Pandas version checks
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[x] I have checked that this issue has not already been reported.
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[x] I have confirmed this bug exists on the latest version of pandas.
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[x] I have confirmed this bug exists on the main branch of pandas.
Issue Description
The Series .map() function frequently fails when using dictionaries with tuple keys which is given as parameter to the map function. See the below examples:
Ex 1:
import pandas as pd
df = pd.DataFrame({"a": [(1,1), (2,2), (3,4), (5,6)]})
label_mappings = {(1,): "A", (2,2): "B", (3,4): "A", (5,6): "B"}
df["mapped_labels"] = df["a"].map(label_mappings)
print(df)
# Output:
# a mapped_labels
# 0 (1, 1) A
# 1 (2, 2) B
# 2 (3, 4) A
# 3 (5, 6) B
# Expected Ouput:
# a mapped_labels
# 0 (1, 1) NaN
# 1 (2, 2) B
# 2 (3, 4) A
# 3 (5, 6) B
Ex 2:
import pandas as pd
df = pd.DataFrame({"a": [(1,1), (2,2), (3,4), (5,6)]})
label_mappings = {(2,): "A", (2,2): "B", (3,4): "A", (5,6): "B"}
df["mapped_labels"] = df["a"].map(label_mappings)
print(df)
# Output:
# Produces error: pandas.errors.InvalidIndexError: Reindexing only valid with uniquely valued Index objects
# Expected Ouput:
# a mapped_labels
# 0 (1, 1) NaN
# 1 (2, 2) B
# 2 (3, 4) A
# 3 (5, 6) B
EX 3:
import pandas as pd
df = pd.DataFrame({"a": [(1,), (2,2), (3,4), (5,6)]})
label_mappings = {(1,None): "A", (2,2): "B", (3,4): "A", (5,6): "B"}
df["mapped_labels"] = df["a"].map(label_mappings)
print(df)
# Output:
# Produces error: AssertionError: Length of new_levels (2) must be <= self.nlevels (1)
# Expected Ouput:
# a mapped_labels
# 0 (1, ) NaN
# 1 (2, 2) B
# 2 (3, 4) A
# 3 (5, 6) B
EX 4:
import pandas as pd
df = pd.DataFrame({"a": [(1,), (2,2), (3,4), (5,6)]})
label_mappings = {(1,1): "A", (2,2): "B", (3,4): "A", (5,6): "B"}
df["mapped_labels"] = df["a"].map(label_mappings)
print(df)
# Output:
# Produces error: AssertionError: Length of new_levels (2) must be <= self.nlevels (1)
# Expected Ouput:
# a mapped_labels
# 0 (1, ) NaN
# 1 (2, 2) B
# 2 (3, 4) A
# 3 (5, 6) B
EX 5:
import pandas as pd
df = pd.DataFrame({"a": [(1,1), (1,2), (3,4), (5,6)]})
label_mappings = {(1,): "A", (2,2): "B", (3,4): "A", (5,6): "B"}
df["mapped_labels"] = df["a"].map(label_mappings)
print(df)
# Output:
# a mapped_labels
# 0 (1, 1) A
# 1 (1, 2) A
# 2 (3, 4) A
# 3 (5, 6) B
# Expected Ouput:
# a mapped_labels
# 0 (1, 1) NaN
# 1 (1, 2) NaN
# 2 (3, 4) A
# 3 (5, 6) B
Expected Behavior
Gave the actual outputs and expected outputs.
Installed Versions
INSTALLED VERSIONS
------------------
commit : 6bcd30397d67c3887288c7a82c2c235ce8bc3c7f
python : 3.10.14
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.26120
machine : AMD64
processor : AMD64 Family 23 Model 96 Stepping 1, AuthenticAMD
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 3.0.0.dev0+1944.g6bcd30397d.dirty
numpy : 1.26.4
dateutil : 2.9.0.post0
pip : 24.0
Cython : 3.0.10
sphinx : 7.3.7
IPython : 8.18.1
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
blosc : None
bottleneck : None
fastparquet : None
fsspec : 2024.6.1
html5lib : 1.1
hypothesis : 6.105.0
gcsfs : 2024.6.1
jinja2 : 3.1.4
lxml.etree : None
matplotlib : None
numba : 0.61.0
numexpr : None
odfpy : None
openpyxl : 3.1.5
psycopg2 : None
pymysql : 1.4.6
pyarrow : 19.0.0
pyreadstat : None
pytest : 8.3.4
python-calamine : None
pytz : 2025.1
pyxlsb : 1.0.10
s3fs : 2024.6.1
scipy : 1.15.2
sqlalchemy : 2.0.31
tables : None
tabulate : 0.9.0
xarray : 2024.6.0
xlrd : 2.0.1
xlsxwriter : 3.2.0
zstandard : None
tzdata : 2025.1
qtpy : None
pyqt5 : None
Comment From: Anurag-Varma
When I was trying to fix the issue #60695
The below test case was failing:
pandas/tests/series/methods/test_map.py::test_map_dict_with_tuple_keys
When i further tried to fix it, then found that Series.map() was failing for multiple examples as mentioned above.
Comment From: Anurag-Varma
take