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# /// 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()
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