Replace comma and dot in Pandas

Question

I have a Column with data like 3.4500,00 EUR. Now I want to compare this with another column having float numbers like 4000.00. How do i take this string, remove the EUR and replace comma with decimal and then convert into float to compare.

Solution

You can use regular expressions to make your conditions general that would work in all cases:

# Make example dataframe for showing answer
df = pd.DataFrame({'Value':['3.4500,00 EUR', '88.782,21 DOLLAR']})

              Value
0     3.4500,00 EUR
1  88.782,21 DOLLAR

Use str.replace with regular expression:

df['Value'].str.replace('[A-Za-z]', '').str.replace(',', '.').astype(float)

0    34500.00
1    88782.21
Name: Value, dtype: float64

Explanation:

• str.replace('[A-Za-z\.]', '') removes all alphabetic characters and dots.
• str.replace(',', '.') replaces the comma for a dot
• astype(float) converts it from object (string) type to float