ValueError: invalid literal for int() with base 10

invalid literal for int() with base 10

$ python - <<'PY'
import numpy as np
arr = np.array(['1', '2', 'three'])
arr.astype(int)
PY
Traceback (most recent call last):
  File "<stdin>", line 3, in <module>
ValueError: invalid literal for int() with base 10: 'three'

Why this happens

Some strings can’t be parsed as integers; astype(int) attempts direct Python conversion and fails on invalid literals.

Fix

Clean or validate data before converting. Use np.char.isdigit, list comprehensions, or pandas to_numeric with coercion.

Wrong code

import numpy as np
arr = np.array(['1', '2', 'three'])
arr.astype(int)

Fixed code

import numpy as np
arr = np.array(['1', '2', 'three'])
from pandas import to_numeric
clean = to_numeric(arr, errors='coerce')
clean.astype('Int64')

# or filter
valid = [int(x) for x in arr if x.isdigit()]