从数据框列中的字符串值中删除字符

Question

I hope you can help me with this question. I have a column with numeric values as strings. Since they are data from diferent countries, some of them have different formats such as "," and "$". I'm trying to convert the serie to numbers, but i'm having trouble with "," and "$" values.

data={"valores":[1,1,3,"4","5.00","1,000","$5,700"]}
df=pd.DataFrame(data)
df

    valores
0   1
1   1
2   3
3   4
4   5.00
5   1,000
6   $5,700

Ive tried the following:

df["valores"].replace(",","")

but it does not change a thing since the "," value is in the string, not the string value itself

pd.to_numeric(df["valores"])

But I receive the "ValueError: Unable to parse string "1,000" at position 5" error.

valores=[i.replace(",","") for i in df["valores"].values]

But I receive the "AttributeError: 'int' object has no attribute 'replace' error.

So, at last, I tried with this:

valores=[i.replace(",","") for i in df["valores"].values if type(i)==str]
valores
['4', '5.00', '1000', '$5700']

But it skipped the first three values since they are not strings..

I think that with a Regex code i would be able to manage it, but I just simply dont understand how to work with it.

I hope you can help me since i've been struggling with this for about 7 hours.

Answer 1

你可以试试这个：

df['valores'] = df['valores'].replace(to_replace='[\,\$]',value='',regex=True).astype(float)

Answer 2

你应该首先从它创建一个字符串，所以像这样

valores=[str(i).replace(",","") for i in df["valores"].values]

Answer 3

.replace by default searches for the whole cell values . Since you want to replace a part of the string, you need .str.replace or replace(...,regex=True) :

df['valores'] = df["valores"].replace(",","", regex=True)

Or:

df['valore'] = df["valores"].str.replace(",","")

Answer 4

You need to cast the values in the valores column to string using .astype(str) , then remove all $ and , using .str.replace('[,$]', '') and then you may convert all data to numeric using pd.to_numeric :

>>> pd.to_numeric(df["valores"].astype(str).str.replace("[,$]",""))
0       1.0
1       1.0
2       3.0
3       4.0
4       5.0
5    1000.0
6    5700.0