Convert Formatted Currency Strings to Floats in Pandas

Question

Given a column with messy strings like `['$1,250.50', ' ₹ 4,999.00 ', ' $800 ' ]`, clean the column and convert it into a pure `float64` Series.

Accepted Answer

Optimal Solution:
import pandas as pd

# Vectorized regex replacement and float casting
df['clean_price'] = (
    df['raw_price']
    .str.replace(r'[^0-9.]', '', regex=True)
    .astype(float)
)

result_df = df[['clean_price']]

Technical Explanation:
`.str.replace(r'[^0-9.]', '', regex=True)` removes everything except digits and decimal points in a single vectorized pass, followed by `.astype(float)`.

raw_price
$1,250.50
₹ 4,999.00

clean_price
1250.5
4999