尝试将Python Pandas中的字符串转换为Float时发生错误(Error when trying to convert a column with string in Python Panda

尝试将Python Pandas中的字符串转换为Float时发生错误(Error when trying to convert a column with string in Python Pandas to Float)

我有一个名为'market_cap_（in_us_ $）'的列，其值如下所示：

$5.41 $18,160.50 $9,038.20 $8,614.30 $368.50 $2,603.80 $6,701.50 $8,942.40

我的最终目标是能够根据特定的数值进行过滤（例如，> 2000.00）。

通过阅读本网站的其他问题，我遵循以下指示：

cleaned_data['market_cap_(in_us_$)'].replace( '$', '', regex = True ).astype(float)

但是，我收到以下错误

TypeError: replace() got an unexpected keyword argument 'regex'

如果我从替换参数中删除“regex = True”，我会得到

ValueError: could not convert string to float: $5.41

所以我该怎么做？

I have a column named 'market_cap_(in_us_$)' which values are like:

$5.41 $18,160.50 $9,038.20 $8,614.30 $368.50 $2,603.80 $6,701.50 $8,942.40

My final goal is to be able to filter based on specific numeric values (for example, > 2000.00).

By reading other questions in this site, I followed the instructions as:

cleaned_data['market_cap_(in_us_$)'].replace( '$', '', regex = True ).astype(float)

However, I receiving the following error

TypeError: replace() got an unexpected keyword argument 'regex'

If I remove the "regex = True" from the replace arguments, I get

ValueError: could not convert string to float: $5.41

So, what should I do?

最满意答案

这里给出了正确使用的正则表达式，因为您想要移除$和：

In [7]: df['market_cap_(in_us_$)'].replace('[\$,]', '', regex=True).astype(float) Out[7]: 0 5.41 1 18160.50 2 9038.20 3 8614.30 4 368.50 5 2603.80 6 6701.50 7 8942.40 Name: market_cap_(in_us_$), dtype: float64

但既然你得到了keyword argument 'regex'错误，你必须使用一个非常旧的版本，并且应该更新。

The right regular expression to use is given here, as you want to remove the $ and ,:

In [7]: df['market_cap_(in_us_$)'].replace('[\$,]', '', regex=True).astype(float) Out[7]: 0 5.41 1 18160.50 2 9038.20 3 8614.30 4 368.50 5 2603.80 6 6701.50 7 8942.40 Name: market_cap_(in_us_$), dtype: float64

But since you got that keyword argument 'regex' error, you must be using a very old version, and should update.