ValueError: Multi-dimensional indexing (e.g. `obj[:, None]`) is no longer supported. Convert to a numpy array before indexing instead

Problem:

ValueError: Multi-dimensional indexing (e.g. `obj[:, None]`) is no longer supported. Convert to a numpy array before indexing instead.

Potential Causes and Solutions:

• Incompatibility between Matplotlib, Pandas, and Seaborn:
  • Ensure that you have compatible versions of these libraries. Refer to the GitHub issue for more details: https://github.com/mwaskom/seaborn/issues/3312
  • Consider upgrading or downgrading the packages based on compatibility with other libraries.
• Using Pandas DataFrames Directly in Matplotlib:
  • Pandas DataFrames have undergone changes in their indexing behavior, resulting in the error. To resolve this:
  • Convert the DataFrame to a NumPy array using df.to_numpy().
  • Use the NumPy array in the Matplotlib plotting function.

  plt.plot(df['var_name'].to_numpy(), df['other_var_name'].to_numpy())
  

• Using .values Attribute:
  • While df['var_name'].values can be used as a workaround, it is not recommended.
  • Use df['var_name'].to_numpy() instead, as it is the preferred method for converting DataFrames to NumPy arrays.
• Incompatibility with Different NumPy Versions:
  • Ensure that your NumPy version is compatible with the other libraries you are using.
  • Consider upgrading or downgrading NumPy based on compatibility requirements.
• Multi-dimensional Indexing:
  • Avoid using multi-dimensional indexing (e.g., obj[:, None]) on Pandas objects when plotting with Matplotlib.
  • Convert the objects to NumPy arrays before performing such indexing operations.
• Modifying utils.py:
  • (Not Recommended) As a workaround, you can modify the utils.py file to allow multi-dimensional indexing, but this is not a recommended solution and may cause unexpected issues.
  • Follow the steps mentioned in the provided solution to modify utils.py, but proceed with caution.