KeyError / TypeError: Selecting rows in MultiIndex with tuple syntax

KeyError / TypeError: Selecting rows in MultiIndex with tuple syntax

$ python - <<'PY'
import pandas as pd
idx = pd.MultiIndex.from_tuples([(1,10),(2,20)], names=['a','b'])
df = pd.DataFrame({'x': [1, 2]}, index=idx)
# Mistaken attempt to use tuple indexing on the DataFrame like df[1,10]
df[1,10]
PY
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
KeyError: 1

Why this happens

Using df[1,10] is interpreted as looking up a column label 1 (then trying to index column with key 10), not selecting by row index. With a MultiIndex, selecting a row by a tuple must use .loc, .xs (cross-section), or direct tuple indexing on .loc. Without .loc or .xs, pandas raises a KeyError because it interprets the tuple as chained column selectors.

Fix

Use .loc with a tuple to index a row by a full multi-level key, or use .xs or nested .loc to select slices of a MultiIndex.

Wrong code

import pandas as pd
idx = pd.MultiIndex.from_tuples([(1,10),(2,20)], names=['a','b'])
df = pd.DataFrame({'x': [1, 2]}, index=idx)
df[1,10]  # raises KeyError - parsed as column lookup not row selection

Fixed code

import pandas as pd
idx = pd.MultiIndex.from_tuples([(1,10),(2,20)], names=['a','b'])
df = pd.DataFrame({'x': [1, 2]}, index=idx)

# Use .loc with a tuple for row selection
df.loc[(1, 10)]

# Or use xs to select by a level
df.xs(1, level='a')

# Or chain .loc/indexing to select nested keys
df.loc[1].loc[10]