remove other polars work

polars/basic_polars_joins.py

@@ -1,99 +0,0 @@
-# /// script
-# dependencies = [
-#     "marimo",
-#     "polars==1.28.1",
-# ]
-# [tool.marimo.runtime]
-# auto_instantiate = false
-# ///
-
-import marimo
-
-__generated_with = "0.13.2"
-app = marimo.App(width="medium")
-
-
-@app.cell
-def _():
-    import marimo as mo
-    import polars as pl
-    return mo, pl
-
-
-@app.cell
-def _(pl):
-    base = pl.DataFrame(
-        {"id": [1, 2, 3, 4], "name": ["Alice", "Bob", "Charlie", "Diana"]}
-    )
-
-    other = pl.DataFrame({"id": [3, 4, 5, 6], "age": [25, 32, 40, 28]})
-    return base, other
-
-
-@app.cell
-def _(base, mo, other):
-    mo.vstack(
-        [
-            mo.hstack([mo.ui.table(base, show_download=False , label='base'), mo.ui.table(other, show_download=False, label='other')], justify="center"),
-        ]
-    )
-    return
-
-
-@app.cell
-def _(mo):
-    join_options: dict = {
-        "inner (default)": "inner",
-        "left": "left",
-        "right": "right",
-        "full": "full",
-        "semi": "semi",
-        "anti": "anti",
-    }
-
-    # These are from https://docs.pola.rs/user-guide/transformations/joins/#quick-reference-table
-    descriptions: dict = {
-        "inner": "Keeps rows that matched both on the left and right.",
-        "left": "Keeps all rows from the left plus matching rows from the right. Non-matching rows from the left have their right columns filled with null.",
-        "right": "Keeps all rows from the right plus matching rows from the left. Non-matching rows from the right have their left columns filled with null.",
-        "full": "Keeps all rows from either dataframe, regardless of whether they match or not. Non-matching rows from one side have the columns from the other side filled with null.",
-        "semi": "Keeps rows from the left that have a match on the right.",
-        "anti": "Keeps rows from the left that do not have a match on the right.",
-        "join_where": "Finds all possible pairings of rows from the left and right that satisfy the given predicate(s).",
-        "join_asof": "Like a left outer join, but matches on the nearest key instead of on exact key matches.",
-        "cross": "Computes the Cartesian product of the two dataframes.",
-    }
-    dropdown = mo.ui.dropdown(
-        value="inner (default)",
-        options=join_options,
-    )
-    return descriptions, dropdown
-
-
-@app.cell
-def _(base, descriptions, dropdown, mo, other, pl):
-    result: pl.DataFrame = base.join(other, on="id", how=dropdown.value)
-    n_rows, n_columns = result.shape
-    mo.vstack(
-        [
-            dropdown,
-            mo.md(descriptions[dropdown.value]),
-            mo.md(f"rows: {n_rows} columns: {n_columns}"),
-        ]
-    )
-    return (result,)
-
-
-@app.cell
-def _(mo, result):
-    mo.vstack([result])
-    return
-
-
-@app.cell
-def _():
-    return
-
-
-if __name__ == "__main__":
-    app.run()