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First of all, thanks for this awesome package. May I ask, can you please add a way of dealing with nans (or missing values) in the dataset, especially if the columns are a numeric type of some sort. This could be dropping columns or rows that have nans, or maybe imputing a user defined values.
Thank you,
J.
The text was updated successfully, but these errors were encountered:
Hi,
First of all, thanks for this awesome package. May I ask, can you please add a way of dealing with nans (or missing values) in the dataset, especially if the columns are a numeric type of some sort. This could be dropping columns or rows that have nans, or maybe imputing a user defined values.
Thank you,
J.
The text was updated successfully, but these errors were encountered: