feat(rust!): Change DataFrame.is_empty() to check height == 0 instead of width == 0

crates/polars-core/src/frame/explode.rs

@@ -38,7 +38,7 @@ impl DataFrame {
     pub fn explode_impl(&self, mut columns: Vec<Series>) -> PolarsResult<DataFrame> {
         polars_ensure!(!columns.is_empty(), InvalidOperation: "no columns provided in explode");
         let mut df = self.clone();
-        if self.height() == 0 {
+        if self.is_empty() {
             for s in &columns {
                 df.with_column(s.explode()?)?;
             }

crates/polars-core/src/frame/group_by/mod.rs

@@ -76,7 +76,7 @@ impl DataFrame {
                 .cloned()
                 .collect::<Vec<_>>();
             if by.is_empty() {
-                let groups = if self.height() == 0 {
+                let groups = if self.is_empty() {
                     vec![]
                 } else {
                     vec![[0, self.height() as IdxSize]]

crates/polars-core/src/frame/mod.rs

@@ -729,7 +729,7 @@ impl DataFrame {
         self.shape().0
     }
 
-    /// Check if the [`DataFrame`] is empty.
+    /// Returns `true` if the [`DataFrame`] contains no rows.
     ///
     /// # Example
     ///
@@ -744,7 +744,7 @@ impl DataFrame {
     /// # Ok::<(), PolarsError>(())
     /// ```
     pub fn is_empty(&self) -> bool {
-        self.columns.is_empty()
+        self.height() == 0
     }
 
     /// Add columns horizontally.
@@ -779,7 +779,7 @@ impl DataFrame {
         // this DataFrame is already modified when an error occurs.
         for col in columns {
             polars_ensure!(
-                col.len() == self.height() || self.height() == 0,
+                col.len() == self.height() || self.is_empty(),
                 ShapeMismatch: "unable to hstack Series of length {} and DataFrame of height {}",
                 col.len(), self.height(),
             );
@@ -1146,7 +1146,7 @@ impl DataFrame {
                 series = series.new_from_index(0, height);
             }
 
-            if series.len() == height || df.is_empty() {
+            if series.len() == height || df.get_columns().is_empty() {
                 df.add_column_by_search(series)?;
                 Ok(df)
             }
@@ -1219,7 +1219,7 @@ impl DataFrame {
             series = series.new_from_index(0, height);
         }
 
-        if series.len() == height || self.is_empty() {
+        if series.len() == height || self.columns.is_empty() {
             self.add_column_by_schema(series, schema)?;
             Ok(self)
         }
@@ -1795,7 +1795,7 @@ impl DataFrame {
             });
         };
 
-        if self.height() == 0 {
+        if self.is_empty() {
             let mut out = self.clone();
             set_sorted(&mut out);
 

crates/polars-core/src/utils/flatten.rs

@@ -19,7 +19,7 @@ pub fn flatten_df_iter(df: &DataFrame) -> impl Iterator<Item = DataFrame> + '_ {
             })
             .collect();
         let df = unsafe { DataFrame::new_no_checks(columns) };
-        if df.height() == 0 {
+        if df.is_empty() {
             None
         } else {
             Some(df)

crates/polars-core/src/utils/mod.rs

@@ -205,7 +205,7 @@ pub fn split_df_as_ref(df: &DataFrame, target: usize, strict: bool) -> Vec<DataF
 /// Split a [`DataFrame`] into `n` parts. We take a `&mut` to be able to repartition/align chunks.
 /// `strict` in that it respects `n` even if the chunks are suboptimal.
 pub fn split_df(df: &mut DataFrame, target: usize) -> Vec<DataFrame> {
-    if target == 0 || df.height() == 0 {
+    if target == 0 || df.is_empty() {
         return vec![df.clone()];
     }
     // make sure that chunks are aligned.

crates/polars-expr/src/expressions/window.rs

@@ -399,7 +399,7 @@ impl PhysicalExpr for WindowExpr {
 
         // 4. select the final column and return
 
-        if df.height() == 0 {
+        if df.is_empty() {
             let field = self.phys_function.to_field(&df.schema())?;
             return Ok(Series::full_null(field.name(), 0, field.data_type()));
         }

crates/polars-io/src/csv/write/write_impl.rs

@@ -143,8 +143,7 @@ pub(crate) fn write<W: Write>(
             let cols = unsafe { std::mem::transmute::<&[Series], &[Series]>(cols) };
             let mut write_buffer = write_buffer_pool.get();
 
-            // don't use df.empty, won't work if there are columns.
-            if df.height() == 0 {
+            if df.is_empty() {
                 return Ok(write_buffer);
             }
 

crates/polars-io/src/parquet/read/read_impl.rs

@@ -727,7 +727,7 @@ impl BatchedParquetReader {
             skipped_all_rgs |= dfs.is_empty();
             for mut df in dfs {
                 // make sure that the chunks are not too large
-                let n = df.shape().0 / self.chunk_size;
+                let n = df.height() / self.chunk_size;
                 if n > 1 {
                     for df in split_df(&mut df, n) {
                         self.chunks_fifo.push_back(df)

crates/polars-io/src/predicates.rs

@@ -25,7 +25,7 @@ pub fn apply_predicate(
     predicate: Option<&dyn PhysicalIoExpr>,
     parallel: bool,
 ) -> PolarsResult<()> {
-    if let (Some(predicate), false) = (&predicate, df.is_empty()) {
+    if let (Some(predicate), false) = (&predicate, df.get_columns().is_empty()) {
         let s = predicate.evaluate_io(df)?;
         let mask = s.bool().expect("filter predicates was not of type boolean");
 

crates/polars-lazy/src/physical_plan/executors/projection.rs

@@ -39,11 +39,7 @@ impl ProjectionExec {
                     self.has_windows,
                     self.options.run_parallel,
                 )?;
-                check_expand_literals(
-                    selected_cols,
-                    df.height() == 0,
-                    self.options.duplicate_check,
-                )
+                check_expand_literals(selected_cols, df.is_empty(), self.options.duplicate_check)
             });
 
             let df = POOL.install(|| iter.collect::<PolarsResult<Vec<_>>>())?;
@@ -60,11 +56,7 @@ impl ProjectionExec {
                 self.has_windows,
                 self.options.run_parallel,
             )?;
-            check_expand_literals(
-                selected_cols,
-                df.height() == 0,
-                self.options.duplicate_check,
-            )?
+            check_expand_literals(selected_cols, df.is_empty(), self.options.duplicate_check)?
         };
 
         // this only runs during testing and check if the runtime type matches the predicted schema

crates/polars-lazy/src/physical_plan/executors/unique.rs

@@ -20,7 +20,7 @@ impl Executor for UniqueExec {
 
         state.record(
             || {
-                if df.height() == 0 {
+                if df.is_empty() {
                     return Ok(df);
                 }
 

crates/polars-pipe/src/operators/chunks.rs

@@ -23,7 +23,7 @@ impl DataChunk {
         Self::new(self.chunk_index, data)
     }
     pub(crate) fn is_empty(&self) -> bool {
-        self.data.height() == 0
+        self.data.is_empty()
     }
 }
 

crates/polars/tests/it/lazy/predicate_queries.rs

@@ -189,7 +189,7 @@ fn test_binaryexpr_pushdown_left_join_9506() -> PolarsResult<()> {
     }?;
     let df = df1.lazy().left_join(df2.lazy(), col("b"), col("b"));
     let out = df.filter(col("c").eq(lit("c2"))).collect()?;
-    assert!(out.height() == 0);
+    assert!(out.is_empty());
     Ok(())
 }
 

py-polars/polars/dataframe/frame.py

@@ -10379,7 +10379,7 @@ def interpolate(self) -> DataFrame:
 
     def is_empty(self) -> bool:
         """
-        Check if the dataframe is empty.
+        Returns `True` if the DataFrame contains no rows.
 
         Examples
         --------
@@ -10389,7 +10389,7 @@ def is_empty(self) -> bool:
         >>> df.filter(pl.col("foo") > 99).is_empty()
         True
         """
-        return self.height == 0
+        return self._df.is_empty()
 
     def to_struct(self, name: str = "") -> Series:
         """

py-polars/src/dataframe/general.rs

@@ -201,6 +201,10 @@ impl PyDataFrame {
         self.df.width()
     }
 
+    pub fn is_empty(&self) -> bool {
+        self.df.is_empty()
+    }
+
     pub fn hstack(&self, columns: Vec<PySeries>) -> PyResult<Self> {
         let columns = columns.to_series();
         let df = self.df.hstack(&columns).map_err(PyPolarsErr::from)?;

py-polars/src/interop/numpy/to_numpy_df.rs

@@ -44,9 +44,7 @@ fn df_to_numpy(
     writable: bool,
     allow_copy: bool,
 ) -> PyResult<PyObject> {
-    // TODO: Use `is_empty` when fixed:
-    // https://github.com/pola-rs/polars/pull/16351
-    if df.height() == 0 {
+    if df.is_empty() {
         // Take this path to ensure a writable array.
         // This does not actually copy data for an empty DataFrame.
         return df_to_numpy_with_copy(py, df, order, true);
@@ -76,10 +74,7 @@ fn df_to_numpy(
 }
 
 fn try_df_to_numpy_view(py: Python, df: &DataFrame) -> Option<PyObject> {
-    if df.is_empty() {
-        return None;
-    }
-    let first = df.get_columns().first().unwrap().dtype();
+    let first = df.get_columns().first()?.dtype();
     // TODO: Support Datetime/Duration/Array types
     if !first.is_numeric() {
         return None;