用 $ 将货币转换为 Python pandas 中的数字

问题描述

我在熊猫数据框中有以下数据:

I have the following data in pandas dataframe:

    state        1st        2nd             3rd
0   California  $11,593,820 $109,264,246    $8,496,273
1   New York    $10,861,680 $45,336,041     $6,317,300
2   Florida     $7,942,848  $69,369,589     $4,697,244
3   Texas       $7,536,817  $61,830,712     $5,736,941

我想用三列(第一、第二、第三)执行一些简单的分析(例如，sum、groupby)，但是这三列的数据类型是对象(或字符串).

I want to perform some simple analysis (e.g., sum, groupby) with three columns (1st, 2nd, 3rd), but the data type of those three columns is object (or string).

所以我使用了以下代码进行数据转换:

So I used the following code for data conversion:

data = data.convert_objects(convert_numeric=True)

但是，转换不起作用，也许是由于美元符号.有什么建议吗?

But, conversion does not work, perhaps, due to the dollar sign. Any suggestion?

推荐答案

@EdChum 的回答很聪明而且效果很好.但是既然有不止一种烤蛋糕的方法......为什么不使用正则表达式?例如:

@EdChum's answer is clever and works well. But since there's more than one way to bake a cake.... why not use regex? For example:

df[df.columns[1:]] = df[df.columns[1:]].replace('[$,]', '', regex=True).astype(float)

对我来说，这更具可读性.

To me, that is a little bit more readable.

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