替换包含特定子字符串的单元格中的字符

Question

I have the following setup:

data = pd.DataFrame({
    "a": ["Amount 3,7$", "Amount 6,7$", "Amount 1,3$"],
    "b": ["2,3", " Amount 3,5", "4,7"]
})

I want to find any cells with the substring Amount and replace the character , with .

I expect:

    a           b
0   Amount 3.7$     2,3
1   Amount 6.7$     Amount 3.5
2   Amount 1.3$     4,7

I have tried:

for column in data.columns:
    data[column] = data[column][data[column].str.contains("Amount", na=False)].replace(",", ".", regex=True)

What I get is:

    a           b
0   Amount 3.7$     NaN
1   Amount 6.7$     NaN
2   Amount 1.3$     NaN

Somehow the mask is not working as expected

Answer 1

One approach:

data["b"] = np.where(data["b"].str.contains("Amount"), data["b"].str.replace(",", "."), data["b"])
print(data)

Output

             a            b
0  Amount 3,7$          2,3
1  Amount 6,7$   Amount 3.5
2  Amount 1,3$          4,7

An alternative is to use the following list comprehension:

data["b"] = [x.replace(",", ".") if "Amount" in x else x for x in data["b"]]

If "Amount" is always at the beginning, you could use a more elaborated regex, as below:

data["b"] = data["b"].str.replace("(.*Amount.*)(,)", r"\1.", regex=True)

Answer 2

applymap

data.applymap(lambda s: s.replace(',', '.') if 'Amount' in s else s)

---

             a            b
0  Amount 3.7$          2,3
1  Amount 6.7$   Amount 3.5
2  Amount 1.3$          4,7