LaverdeS/Multivariate-Time-Series-Classification

clean colab notebook

Closed this issue · 6 comments

Some figures in the notebook are displayed twice. The return for plot_outliers_in is a figure that should be wrapped around plt.show() to avoid this.

Can you please help me with this error?
image

Hi @Soumya-Kushwaha 🎊! For now, if you are running a jupyter locally, you would have to move the notebook to the python folder to debug, or open it on google colab and upload the 3 python scripts there. Nevertheless, I just realised that you will face other errors because you don't have sample data to test it with. It will be on a sample-data folder soon! I will be sure to ping you when is there. Thank you for your interest!

Alright.
I'll be happy to contribute whenever possible!

Hi @Soumya-Kushwaha!

  • I created a sample-data/tinder folder with some .json files that the notebook uses. The dataset is part of a pending publication so I just shared 20% of it and I kindly ask you to keep that in mind 🤗.
  • I preferred to create a google colab that installs the repo so you can just run every cell without any path-related issues. Here is the link (all notebook links for this issue have been also updated).
  • Your gmail account has been granted edit permissions so you can simply make the necessary changes in the colab and paste a snippet of the solution(s) in a Pull Request (you can create a new branch but are not forced to). Name the PR/branch however you want.
  • You need to do changes in two cells inside the OUTLIER DETECTION + REMOVAL USING IQR > Lenghts section of the notebook.

@LaverdeS I tried but seems like I am unable to help you here. I can't understand what should be done to avoid those double plots.
I believe I may contribute some other time!

@Soumya-Kushwaha No problem, there are some other issues if you are interested. You can always write me a comment if you need help or me to clarify the task. Thanks again for your interest.

-- The issue has been closed, colab notebook is now updated wrapping figures with plt.show(--figure--)