Skip to content

BUG: DataFrame.to_markdown exception when a cell has numpy.array type #61337

Open
@omarsaad98

Description

@omarsaad98

Pandas version checks

  • 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

results = pd.DataFrame({"col1": [np.array(["hello","world"], dtype=object), "world"]})
results.to_markdown()

Issue Description

When a dataframe contains a cell with type numpy.array, the to_markdown function will fail. The exact issue is due to differing behavior between any other value and numpy arrays, but the reason I think this is a pandas issue is because an assumption is made about the value:

def _is_separating_line(row):
    row_type = type(row)
    is_sl = (row_type == list or row_type == str) and (
        (len(row) >= 1 and row[0] == SEPARATING_LINE) # <- compares row[0] to a string
        or (len(row) >= 2 and row[1] == SEPARATING_LINE)
    )
    return is_sl

Anything that isn't a string will normally result in this comparison resolving to False, but this should be explicit to avoid strange datatypes causing undefined behavior.

Stack trace:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[69], line 3
      1 import numpy as np
      2 results = pd.DataFrame({"col1": [np.array(["hello","world"], dtype=object), "world"]})
----> 3 results.to_markdown()

File [...]\.venv\Lib\site-packages\pandas\util\_decorators.py:333, in deprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper(*args, **kwargs)
    327 if len(args) > num_allow_args:
    328     warnings.warn(
    329         msg.format(arguments=_format_argument_list(allow_args)),
    330         FutureWarning,
    331         stacklevel=find_stack_level(),
    332     )
--> 333 return func(*args, **kwargs)

File [...]\.venv\Lib\site-packages\pandas\core\frame.py:2984, in DataFrame.to_markdown(self, buf, mode, index, storage_options, **kwargs)
   2982 kwargs.setdefault("showindex", index)
   2983 tabulate = import_optional_dependency("tabulate")
-> 2984 result = tabulate.tabulate(self, **kwargs)
   2985 if buf is None:
   2986     return result

File [...]\.venv\Lib\site-packages\tabulate\__init__.py:2048, in tabulate(tabular_data, headers, tablefmt, floatfmt, intfmt, numalign, stralign, missingval, showindex, disable_numparse, colalign, maxcolwidths, rowalign, maxheadercolwidths)
   2045 if tabular_data is None:
   2046     tabular_data = []
-> 2048 list_of_lists, headers = _normalize_tabular_data(
   2049     tabular_data, headers, showindex=showindex
   2050 )
   2051 list_of_lists, separating_lines = _remove_separating_lines(list_of_lists)
   2053 if maxcolwidths is not None:

File [...]\.venv\Lib\site-packages\tabulate\__init__.py:1471, in _normalize_tabular_data(tabular_data, headers, showindex)
   1469 headers = list(map(str, headers))
   1470 #    rows = list(map(list, rows))
-> 1471 rows = list(map(lambda r: r if _is_separating_line(r) else list(r), rows))
   1473 # add or remove an index column
   1474 showindex_is_a_str = type(showindex) in [str, bytes]

File [...]\.venv\Lib\site-packages\tabulate\__init__.py:1471, in _normalize_tabular_data.<locals>.<lambda>(r)
   1469 headers = list(map(str, headers))
   1470 #    rows = list(map(list, rows))
-> 1471 rows = list(map(lambda r: r if _is_separating_line(r) else list(r), rows))
   1473 # add or remove an index column
   1474 showindex_is_a_str = type(showindex) in [str, bytes]

File [...]\.venv\Lib\site-packages\tabulate\__init__.py:107, in _is_separating_line(row)
    104 def _is_separating_line(row):
    105     row_type = type(row)
    106     is_sl = (row_type == list or row_type == str) and (
--> 107         (len(row) >= 1 and row[0] == SEPARATING_LINE)
    108         or (len(row) >= 2 and row[1] == SEPARATING_LINE)
    109     )
    110     return is_sl

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Expected Behavior

to_markdown converts this numpy array to string and outputting a markdown normally. Instead there's an exception

Installed Versions

INSTALLED VERSIONS

commit : 0691c5c
python : 3.13.1
python-bits : 64
OS : Windows
OS-release : 11
Version : 10.0.26100
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.2.3
numpy : 2.2.4
pytz : 2025.2
dateutil : 2.9.0.post0
pip : 25.0.1
Cython : None
sphinx : None
IPython : 9.0.2
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.13.3
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.6
lxml.etree : None
matplotlib : 3.10.1
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 19.0.1
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.2
qtpy : None
pyqt5 : None

Metadata

Metadata

Assignees

Labels

BugDependenciesRequired and optional dependenciesIO DataIO issues that don't fit into a more specific labelNeeds DiscussionRequires discussion from core team before further actionNested DataData where the values are collections (lists, sets, dicts, objects, etc.).

Type

No type

Projects

No projects

Milestone

No milestone

Relationships

None yet

Development

No branches or pull requests

Issue actions