pandas 如何在熊猫系列中用 at[] 替换 set_value
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How do I replace set_value with at[] in a pandas Series
提问by user1067305
I'm trying to construct a pandas Series to concatenate onto a dataframe.
我正在尝试构建一个Pandas系列来连接到数据帧上。
import numpy as np
import pandas as pd
rawData = pd.read_csv(input, header=1) # the DataFrame
strikes = pd.Series() # the empty Series
for i, row in rawData.iterrows():
sym = rawData.loc[i,'Symbol']
strike = float(sym[-6:])/1000
strikes = strikes.set_value(i, strike)
print("at26: ",strikes.values)
This program works, but I get the error message:
该程序有效，但我收到错误消息：
"line 25: FutureWarning: set_value is deprecated and will be removed in a future release. Please use .at[] or .iat[] accessors instead."
“第 25 行：FutureWarning：set_value 已弃用，将在未来版本中删除。请改用 .at[] 或 .iat[] 访问器。”
Every way I have tried to substitute .at, I get a syntax error. Many of the suggestions posted relate to DataFrames, not Series. Append requires another series, and complains when I give it a scalar.
我尝试用每种方式替换 .at 时，都会出现语法错误。发布的许多建议与 DataFrames 相关，而不是 Series。Append 需要另一个系列，当我给它一个标量时会抱怨。
What is the proper way to do it?
什么是正确的方法呢？
回答by jpp
Replace strikes.set_value(i, strike)with strikes.at[i] = strike.
替换strikes.set_value(i, strike)为strikes.at[i] = strike。
Note that assignment back to a series is not necessary with set_value:
请注意，分配回系列不是必需的set_value：
s = pd.Series()
s.set_value(0, 10)
s.at[1] = 20
print(s)
0 10
1 20
dtype: int64
For the algorithm you are looking to run, you can simply use assignment:
对于您要运行的算法，您可以简单地使用赋值：
strikes = rawData['Symbol'].str[-6:].astype(float) / 1000
