Add weekday barplot
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1 changed files with 51 additions and 14 deletions
65
popcorn.py
65
popcorn.py
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@ -129,20 +129,58 @@ def _():
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@app.cell
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def _(df: pl.DataFrame):
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weekly_downloads = (
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df.sort("date")
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.group_by_dynamic("date", every="1w")
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.agg(pl.col("downloads").sum())
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.sort("date")
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)
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(
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lp.ggplot(weekly_downloads, lp.aes("date", "downloads"))
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+ lp.geom_line()
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+ lp.geom_smooth(method="loess")
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+ lp.labs(
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title="Weekly downloads",
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def _():
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weekly_downloads = (
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df.sort("date")
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.group_by_dynamic("date", every="1w")
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.agg(pl.col("downloads").sum())
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.sort("date")
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)
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)
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return (
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lp.ggplot(weekly_downloads, lp.aes("date", "downloads"))
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+ lp.geom_line()
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+ lp.geom_smooth(method="loess")
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+ lp.labs(
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title="Weekly downloads",
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)
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)
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_()
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return
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@app.cell
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def _(df: pl.DataFrame):
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def _():
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weekday_downloads = df.sort("date").with_columns(
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pl.col("date")
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.dt.weekday()
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.sort()
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.replace_strict(
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{
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1: "Mon",
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2: "Tue",
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3: "Wed",
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4: "Thu",
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5: "Fri",
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6: "Sat",
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7: "Sun",
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}
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)
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.alias("weekday")
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)
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return (
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lp.ggplot(weekday_downloads, lp.aes("weekday", "downloads"))
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+ lp.geom_bar()
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+ lp.labs(
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title="Weekday downloads",
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caption="Downloads aggregated per day of the week they took place.",
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)
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)
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_()
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return
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@ -193,7 +231,6 @@ def _(sizes_df):
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# further ideas:
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#
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# - daily download habits:
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# - which weekday has most downloads?
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# - are we downloading further spread of versions on specific days
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# - are there 'update' days, where things converge? specific weekday/on holidays/etc?
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#
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