[Python] Simplest way to convert aggregated data to visualize in polars

Suppose I have aggregated the mean and the median of some value over 3 months, like:

df = (data.group_by('month_code').agg(pl.col('value').mean().alias('avg'),
pd.col('value').median().alias('med')
)
.sort('month_code')
.collect()
)


Resulting in something like:

df = pd.DataFrame({'month': ['M202412','M202501','M202502'],
'avg': [0.037824, 0.03616, 0.038919],
'med': [0.01381, 0.013028, 0.014843]
})


And I'd like to visualize it, so should convert to the format:

df_ = pd.DataFrame({'month': ['M202412','M202501','M202502']*2,
'type': ['avg','avg','avg','med','med','med'],
'value': [0.037824, 0.03616, 0.038919, 0.01381, 0.013028, 0.014843],
})


Which is then easy to visualize:

df_.plot.line(x='month',y='value',color='type').properties(width=400, height=350, title='avg and med')


What is the simplest way to convert df to df_ above?

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