ValueError: invalid literal for int() with base 10 — how to fix

Traceback (most recent call last):
  File "app.py", line 2, in <module>
    age = int(value)
ValueError: invalid literal for int() with base 10: '12.5'

Quick fix: Look at the quoted value in the message. For decimals use int(float(s)); strip whitespace with s.strip(); skip empty strings and header rows; or wrap in try: int(s) except ValueError: to handle bad input.

What it means

int("42") works. int() with a string only accepts optional whitespace, an optional sign, and digits (underscores between digits are allowed, e.g. "1_000"). Anything else raises ValueError, and the message ends with repr() of the bad input. That quoted value is the key to the fix:

Cause 1: the string is a decimal

int("12.5")          # ValueError
int(float("12.5"))   # 12 (truncates toward zero)
round(float("12.5")) # 12 (banker's rounding)

For money or exact values use decimal.Decimal("12.5").

Cause 2: empty string

Common with input() when the user presses Enter, blank CSV cells, or line.split(",") on a trailing comma.

s = s.strip()
n = int(s) if s else 0

Cause 3: header row or labels in a file

with open("data.csv") as f:
    for line in f:
        total += int(line.split(",")[1])   # first line is "name,age"

Skip the header, or use the csv module:

import csv
with open("data.csv", newline="") as f:
    reader = csv.DictReader(f)
    total = sum(int(row["age"]) for row in reader if row["age"].strip())

Cause 4: formatted numbers

int("1,000".replace(",", ""))   # 1000
int("$25".lstrip("$"))          # 25

For locale-aware parsing ("1.234,5"), use locale.atof after locale.setlocale, or babel.numbers.parse_decimal.

Cause 5: other bases

int("0x1f", 16)   # 31
int("0x1f", 0)    # 31, base inferred from prefix
int("1010", 2)    # 10

Cause 6: hidden characters

Newlines are fine (int("5\n") works), but a BOM, non-breaking space or \x00 is not. Print with repr() to see them:

print(repr(s))    # '\ufeff42'

Open the file with encoding="utf-8-sig" to drop a BOM.

Handling user input robustly

def to_int(s, default=None):
    try:
        return int(s)
    except (TypeError, ValueError):
        return default

while True:
    try:
        age = int(input("Age: "))
        break
    except ValueError:
        print("Please enter a whole number.")

In pandas, use pd.to_numeric(df["col"], errors="coerce") to turn bad values into NaN instead of crashing.

Last updated 2026-11-03.