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{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Expand use of sql parsing string expressions in DataFrame","articleBody":"**Is your feature request related to a problem or challenge? Please describe what you are trying to do.**\n\nThis is a follow on to https://github.com/apache/datafusion-python/issues/1273\n\nThere are a number of places where it would be convenient to pass SQL strings as expressions. For example, it would be nice to do\n\n```\ndf.select(\n    \"a\",\n    \"a - b\",\n    col(\"c\"),\n)\n```\n\nThis should intuitively know that we are getting column `a`, followed by `col(\"a\") - col(\"b\")` followed by column 'c'.\n\n**Describe the solution you'd like**\n\nUsing the sql parsing on the DataFrame make the following functions handle SQL strings. We must be *very* careful that we do not break things like cases where users have a column name that is not SQL parseable.\n\n**Describe alternatives you've considered**\n\nStatus quo\n\n**Additional context**\n\nDataFrame functions to update:\n\n- [ ] select\n- [ ] remove `select_exprs`\n- [x] `with_column` #1284 \n- [ ] `with_columns` #1286 \n- [ ] aggregate\n- [x] `repartition_by_hash` #1285\n\nWe do **not** want to apply this treatment to joins because there is no easy way to know *which* DataFrame to perform the SQL parsing against.\n","author":{"url":"https://github.com/timsaucer","@type":"Person","name":"timsaucer"},"datePublished":"2025-10-15T13:50:30.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":11},"url":"https://github.com/1278/datafusion-python/issues/1278"}