RishavTiwari25 opened a new pull request, #26255:
URL: https://github.com/apache/datafusion/pull/26255
## Which issue does this PR close?
- Closes #25829.
## Rationale for this change
`DataFrame::fill_null` and `DataFrame::fill_nan` fail with `FieldNotFound`
on any DataFrame that has a column whose name is not a plain lowercase
identifier (for example `Name` or `a.b`), even when that column is not in the
list being filled.
`fill_columns` rebuilt every column of the projection with
`col(field.name())`. `col` parses its argument as a SQL identifier, so `Name`
was normalized to `name` and `a.b` was split into table `a`, column `b`.
Neither resolves against the schema.
## What changes are included in this PR?
`fill_columns` now iterates the schema's `(qualifier, field)` pairs and
builds each projection entry as `Expr::Column(Column::from((qualifier,
field)))`, the same way the other DataFrame methods in this file reference
their columns. The fill logic itself is unchanged.
## What is the testing strategy for this PR?
New test `test_fill_null_and_nan_with_non_normalized_column_names` in
`datafusion/core/tests/dataframe/mod.rs` builds a DataFrame with columns
`Name`, `a.b` and `v`, and calls `fill_null` on `v` and `Name` and `fill_nan`
on `a.b`. It fails on `main` with the `FieldNotFound { name: "name" }` error
from the issue and passes with this change. The existing `fill_null` /
`fill_nan` tests still pass.
## Are there any user-facing changes?
`fill_null` and `fill_nan` work on DataFrames with mixed-case or dotted
column names. No API change.
I used an AI coding assistant while working on this change; I have read the
diff and the test and can walk through them.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
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