Python 类型错误：无法将系列转换为 <class 'float'>
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TypeError: cannot convert the series to <class 'float'>
提问by Stacey
I have a dataframe (df) that looks like:
我有一个看起来像的数据框（df）：
date A
2001-01-02 1.0022
2001-01-03 1.1033
2001-01-04 1.1496
2001-01-05 1.1033
2015-03-30 126.3700
2015-03-31 124.4300
2015-04-01 124.2500
2015-04-02 124.8900
For the entire time-series I'm trying to divide today's value by yesterdays and log the result using the following:
对于整个时间序列，我试图将今天的值除以昨天的值并使用以下命令记录结果：
df["B"] = math.log(df["A"] / df["A"].shift(1))
However I get the following error:
但是我收到以下错误：
TypeError: cannot convert the series to <class 'float'>
How can I fix this? I've tried to cast as float using:
我怎样才能解决这个问题？我尝试使用以下方法将其转换为浮点数：
df["B"] .astype(float)
But can't get anything to work.
但不能得到任何工作。
回答by user3582076
You can use numpy.log instead. Math.log is expecting a single number, not array.
您可以改用 numpy.log。Math.log 需要一个数字，而不是数组。
回答by William Welsh
If you just write df["A"].astype(float)you will not change df. You would need to assign the output of the astypemethod call to something else, including to the existing series using df['A'] = df['A'].astype(float). Also you might want to either use numpy as @user3582076 suggests, or use .applyon the Series that results from dividing today's value by yesterday's.
如果你只是写df["A"].astype(float)你不会改变df。您需要将astype方法调用的输出分配给其他内容，包括使用df['A'] = df['A'].astype(float). 此外，您可能希望按照@user3582076 的建议使用 numpy，或者.apply在将今天的值除以昨天的值所得的系列上使用。
回答by Laura Baker
I had the same issue, for me the answer was to look at the cause of why I had series in the first place. After looking for a long time about how to change the series into the different assigned data type, I realised that I had defined the same column name twice in the dataframe and that was why I had a series.
我有同样的问题，对我来说，答案是首先看看为什么我有系列的原因。在寻找了很长时间关于如何将系列更改为不同的指定数据类型之后，我意识到我在数据框中定义了两次相同的列名，这就是我有一个系列的原因。
Removing the accidental duplication of column name removes this issue :)
删除列名的意外重复可以解决此问题:)
