# Code Error caused by defined image\_name in M2\_UGL\_1

**URL:** <https://community.deeplearning.ai/t/code-error-caused-by-defined-image-name-in-m2-ugl-1/888448>\
**Category:** Agentic AI\
**Tags:** week-module-2, dl-ai-learning-platform\
**Created:** [February 7, 2026, 3:47am UTC](https://community.deeplearning.ai/t/code-error-caused-by-defined-image-name-in-m2-ugl-1/888448 "2026-02-07T03:47:51Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![haohao](https://avatars.discourse-cdn.com/v4/letter/h/bc8723/32.png) [@haohao](https://community.deeplearning.ai/u/haohao)\
**Post date:** [February 7, 2026, 3:47am UTC](https://community.deeplearning.ai/t/code-error-caused-by-defined-image-name-in-m2-ugl-1/888448/1 "2026-02-07T03:47:51Z")

</div>

The generated first version code does not work when wrapped into run\_workflow() function, although everything works in the previous codes. The error is as below. The only difference I found compared to previous code is just the image\_basename=“drink\_sales”. When I change this name to some others. The error has gone. However, the generated chart looks quite different with different names…

With image\_basename=“drink\_sales”, the generated code has one line for date formatting which seems causing the error.

df[‘date’] = pd.to\_datetime(df[‘date’] + ’ ’ + df[‘year’].astype(str))

Although prompt change will definitely affect result, the resulting error sometimes seems unpredictable…

```auto
TypeError Traceback (most recent call last)
Cell In[14], line 8
      5 image_basename="drink_sales"
      7 # Run the complete agentic workflow
----> 8 _ = run_workflow(
      9 dataset_path="coffee_sales.csv",
     10 user_instructions=user_instructions,
     11 generation_model=generation_model,
     12 reflection_model=reflection_model,
     13 image_basename=image_basename
     14 )

Cell In[9], line 41, in run_workflow(dataset_path, user_instructions, generation_model, reflection_model, image_basename)
     39 initial_code = match.group(1).strip()
     40 exec_globals = {"df": df}
---> 41 exec(initial_code, exec_globals)
     42 utils.print_html(out_v1, is_image=True, title="Generated Chart (V1)")
     44 # 3) Reflect on V1 (image + original code) to get feedback and refined code (V2)

File <string>:5

File /usr/local/lib/python3.11/site-packages/pandas/core/ops/common.py:76, in _unpack_zerodim_and_defer.<locals>.new_method(self, other)
     72 return NotImplemented
     74 other = item_from_zerodim(other)
---> 76 return method(self, other)

File /usr/local/lib/python3.11/site-packages/pandas/core/arraylike.py:186, in OpsMixin. __add__ (self, other)
     98 @unpack_zerodim_and_defer(" __add__")
     99 def __add__ (self, other):
    100 """
    101 Get Addition of DataFrame and other, column-wise.
    102 
   (...)
    184 moose 3.0 NaN
    185 """
--> 186 return self._arith_method(other, operator.add)

File /usr/local/lib/python3.11/site-packages/pandas/core/series.py:6154, in Series._arith_method(self, other, op)
   6152 def _arith_method(self, other, op):
   6153 self, other = self._align_for_op(other)
-> 6154 return base.IndexOpsMixin._arith_method(self, other, op)

File /usr/local/lib/python3.11/site-packages/pandas/core/base.py:1391, in IndexOpsMixin._arith_method(self, other, op)
   1388 rvalues = np.arange(rvalues.start, rvalues.stop, rvalues.step)
   1390 with np.errstate(all="ignore"):
-> 1391 result = ops.arithmetic_op(lvalues, rvalues, op)
   1393 return self._construct_result(result, name=res_name)

File /usr/local/lib/python3.11/site-packages/pandas/core/ops/array_ops.py:273, in arithmetic_op(left, right, op)
    260 # NB: We assume that extract_array and ensure_wrapped_if_datetimelike
    261 # have already been called on `left` and `right`,
    262 # and `maybe_prepare_scalar_for_op` has already been called on `right`
    263 # We need to special-case datetime64/timedelta64 dtypes (e.g. because numpy
    264 # casts integer dtypes to timedelta64 when operating with timedelta64 - GH#22390)
    266 if (
    267 should_extension_dispatch(left, right)
    268 or isinstance(right, (Timedelta, BaseOffset, Timestamp))
   (...)
    271 # Timedelta/Timestamp and other custom scalars are included in the check
    272 # because numexpr will fail on it, see GH#31457
--> 273 res_values = op(left, right)
    274 else:
    275 # TODO we should handle EAs consistently and move this check before the if/else
    276 # (https://github.com/pandas-dev/pandas/issues/41165)
    277 # error: Argument 2 to "_bool_arith_check" has incompatible type
    278 # "Union[ExtensionArray, ndarray[Any, Any]]"; expected "ndarray[Any, Any]"
    279 _bool_arith_check(op, left, right) # type: ignore[arg-type]

TypeError: unsupported operand type(s) for +: 'DatetimeArray' and 'str'
"

```

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<div class="post-metadata">

**Author:** ![reinoudbosch](https://avatars.discourse-cdn.com/v4/letter/r/22d042/32.png) [@reinoudbosch](https://community.deeplearning.ai/u/reinoudbosch)\
**Post date:** [February 12, 2026, 1:45am UTC](https://community.deeplearning.ai/t/code-error-caused-by-defined-image-name-in-m2-ugl-1/888448/2 "2026-02-12T01:45:32Z")

</div>

Hi haohao,

Thanks for reporting this. I got the same error using the original prompt. After I added “Check operand types carefully to avoid errors” everything worked well.

Comes to show that intelligence can be rather interactive…