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| 1 | +# /// script |
| 2 | +# requires-python = ">=3.11" |
| 3 | +# dependencies = [ |
| 4 | +# "duckdb==1.3.0", |
| 5 | +# "marimo", |
| 6 | +# "narwhals==1.40.0", |
| 7 | +# "pandas==2.2.3", |
| 8 | +# "polars==1.30.0", |
| 9 | +# "pyarrow==20.0.0", |
| 10 | +# ] |
| 11 | +# /// |
| 12 | + |
| 13 | +import marimo |
| 14 | + |
| 15 | +__generated_with = "0.13.7" |
| 16 | +app = marimo.App(width="medium") |
| 17 | + |
| 18 | + |
| 19 | +@app.cell |
| 20 | +def _(): |
| 21 | + import marimo as mo |
| 22 | + return (mo,) |
| 23 | + |
| 24 | + |
| 25 | +@app.cell(hide_code=True) |
| 26 | +def _(mo): |
| 27 | + mo.md(r"""# Eager vs Lazy DataFrames: One Fix to Make Your Code Work Anywhere""") |
| 28 | + return |
| 29 | + |
| 30 | + |
| 31 | +@app.cell |
| 32 | +def _(): |
| 33 | + from datetime import datetime |
| 34 | + |
| 35 | + data = { |
| 36 | + "sale_date": [ |
| 37 | + datetime(2025, 5, 22), |
| 38 | + datetime(2025, 5, 23), |
| 39 | + datetime(2025, 5, 24), |
| 40 | + datetime(2025, 5, 22), |
| 41 | + datetime(2025, 5, 23), |
| 42 | + datetime(2025, 5, 24), |
| 43 | + ], |
| 44 | + "store": [ |
| 45 | + "Thimphu", |
| 46 | + "Thimphu", |
| 47 | + "Thimphu", |
| 48 | + "Paro", |
| 49 | + "Paro", |
| 50 | + "Paro", |
| 51 | + ], |
| 52 | + "sales": [1100, None, 1450, 501, 500, None], |
| 53 | + } |
| 54 | + return (data,) |
| 55 | + |
| 56 | + |
| 57 | +@app.cell(hide_code=True) |
| 58 | +def _(mo): |
| 59 | + mo.md(r"""## Eager-only solution""") |
| 60 | + return |
| 61 | + |
| 62 | + |
| 63 | +@app.cell |
| 64 | +def _(): |
| 65 | + import narwhals as nw |
| 66 | + from narwhals.typing import IntoFrameT |
| 67 | + |
| 68 | + |
| 69 | + def agnostic_ffill_by_store(df_native: IntoFrameT) -> IntoFrameT: |
| 70 | + # Supports pandas and Polars.DataFrame, but not lazy ones. |
| 71 | + return ( |
| 72 | + nw.from_native(df_native) |
| 73 | + .with_columns( |
| 74 | + nw.col("sales").fill_null(strategy="forward").over("store") |
| 75 | + ) |
| 76 | + .to_native() |
| 77 | + ) |
| 78 | + return IntoFrameT, agnostic_ffill_by_store, nw |
| 79 | + |
| 80 | + |
| 81 | +@app.cell |
| 82 | +def _(agnostic_ffill_by_store, data): |
| 83 | + import pandas as pd |
| 84 | + import polars as pl |
| 85 | + |
| 86 | + # pandas.DataFrame |
| 87 | + df_pandas = pd.DataFrame(data) |
| 88 | + agnostic_ffill_by_store(df_pandas) |
| 89 | + |
| 90 | + # polars.DataFrame |
| 91 | + df_polars = pl.DataFrame(data) |
| 92 | + agnostic_ffill_by_store(df_polars) |
| 93 | + return (df_pandas,) |
| 94 | + |
| 95 | + |
| 96 | +@app.cell |
| 97 | +def _(): |
| 98 | + import duckdb |
| 99 | + |
| 100 | + duckdb_rel = duckdb.table("df_polars") |
| 101 | + duckdb_rel |
| 102 | + return (duckdb_rel,) |
| 103 | + |
| 104 | + |
| 105 | +@app.cell(hide_code=True) |
| 106 | +def _(mo): |
| 107 | + mo.md(r"""## Eager and lazy solution""") |
| 108 | + return |
| 109 | + |
| 110 | + |
| 111 | +@app.cell |
| 112 | +def _(IntoFrameT, nw): |
| 113 | + def agnostic_ffill_by_store_improved(df_native: IntoFrameT) -> IntoFrameT: |
| 114 | + return ( |
| 115 | + nw.from_native(df_native) |
| 116 | + .with_columns( |
| 117 | + nw.col("sales") |
| 118 | + .fill_null(strategy="forward") |
| 119 | + # Note the `order_by` statement |
| 120 | + .over("store", order_by="sale_date") |
| 121 | + ) |
| 122 | + .to_native() |
| 123 | + ) |
| 124 | + return (agnostic_ffill_by_store_improved,) |
| 125 | + |
| 126 | + |
| 127 | +@app.cell |
| 128 | +def _(agnostic_ffill_by_store_improved, duckdb_rel): |
| 129 | + agnostic_ffill_by_store_improved(duckdb_rel) |
| 130 | + return |
| 131 | + |
| 132 | + |
| 133 | +@app.cell |
| 134 | +def _(agnostic_ffill_by_store_improved, df_pandas): |
| 135 | + # Note that it still supports pandas |
| 136 | + agnostic_ffill_by_store_improved(df_pandas) |
| 137 | + return |
| 138 | + |
| 139 | + |
| 140 | +if __name__ == "__main__": |
| 141 | + app.run() |
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