Convert amount to numbers: remove commas, and turn anything that can't be parsed (like n/a or empty) into NaN. Store the numeric Series in result.
import pandas as pd
import numpy as np
raw = pd.DataFrame({
"id": [1, 2, 3, 3, 4, 5, 6, 7],
"name": [" asha ", "RAVI", "kiran", "kiran", "Meena", None, "om ", "Farah"],
"city": ["Pune", "delhi", "Mumbai", "Mumbai", None, "Pune", "PUNE", "Delhi "],
"amount": ["1,200", "850", "2,000", "2,000", "n/a", "430", "", "990"],
"signup": ["2025-01-05", "2025/01/12", "2025-02-03", "2025-02-03", "2025-02-14", "not known", "2025-03-01", "2025-03-09"],
"score": [78.0, np.nan, 91.0, 91.0, 66.0, np.nan, 55.0, 83.0],
})Store your final answer in a variable named result.
Each hint gives a little more help. Try on your own first.
Run your code to see the output here.