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DataFramePlotzDataFrame.plot namespace.c 8 t j | | _ y )N)altChart_chart)selfdfs u/var/www/html/wine-match-dev/backend/winematch-backend/venv/lib/python3.12/site-packages/polars/dataframe/plotting.py__init__zDataFramePlot.__init__% s iim Nc i }|||d< |||d< |||d< | j j d j di ||j S )a
Draw bar plot.
Polars does not implement plotting logic itself but instead defers to
`Altair `_.
`df.plot.bar(**kwargs)` is shorthand for
`alt.Chart(df).mark_bar().encode(**kwargs).interactive()`,
and is provided for convenience - for full customisability, use a plotting
library directly.
.. versionchanged:: 1.6.0
In prior versions of Polars, HvPlot was the plotting backend. If you would
like to restore the previous plotting functionality, all you need to do
is add `import hvplot.polars` at the top of your script and replace
`df.plot` with `df.hvplot`.
Parameters
----------
x
Column with x-coordinates of bars.
y
Column with y-coordinates of bars.
color
Column to color bars by.
**kwargs
Additional keyword arguments passed to Altair.
Examples
--------
>>> df = pl.DataFrame(
... {
... "day": ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"] * 2,
... "group": ["a"] * 7 + ["b"] * 7,
... "value": [1, 3, 2, 4, 5, 6, 1, 1, 3, 2, 4, 5, 1, 2],
... }
... )
>>> df.plot.bar(
... x="day", y="value", color="day", column="group"
... ) # doctest: +SKIP
xycolorTtooltip )r mark_barencode interactive)r r# r$ r% kwargs encodingss r barzDataFramePlot.bar( su b " = IcN = IcN !&Ig
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+
[]
r! c i }|||d< |||d< |||d< |||d< | j j d j di ||j S )a
Draw line plot.
Polars does not implement plotting logic itself but instead defers to
`Altair `_.
`df.plot.line(**kwargs)` is shorthand for
`alt.Chart(df).mark_line().encode(**kwargs).interactive()`,
and is provided for convenience - for full customisatibility, use a plotting
library directly.
.. versionchanged:: 1.6.0
In prior versions of Polars, HvPlot was the plotting backend. If you would
like to restore the previous plotting functionality, all you need to do
is add `import hvplot.polars` at the top of your script and replace
`df.plot` with `df.hvplot`.
Parameters
----------
x
Column with x-coordinates of lines.
y
Column with y-coordinates of lines.
color
Column to color lines by.
order
Column to use for order of data points in lines.
**kwargs
Additional keyword arguments passed to Altair.
Examples
--------
>>> from datetime import date
>>> df = pl.DataFrame(
... {
... "date": [date(2020, 1, 2), date(2020, 1, 3), date(2020, 1, 4)] * 2,
... "price": [1, 4, 6, 1, 5, 2],
... "stock": ["a", "a", "a", "b", "b", "b"],
... }
... )
>>> df.plot.line(x="date", y="price", color="stock") # doctest: +SKIP
r# r$ r% orderTr& r( )r mark_liner* r+ )r r# r$ r% r0 r, r- s r linezDataFramePlot.linef s f " = IcN = IcN !&Ig !&Ig
DKK ! !$ ! /
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[]
r! c i }|||d< |||d< |||d< |||d< | j j d j di ||j S )a
Draw scatter plot.
Polars does not implement plotting logic itself but instead defers to
`Altair `_.
`df.plot.point(**kwargs)` is shorthand for
`alt.Chart(df).mark_point().encode(**kwargs).interactive()`,
and is provided for convenience - for full customisatibility, use a plotting
library directly.
.. versionchanged:: 1.6.0
In prior versions of Polars, HvPlot was the plotting backend. If you would
like to restore the previous plotting functionality, all you need to do
is add `import hvplot.polars` at the top of your script and replace
`df.plot` with `df.hvplot`.
Parameters
----------
x
Column with x-coordinates of points.
y
Column with y-coordinates of points.
color
Column to color points by.
size
Column which determines points' sizes.
**kwargs
Additional keyword arguments passed to Altair.
Examples
--------
>>> df = pl.DataFrame(
... {
... "length": [1, 4, 6],
... "width": [4, 5, 6],
... "species": ["setosa", "setosa", "versicolor"],
... }
... )
>>> df.plot.point(x="length", y="width", color="species") # doctest: +SKIP
r# r$ r% sizeTr& r( )r
mark_pointr* r+ )r r# r$ r% r4 r, r- s r pointzDataFramePlot.point s d " = IcN = IcN !&Ig $If
DKK " "4 " 0
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[]
r! c t | j d| d d| d}t | dt j j
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