ValueError: too many values to unpack (expected 2) — how to fix

Traceback (most recent call last):
  File "app.py", line 3, in <module>
    for key, value in data:
ValueError: too many values to unpack (expected 2)

Quick fix: Make the left side match the number of items. Looping over a dict? Use for key, value in d.items():. Splitting a string? Use a, b = s.split(',', 1) or first, *rest = s.split(',').

What it means

Unpacking like a, b = something requires something to have exactly two items. Python found more (too many) or fewer (not enough values to unpack (expected 2, got 1)).

Cause 1: iterating over a dict directly

data = {"a": 1, "b": 2}
for key, value in data:          # iterates over keys: "a", "b"

Each key is a string, and Python tries to unpack its characters. Use .items():

for key, value in data.items():

Cause 2: string split produces more parts

line = "name,city,country"
name, city = line.split(",")     # 3 parts

Options:

name, city = line.split(",", 1)          # split only once
name, city, *_ = line.split(",")         # ignore the rest
name, *rest = line.split(",")            # rest is a list

For CSV data use the csv module; it handles quoted commas correctly.

Cause 3: a function returns more than you expect

def stats(xs):
    return min(xs), max(xs), sum(xs)

lo, hi = stats([1, 2, 3])        # returns 3 values

Print what you're unpacking to check its shape:

result = stats([1, 2, 3])
print(type(result), len(result), result)

Cause 4: rows with different lengths

When looping over rows (for x, y in points:), one malformed row breaks the loop. Find it:

for i, row in enumerate(points):
    if len(row) != 2:
        print(i, row)

NumPy / pandas

for a, b in df: iterates column names, not rows. Use df.itertuples() or df.iterrows(); for arrays check arr.shape before unpacking.

Last updated 2026-10-27.