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As we know many data sources have missing values. After reading the data source (csv file for example), is there a way to fill in missing entries in the DataFrame with an arbitrary value. As a comparison with Python Pandas DataFrame we can just call dataframe['some_column_name'].fillna('Missing')
Is that possible? Also, is there a forum or a user group for discussions available where we can post questions like these?
Thanks
The text was updated successfully, but these errors were encountered:
There are several algorithms to handle missing values in package smile.feature.imputation. SimpleImputer may be used to fill a fixed value. I would suggest trying other advanced algorithms in the package too.
For simplicity, I will add some methods like fillna to Vector classes.
As we know many data sources have missing values. After reading the data source (csv file for example), is there a way to fill in missing entries in the DataFrame with an arbitrary value. As a comparison with Python Pandas DataFrame we can just call
dataframe['some_column_name'].fillna('Missing')
Is that possible? Also, is there a forum or a user group for discussions available where we can post questions like these?
Thanks
The text was updated successfully, but these errors were encountered: