Repository: evidentlyai/evidently
Issue: Query on Embeddings Drift Practical
Root cause: Documentation Deficiency

I hope this message finds you well. I've been exploring the provided code for embeddings drift, particularly 
: '[how_to_calculate_embeddings_drift.ipynb](https://github.com/evidentlyai/evidently/blob/main/examples/how_to_questions/how_to_calculate_embeddings_drift.ipynb)'

issue in 'how_to_calculate_embeddings_drift.ipynb':

## 1. Choice of Data
The code seems to use image data for embeddings drift calculation. Could you please clarify why image data was chosen instead of actual embeddings data? Understanding this choice would be beneficial.

## 2. 'small_subset' and 'big_subset, 
The notebook mentions 'small_subset' and 'big_subset,' but there isn't an explanation on how to separate columns of embeddings into these subsets or the rationale behind it.

## 3. Data shape
It expects rows to be more than columns, following this way, it should be (embeddings_dim * data_samples) : each  columns is a data sample of, lets say 768 dims.
  -> let's say, reference data is having 1000 [shape: (768,1000) ] data samples and new data is having 200 samples [ shape: (768,200) ]
      Now, it expects both the ref and new data to have same number of columns, as well as column names.
      shows:
            [ WARNING:root:Column 20 isn't present in data. Skipping it.
             WARNING:root:Column 21 isn't present in data. Skipping it.
             WARNING:root:Column 22 isn't present in data. Skipping it.
             WARNING:root:Column 23 isn't present in data. Skipping it.
             WARNING:root:Column 24 isn't present in data. Skipping it.
             WARNING:root:Column 25 isn't present in data. Skipping it.
             WARNING:root:Column 26 isn't present in data. Skipping it.
             WARNING:root:Column 27 isn't present in data. Skipping it.
             WARNING:root:Column 28 isn't present in data. Skipping it.
             WARNING:root:Column 29 isn't present in data. Skipping it.
             WARNING:root:Column 20 isn't present in data. Skipping it.
             WARNING:root:Column 21 isn't present in data. Skipping it.
             WARNING:root:Column 22 isn't present in data. Skipping it.
             WARNING:root:Column 23 isn't present in data. Skipping it.
             WARNING:root:Column 24 isn't present in data. Skipping it.
             WARNING:root:Column 25 isn't present in data. Skipping it.
             WARNING:root:Column 26 isn't present in data. Skipping it.
             WARNING:root:Column 27 isn't present in data. Skipping it.
             WARNING:root:Column 28 isn't present in data. Skipping it.
             WARNING:root:Column 29 isn't present in data. Skipping it. ]

      -> Now how can I have same number of data samples in Reference as well as new data?

      -> And if not if Ref data is having 1000 columns and New data is having 200 columns, it will consider first 200 columns of ref data and compare with them, having the same column name in both Ref and New data.

### In the provided code same number of rows and columns are taken in the reference data and the new data, that's why it is working perfectly.


These aspects have left me with some confusion, and I wanted to ensure that I am interpreting the code correctly. Your guidance and clarification would be greatly appreciated.

Thank you for your time and assistance.

Best Regards,
Yatrik