Nagato-Yuzuru commented on code in PR #22702:
URL: https://github.com/apache/datafusion/pull/22702#discussion_r3342615087
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datafusion/core/src/dataframe/mod.rs:
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@@ -2527,6 +2528,78 @@ impl DataFrame {
.collect()
}
+ /// Fill NaN values in specified columns with a given value
+ /// If no columns are specified (empty vector), applies to all columns
+ /// Only fills if the value can be cast to the column's type
+ ///
+ /// # Arguments
+ /// * `value` - Value to fill NaNs with
+ /// * `columns` - List of column names to fill. If empty, fills all
columns.
+ ///
+ /// # Example
+ /// ```
+ /// # use datafusion::prelude::*;
+ /// # use datafusion::error::Result;
+ /// # use datafusion_common::ScalarValue;
+ /// # #[tokio::main]
+ /// # async fn main() -> Result<()> {
+ /// let ctx = SessionContext::new();
+ /// let df = ctx
+ /// .read_csv("tests/data/example.csv", CsvReadOptions::new())
+ /// .await?;
+ /// // Fill NaN in only columns "a" and "c":
+ /// let df = df.fill_nan(ScalarValue::from(0.0), vec!["a".to_owned(),
"c".to_owned()])?;
+ /// // Fill NaN across all columns:
+ /// let df = df.fill_nan(ScalarValue::from(0.0), vec![])?;
+ /// # Ok(())
+ /// # }
+ /// ```
+ #[expect(clippy::needless_pass_by_value)]
+ pub fn fill_nan(
+ &self,
+ value: ScalarValue,
+ columns: Vec<String>,
+ ) -> Result<DataFrame> {
Review Comment:
Thanks review. I modeled `fill_nan` on the existing
[fill_null](https://docs.rs/datafusion/latest/datafusion/dataframe/struct.DataFrame.html#method.fill_null),
which also takes Vec<String>, so changing just `fill_nan` would leave the two
siblings inconsistent.
I agree with aligning better, but changing fill_null's signature is a
breaking(e.g. `df.fill_null(val, vec!["a".to_string()])`). So maybe we not
bundle it into this PR? Could keep fill_nan matching fill_null here and migrate
both in a follow-up?
Also unnest_columns uses `&[&str]` while drop_columns uses `&[impl
Into<Column>]`. Do we have any preference which to standardize on?
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