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converting currency with $ to numbers in Python pandas

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

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).

So I used the following code for data conversion:

data = data.convert_objects(convert_numeric=True)

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

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@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)

To me, that is a little bit more readable.


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