在Python Pandas中将带有$的货币转换为数字 [英] converting currency with $ to numbers in Python pandas
问题描述
我在pandas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(第一列,第二列,第三列)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,也许由于美元符号的原因,转换无法正常工作.有什么建议吗?
But, conversion does not work, perhaps, due to the dollar sign. Any suggestion?
推荐答案
@EdChum的答案很聪明,效果很好.但是,既然有多种方法可以烤蛋糕……为什么不使用正则表达式呢?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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