TypeError: 'int' object is not subscriptable — how to fix

Traceback (most recent call last):
  File "main.py", line 3, in <module>
    print(n[0])
TypeError: 'int' object is not subscriptable

Quick fix: Find where the variable became an int (print(type(x))). To get digits use str(n)[0] or int(str(n)[0]); don't reuse a list's name for a counter; and check functions return the container, not a count.

What it means

"Subscriptable" means "supports x[...]". Lists, tuples, strings and dicts are subscriptable; int, float, bool and None are not. Python raises this when the object before [ is an int. The same applies to 'float' object is not subscriptable.

Start by checking what the value really is:

print(type(x), x)

Cause 1: you want a digit of a number

n = 2026
first = n[0]        # TypeError

Convert to a string first:

first = str(n)[0]             # '2'
first_digit = int(str(n)[0])  # 2
digits = [int(d) for d in str(n)]   # [2, 0, 2, 6]

Or use arithmetic: last = n % 10, first = n // 10 ** (len(str(n)) - 1).

Cause 2: a variable got overwritten with a number

scores = [90, 85, 70]
for scores in range(3):      # reuses the name!
    pass
print(scores[0])             # scores is now 2

Or with sum/len:

items = [3, 4]
items = len(items)
items[0]                     # TypeError

Fix: use distinct names (for i in range(...), count = len(items)).

Cause 3: function returns a number, not a list

def get_ids():
    ids = [1, 2, 3]
    return len(ids)          # oops

get_ids()[0]                 # TypeError

Check the return statement. Methods like list.count(), str.find(), cursor.rowcount and dict.get(key, 0) return integers, too.

Cause 4: nested data is shallower than you think

data = {"user": {"id": 7}}
data["user"]["id"][0]        # 'int' object is not subscriptable

Print the intermediate value (print(data["user"])) or use json.dumps(data, indent=2) to see the real structure.

Cause 5: a 2D list that is really 1D

grid = [0] * 5
grid[1][2] = 9               # grid[1] is the int 0

Build a real 2D list:

grid = [[0] * 5 for _ in range(5)]
grid[1][2] = 9

(Don't use [[0] * 5] * 5 — that creates five references to the same row.)

Cause 6: pandas/numpy scalars

df["col"].sum(), df.shape[0] and arr.max() return scalars. Indexing them again (df.shape[0][0]) raises this error, sometimes with 'numpy.int64' object is not subscriptable. Drop the extra index.

Last updated 2026-11-03.