[GitHub] [arrow] bu2 edited a comment on pull request #9024: ARROW-11044: [C++] Add "replace" kernel

[GitBox <gi...@apache.org>]

bu2 edited a comment on pull request #9024:
URL: https://github.com/apache/arrow/pull/9024#issuecomment-754871329


   Wow, I was not expecting such brainstorming on the name of this kernel. My initial intent was to mimic pandas.Series.replace(to_replace, value), where in C++ to_replace could be an BooleanArray mask (same length as input array) which trigger value replacement => So this kernel could be used after any combination of Compare and Boolean operations to implement specific replacement logic.
   
   This could be extended to another implementation where to_replace could be an IntegerArray (length <= as input array) of indexes to replace.
   
   Here is how I use "replace" in combination with "is_nan" ([ARROW-11043](https://github.com/apache/arrow/pull/9023)) to implement fillna():
   
   ```
   template <typename value_type>
   std::shared_ptr<DataFrame> DataFrame::fillna(value_type value) {
       auto outdf = std::make_shared<DataFrame>();
       ...
       ...
       for (int i = 0 ; i < this->table_->num_columns() ; ++i) {
           auto field = this->table_->schema()->field(i);
           auto chunked_array = this->table_->column(i);
           auto value_datum = arrow::compute::Cast(arrow::Datum(value), chunked_array->type()).ValueOrDie();
           auto nulls = arrow::compute::IsNull(chunked_array).ValueOrDie();
           auto nans = arrow::compute::IsNan(chunked_array).ValueOrDie().chunked_array();
           auto to_replace = arrow::compute::Or(nulls, nans).ValueOrDie();
           auto clean_chunked_array = arrow::compute::Replace(chunked_array, to_replace, value_datum).ValueOrDie().chunked_array();
           outdf->table_ = outdf->table_->AddColumn(i, field, clean_chunked_array).ValueOrDie();
       }
   
       return outdf;
   }
   ```


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