,avg_gain
03/09/2018,157.512,NaN,0
04/09/2018,155.393,-0.013453,0
05/09/2018,154.069,-0.00852,0
06/09/2018,155.109,0.00675,0.000482
07/09/2018,156.301,0.007685,0.000997
10/09/2018,156.717,0.002662,0.001116
11/09/2018,157.19,0.003018,0.001251
12/09/2018,157.549,0.002284,0.001325
13/09/2018,159.157,0.010206,0.00196
14/09/2018,158.363,-0.004989,0.00182
17/09/2018,158.968,0.00382,0.001963
问题所在的代码行
for x in range(1,len(df.index)):
if df["delta"].iloc[x] > 0:
df["avg_gain"].iloc[x] = ((df["avg_gain"].iloc[x - 1] * 13) + df["delta"].iloc[x]) / 14
else:
df["avg_gain"].iloc[x] = ((df["avg_gain"].iloc[x - 1] * 13) + 0) / 14
解决方案
我尝试使用.copy()
,但仍然收到相同的错误消息
for x in range(1,len(df.index)):
if df["delta"].iloc[x] > 0:
df["avg_gain"].iloc[x] = ((df["avg_gain"].iloc[x - 1].copy() * 13) + df["delta"].iloc[x].copy()) / 14
else:
df["avg_gain"].iloc[x] = ((df["avg_gain"].iloc[x - 1].copy() * 13) + 0) / 14
谢谢
解决方案
问题代码可以替换为
for x in range(1,len(df.index)):
if df["delta"].iloc[x] > 0:
df.iloc[x, -1] = ((df["avg_gain"].iloc[x - 1] * 13) + df["delta"].iloc[x]) / 14
else:
df.iloc[x,-1] = ((df["avg_gain"].iloc[x - 1].copy() * 13) + 0) / 14
这是因为您avg_gain
最后添加的,所以您可以使用iloc[:,-1]
访问该列。
使用更新ewm
:
arg = df["delta"].clip(lower=0)
arg.iloc[0] = 0
df['avg_gain'] = arg.ewm(alpha=1/14, adjust=False).mean()
输出:
0 0.000000
1 0.000000
2 0.000000
3 0.000482
4 0.000997
5 0.001116
6 0.001251
7 0.001325
8 0.001960
9 0.001820
10 0.001962
Name: delta, dtype: float64
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