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Should DataFrames be treated as a first-class schema (alongside Text, Audio, Images)?
If your feature will improve HUB
Even though Hub is designed for unstructured datasets, many data science projects still rely on DataFrames in some form or fashion. While there may be better solutions for large scale tabular data analysis, Hub should aim for feature parity.
Ultimately, the goal is to create a package familiar to data scientists, and supporting DataFrames is a big step towards that goal.
Description of the possible solution
Since a DataFrame is a collection of numpy arrays, a DataFrame schema could be assembled with existing Schemas (eg Tensors).
The text was updated successfully, but these errors were encountered:
🚨🚨 Feature Request
Should DataFrames be treated as a first-class schema (alongside Text, Audio, Images)?
If your feature will improve
HUB
Even though Hub is designed for unstructured datasets, many data science projects still rely on DataFrames in some form or fashion. While there may be better solutions for large scale tabular data analysis, Hub should aim for feature parity.
Ultimately, the goal is to create a package familiar to data scientists, and supporting DataFrames is a big step towards that goal.
Description of the possible solution
Since a DataFrame is a collection of numpy arrays, a DataFrame schema could be assembled with existing Schemas (eg Tensors).
The text was updated successfully, but these errors were encountered: