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BUG: pd.Series() constructor with 2d NumPy array raises bare Exception #35744

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@micahjsmith

Description

@micahjsmith
  • I have checked that this issue has not already been reported.

  • I have confirmed this bug exists on the latest version of pandas.

  • (optional) I have confirmed this bug exists on the master branch of pandas.


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Code Sample, a copy-pastable example

import pandas as pd
import numpy as np
arr = np.random.rand(10, 4)
pd.Series(arr)

I get this output

---------------------------------------------------------------------------
Exception                                 Traceback (most recent call last)
<ipython-input-4-974eca309da1> in <module>
      2 import numpy as np
      3 arr = np.random.rand(10, 4)
----> 4 pd.Series(arr)

~/.pyenv/versions/3.8.3/envs/census/lib/python3.8/site-packages/pandas/core/series.py in __init__(self, data, index, dtype, name, copy, fastpath)
    325                     data = data.copy()
    326             else:
--> 327                 data = sanitize_array(data, index, dtype, copy, raise_cast_failure=True)
    328 
    329                 data = SingleBlockManager.from_array(data, index)

~/.pyenv/versions/3.8.3/envs/census/lib/python3.8/site-packages/pandas/core/construction.py in sanitize_array(data, index, dtype, copy, raise_cast_failure)
    490     elif subarr.ndim > 1:
    491         if isinstance(data, np.ndarray):
--> 492             raise Exception("Data must be 1-dimensional")
    493         else:
    494             subarr = com.asarray_tuplesafe(data, dtype=dtype)

Exception: Data must be 1-dimensional

Problem description

Yes, creating a series from an array is invalid. But the problem is that a bare Exception is raised for this. A different exception type like ValueError is expected. User code should [mostly] never be catching bare Exceptions, but may reasonable catch ValueErrors or TypeErrors from pandas routines.

I'm not entirely sure of the rationale for raising a bare Exception in the sanitize_array method, I started looking through the git blame but didn't go back that far.

I think a PR that just raises a ValueError in sanitize_array would be an appropriate fix and I can create that if given the thumbs up.

Expected Output

A ValueError is raised, that can be caught be user code.

Output of pd.show_versions()

INSTALLED VERSIONS

commit : d9fff27
python : 3.8.3.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Sun Jul 5 00:43:10 PDT 2020; root:xnu-6153.141.1~9/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.1.0
numpy : 1.19.0
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 49.2.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.0
fastparquet : None
gcsfs : None
matplotlib : 3.3.0
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.5.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None

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ConstructorsSeries/DataFrame/Index/pd.array ConstructorsError ReportingIncorrect or improved errors from pandasSeriesSeries data structure

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