Common issues

TypeError: _plot_histogram() got an unexpected keyword argument ‘title’

This error occurs when using outdated versions of the package.

Ensure that you are using the latest version, and when in a notebook, ensure that you’ve restarted the kernel when needed. Also make sure that you install in the right Python environment (please use !{sys.executable} -m pip install -U pandas-profiling!). More information on installing Python packages directly from a notebook: ‘Installing Python Packages from a Jupyter Notebook’.

Related GitHub issues:

Conda installation defaults to v1.4.1

Some users experience that conda install -c conda-forge pandas-profiling defaults to 1.4.1.

If creating a new environment with a fresh installation does not resolve this issue, or the current environment must be kept, installing a specific version is one alternative to try: conda install -c conda-forge pandas-profiling=3.2.0. If it fails with an UnsatisfiableError that suggests dependent packages are either missing or incompatible, then further intervention is required to resolve the environment issue. However, conda error messages in this regard may be too cryptic or insufficient to pinpoint the culprit, therefore you may have to resort to an alternate means of troubleshooting e.g using the Mamba Package Manager. For an illustration of this approach see this issue.

Related GitHub issues:

Jupyter “IntSlider(value=0)”

When in a Jupyter environment, if only text such as IntSlider(value=0) or (children=(IntSlider(value=0, description='x', max=1), Output()), _dom_classes=('widget-interact',)) is shown, then the Jupyter Widgets are not activated. The Installation page contains instructions on how to resolve this problem.

MemoryError: Unable to allocate… when profiling datasets with very large values

A memory error that comes up when profiling datasets with large outliers (even if the dataset itself is small), which is due to an underlying bug in numpy, used to build an histogram. Although some workarounds are suggested on numpy’s GitHub, the bug is not yet fixed. One workaround is to filter out large outliers prior to report computation.

Related StackOverflow questions:

TypeError: concat() got an unexpected keyword argument ‘join_axes’

This issue happens when, for instance, a report is converted to an iframe via ProfileReport.to_notebook_iframe() in a notebook environment (Google Colab, Jupyter Lab, Jupyter Notebook, etc).

This is due to an incompatibility in an old package version (particularly 1.4.1, which a conda installation may default to, as discussed above). Upgrading the package to a newer version (either via pip install pandas-profiling==3.2.0 or conda install -c conda-forge pandas-profiling=3.2.0 fixes the issue.

Related GitHub issues: