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Here is an idea if the underlying Dataframe is based on a catalog_file and in case it is opened and loaded with pandas read_csv.
Is your feature request related to a problem? Please describe.
The catalog file of a catalog can be very large and contain many columns. It quickly fills user memory when the dataframe is loaded.
Describe the solution you'd like
pandas read_csv allows to set kwarg usecols. One could assemble all columns from the description and set it as values. That reduces the memory requirements.
The text was updated successfully, but these errors were encountered:
Here is an idea if the underlying Dataframe is based on a
catalog_file
and in case it is opened and loaded with pandasread_csv
.Is your feature request related to a problem? Please describe.
The catalog file of a catalog can be very large and contain many columns. It quickly fills user memory when the dataframe is loaded.
Describe the solution you'd like
pandas
read_csv
allows to set kwargusecols
. One could assemble all columns from the description and set it as values. That reduces the memory requirements.The text was updated successfully, but these errors were encountered: