Description
Pandas version checks
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I have checked that this issue has not already been reported.
-
I have confirmed this bug exists on the latest version of pandas.
-
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
import numpy as np
df = pd.DataFrame(
{
"A": ["foo", "foo", "foo", "foo", "foo", "bar", "bar", "bar", "bar"],
"B": ["one", "one", "one", "two", "two", "one", "one", "two", "two"],
"C": [
"small",
"large",
"large",
"small",
"small",
"large",
"small",
"small",
"large",
],
"D": [1, 2, 2, 3, 3, 4, 5, 6, 7],
"E": [2, 4, 5, 5, 6, 6, 8, 9, 9],
("col5",): ["foo", "foo", "foo", "foo", "foo", "bar", "bar", "bar", "bar"],
("col6", 6): [
"one",
"one",
"one",
"two",
"two",
"one",
"one",
"two",
"two",
],
(7, "seven"): [
"small",
"large",
"large",
"small",
"small",
"large",
"small",
"small",
"large",
],
}
)
pd.pivot_table(df, values="D", index=["A", "B"], columns=[(7, "seven")], aggfunc=np.sum)Issue Description
With pandas 1.5.2 and numpy 1.23.5, we get:
C:\Anaconda3\envs\pstubtst\lib\site-packages\pandas\core\common.py:245: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
result = np.asarray(values, dtype=dtype)
With pandas 1.5.2 and numpy 1.24.0, we get:
Traceback (most recent call last):
File "c:\Code\pstubtst\np124.py", line 46, in <module>
pd.pivot_table(
File "C:\Anaconda3\envs\pstubtst\lib\site-packages\pandas\core\reshape\pivot.py", line 97, in pivot_table
table = __internal_pivot_table(
File "C:\Anaconda3\envs\pstubtst\lib\site-packages\pandas\core\reshape\pivot.py", line 155, in __internal_pivot_table
data = data[to_filter]
File "C:\Anaconda3\envs\pstubtst\lib\site-packages\pandas\core\frame.py", line 3811, in __getitem__
indexer = self.columns._get_indexer_strict(key, "columns")[1]
File "C:\Anaconda3\envs\pstubtst\lib\site-packages\pandas\core\indexes\base.py", line 6105, in _get_indexer_strict
keyarr = com.asarray_tuplesafe(keyarr)
File "C:\Anaconda3\envs\pstubtst\lib\site-packages\pandas\core\common.py", line 245, in asarray_tuplesafe
result = np.asarray(values, dtype=dtype)
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (4,) + inhomogeneous part.
Expected Behavior
We should trap the error from numpy 1.24.0
This was picked up with pandas-stubs. Created PR to pin numpy there pandas-dev/pandas-stubs#475
Installed Versions
INSTALLED VERSIONS
commit : 8dab54d
python : 3.9.13.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19045
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.5.2
numpy : 1.24.0
pytz : 2022.1
dateutil : 2.8.2
setuptools : 62.3.2
pip : 22.3.1
Cython : None
pytest : 7.1.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.6.2
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : 1.4.41
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None