add code for analysis of data

1 files changed, 227 insertions, 0 deletions

diff --git a/venv/lib/python3.8/site-packages/narwhals/_ibis/namespace.py b/venv/lib/python3.8/site-packages/narwhals/_ibis/namespace.py
new file mode 100644
index 0000000..25393cf
--- /dev/null
+++ b/venv/lib/python3.8/site-packages/narwhals/_ibis/namespace.py
@@ -0,0 +1,227 @@
+from __future__ import annotations
+
+import operator
+from functools import reduce
+from itertools import chain
+from typing import TYPE_CHECKING, Any, Iterable, Sequence, cast
+
+import ibis
+import ibis.expr.types as ir
+
+from narwhals._compliant import LazyNamespace, LazyThen, LazyWhen
+from narwhals._expression_parsing import (
+    combine_alias_output_names,
+    combine_evaluate_output_names,
+)
+from narwhals._ibis.dataframe import IbisLazyFrame
+from narwhals._ibis.expr import IbisExpr
+from narwhals._ibis.selectors import IbisSelectorNamespace
+from narwhals._ibis.utils import lit, narwhals_to_native_dtype
+from narwhals._utils import Implementation, requires
+
+if TYPE_CHECKING:
+    from narwhals._utils import Version
+    from narwhals.typing import ConcatMethod, IntoDType
+
+
+class IbisNamespace(LazyNamespace[IbisLazyFrame, IbisExpr, "ir.Table"]):
+    _implementation: Implementation = Implementation.IBIS
+
+    def __init__(self, *, backend_version: tuple[int, ...], version: Version) -> None:
+        self._backend_version = backend_version
+        self._version = version
+
+    @property
+    def selectors(self) -> IbisSelectorNamespace:
+        return IbisSelectorNamespace.from_namespace(self)
+
+    @property
+    def _expr(self) -> type[IbisExpr]:
+        return IbisExpr
+
+    @property
+    def _lazyframe(self) -> type[IbisLazyFrame]:
+        return IbisLazyFrame
+
+    def concat(
+        self, items: Iterable[IbisLazyFrame], *, how: ConcatMethod
+    ) -> IbisLazyFrame:
+        if how == "diagonal":
+            msg = "diagonal concat not supported for Ibis. Please join instead."
+            raise NotImplementedError(msg)
+
+        items = list(items)
+        native_items = [item.native for item in items]
+        schema = items[0].schema
+        if not all(x.schema == schema for x in items[1:]):
+            msg = "inputs should all have the same schema"
+            raise TypeError(msg)
+        return self._lazyframe.from_native(ibis.union(*native_items), context=self)
+
+    def concat_str(
+        self, *exprs: IbisExpr, separator: str, ignore_nulls: bool
+    ) -> IbisExpr:
+        def func(df: IbisLazyFrame) -> list[ir.Value]:
+            cols = list(chain.from_iterable(expr(df) for expr in exprs))
+            cols_casted = [s.cast("string") for s in cols]
+
+            if not ignore_nulls:
+                result = cols_casted[0]
+                for col in cols_casted[1:]:
+                    result = result + separator + col
+            else:
+                sep = cast("ir.StringValue", lit(separator))
+                result = sep.join(cols_casted)
+
+            return [result]
+
+        return self._expr(
+            call=func,
+            evaluate_output_names=combine_evaluate_output_names(*exprs),
+            alias_output_names=combine_alias_output_names(*exprs),
+            backend_version=self._backend_version,
+            version=self._version,
+        )
+
+    def all_horizontal(self, *exprs: IbisExpr) -> IbisExpr:
+        def func(df: IbisLazyFrame) -> list[ir.Value]:
+            cols = chain.from_iterable(expr(df) for expr in exprs)
+            return [reduce(operator.and_, cols)]
+
+        return self._expr(
+            call=func,
+            evaluate_output_names=combine_evaluate_output_names(*exprs),
+            alias_output_names=combine_alias_output_names(*exprs),
+            backend_version=self._backend_version,
+            version=self._version,
+        )
+
+    def any_horizontal(self, *exprs: IbisExpr) -> IbisExpr:
+        def func(df: IbisLazyFrame) -> list[ir.Value]:
+            cols = chain.from_iterable(expr(df) for expr in exprs)
+            return [reduce(operator.or_, cols)]
+
+        return self._expr(
+            call=func,
+            evaluate_output_names=combine_evaluate_output_names(*exprs),
+            alias_output_names=combine_alias_output_names(*exprs),
+            backend_version=self._backend_version,
+            version=self._version,
+        )
+
+    def max_horizontal(self, *exprs: IbisExpr) -> IbisExpr:
+        def func(df: IbisLazyFrame) -> list[ir.Value]:
+            cols = chain.from_iterable(expr(df) for expr in exprs)
+            return [ibis.greatest(*cols)]
+
+        return self._expr(
+            call=func,
+            evaluate_output_names=combine_evaluate_output_names(*exprs),
+            alias_output_names=combine_alias_output_names(*exprs),
+            backend_version=self._backend_version,
+            version=self._version,
+        )
+
+    def min_horizontal(self, *exprs: IbisExpr) -> IbisExpr:
+        def func(df: IbisLazyFrame) -> list[ir.Value]:
+            cols = chain.from_iterable(expr(df) for expr in exprs)
+            return [ibis.least(*cols)]
+
+        return self._expr(
+            call=func,
+            evaluate_output_names=combine_evaluate_output_names(*exprs),
+            alias_output_names=combine_alias_output_names(*exprs),
+            backend_version=self._backend_version,
+            version=self._version,
+        )
+
+    def sum_horizontal(self, *exprs: IbisExpr) -> IbisExpr:
+        def func(df: IbisLazyFrame) -> list[ir.Value]:
+            cols = [e.fill_null(lit(0)) for _expr in exprs for e in _expr(df)]
+            return [reduce(operator.add, cols)]
+
+        return self._expr(
+            call=func,
+            evaluate_output_names=combine_evaluate_output_names(*exprs),
+            alias_output_names=combine_alias_output_names(*exprs),
+            backend_version=self._backend_version,
+            version=self._version,
+        )
+
+    def mean_horizontal(self, *exprs: IbisExpr) -> IbisExpr:
+        def func(df: IbisLazyFrame) -> list[ir.Value]:
+            expr = (
+                cast("ir.NumericColumn", e.fill_null(lit(0)))
+                for _expr in exprs
+                for e in _expr(df)
+            )
+            non_null = (
+                cast("ir.NumericColumn", e.isnull().ifelse(lit(0), lit(1)))
+                for _expr in exprs
+                for e in _expr(df)
+            )
+
+            return [
+                (reduce(lambda x, y: x + y, expr) / reduce(lambda x, y: x + y, non_null))
+            ]
+
+        return self._expr(
+            call=func,
+            evaluate_output_names=combine_evaluate_output_names(*exprs),
+            alias_output_names=combine_alias_output_names(*exprs),
+            backend_version=self._backend_version,
+            version=self._version,
+        )
+
+    @requires.backend_version((10, 0))
+    def when(self, predicate: IbisExpr) -> IbisWhen:
+        return IbisWhen.from_expr(predicate, context=self)
+
+    def lit(self, value: Any, dtype: IntoDType | None) -> IbisExpr:
+        def func(_df: IbisLazyFrame) -> list[ir.Value]:
+            ibis_dtype = narwhals_to_native_dtype(dtype, self._version) if dtype else None
+            return [lit(value, ibis_dtype)]
+
+        return self._expr(
+            func,
+            evaluate_output_names=lambda _df: ["literal"],
+            alias_output_names=None,
+            backend_version=self._backend_version,
+            version=self._version,
+        )
+
+    def len(self) -> IbisExpr:
+        def func(_df: IbisLazyFrame) -> list[ir.Value]:
+            return [_df.native.count()]
+
+        return self._expr(
+            call=func,
+            evaluate_output_names=lambda _df: ["len"],
+            alias_output_names=None,
+            backend_version=self._backend_version,
+            version=self._version,
+        )
+
+
+class IbisWhen(LazyWhen["IbisLazyFrame", "ir.Value", IbisExpr]):
+    lit = lit
+
+    @property
+    def _then(self) -> type[IbisThen]:
+        return IbisThen
+
+    def __call__(self, df: IbisLazyFrame) -> Sequence[ir.Value]:
+        is_expr = self._condition._is_expr
+        condition = df._evaluate_expr(self._condition)
+        then_ = self._then_value
+        then = df._evaluate_expr(then_) if is_expr(then_) else lit(then_)
+        other_ = self._otherwise_value
+        if other_ is None:
+            result = ibis.cases((condition, then))
+        else:
+            otherwise = df._evaluate_expr(other_) if is_expr(other_) else lit(other_)
+            result = ibis.cases((condition, then), else_=otherwise)
+        return [result]
+
+
+class IbisThen(LazyThen["IbisLazyFrame", "ir.Value", IbisExpr], IbisExpr): ...