Notebook: AttributeError: 'LazyConfigValue' object has no attribute 'lower'

[mikkokotila]

This error is arising when I run a notebook in conda env that I had previously created in another env.

AttributeError                            Traceback (most recent call last)
~/miniconda3/envs/wip_conda/lib/python3.6/site-packages/IPython/core/formatters.py in __call__(self, obj)
    343             method = get_real_method(obj, self.print_method)
    344             if method is not None:
--> 345                 return method()
    346             return None
    347         else:

~/miniconda3/envs/wip_conda/lib/python3.6/site-packages/pandas/core/frame.py in _repr_html_(self)
    647         # display HTML, so this check can be removed when support for
    648         # IPython 2.x is no longer needed.
--> 649         if console.in_qtconsole():
    650             # 'HTML output is disabled in QtConsole'
    651             return None

~/miniconda3/envs/wip_conda/lib/python3.6/site-packages/pandas/io/formats/console.py in in_qtconsole()
    121             ip.config.get('KernelApp', {}).get('parent_appname', "") or
    122             ip.config.get('IPKernelApp', {}).get('parent_appname', ""))
--> 123         if 'qtconsole' in front_end.lower():
    124             return True
    125     except NameError:

AttributeError: 'LazyConfigValue' object has no attribute 'lower'

[chadbot]

I'm having this issue too, specifically when trying to print Pandas DataFrames. I've noticed that DataFrames print fine when I've only loaded Pandas (import pandas as pd). But when I also import spacy, I get this error.

I am running JupyterLab v. 0.35.4, Python v. 3.7.2, and Pandas v. 0.24.0 inside a Pipenv virtual environment on MacOS 10.14.2. Happy to provide other information if helpful.

[A2ed]

This also occurred to me this morning when displaying a data frame in Jupyter Lab. I'm running it through a conda environment and the import is handled by fastai. I tried importing Pandas on its own and it works fine. My set up is similar to what chadbot lists ^^

[sahilseth]

I have exact same experience as @A2ed
Also, the sequence of import (importing pandas before fastai), does not seem to help.

[mikkokotila]

For me removing the dataframe / series returns from my functions "resolved" the issue. I'm also having spacy in the same env and same imports, so will check that as well later today.

[viniciuscadorereed]

I have exactly the same issue here. I haven't looked the spacy code to understand what it is causing the issue, however, as a quite dirty workaround, it is possible to add the following line:

get_ipython().config.get('IPKernelApp', {})['parent_appname'] = ""

This should avoid panda to break.

[Etang21]

I also get the issue when I have both pandas and spacy, like @chadbot did.

[jmunar]

As a simple workaround until the issue is fixed:

from IPython.display import HTML
HTML(df)

[bhaskar-dhariyal]

I'm also having same issue

[CloudCray]

Same problem here.

The workaround from @viniciuscadorereed sets notebook behavior back to normal for me (fixes default dataframe view in output cells - don't have to call HTML(df) for each display). Execute this line anywhere prior to displaying a dataframe:

get_ipython().config.get('IPKernelApp', {})['parent_appname'] = ""

Current setup:

• python 3.6.6
• pandas 0.24.0
• jupyter 4.4.0
• spacy 2.0.18

[ines]

This will be resolved in the next update of pandas and we'll also be issuing a workaround for spaCy. If you're interested, see here for some background on the problem: pandas-dev/pandas#25036

[pechyonkin]

Same problem here.

The workaround from @viniciuscadorereed sets notebook behavior back to normal for me (fixes default dataframe view in output cells - don't have to call HTML(df) for each display). Execute this line anywhere prior to displaying a dataframe:

get_ipython().config.get('IPKernelApp', {})['parent_appname'] = ""

This solved the issue for me.

[mdalvi]

from IPython.display import HTML

Does not work in case of Null in DataFrame!

ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().