#๐ Colormap of date in sns.pairplots
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@sinful matrix
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anyone ?
Can you rephrase? It's hard to understand what you're trying to do
Yeah sure ! sorry if it wasnt clear
i only manage
either
this
or this
i want the second one where each point is associated with a date but i want to keep the distrubutions in the diagonal
Ok, and how do you produce each of the plots currently?
the first one is :
sns.pairplot(filtered_data[analysis_columns + ['Julian Date']], diag_kind='kde', corner=True)
the second one is "
sns.pairplot(filtered_data[analysis_columns + ['Julian Date']], diag_kind='kde', corner=True, hue='Julian Date')
which hue adds a colormap but for some reason it removes the diagonal distribution
how would you assign the hue to the distribution?
basically i have a csv file that looks like this :
so each point is associate with a date
I understand how you assign the hue to the points, I'm asking about the missing diagonal distributions which don't look like points
sry not sure i understand your question. I dont want the hue in the diagonal, simply the distribution and the hue everywhere else
yeah I'm just not sure that's how the function works
I'm looking at https://seaborn.pydata.org/generated/seaborn.pairplot.html and it looks as if the diagonal distributions are split according to the hue argument, which in your case would be a different date per point
hmm
i see what you mean yeah
weird that i cant bypass it to not pass the hue but i guess its how the function is made
I'm no seaborn expert so take it with a grain of salt, but that's what I see from their documentation
yeah thats my conclusion too
Maybe it's possible to to do all the off-diagonals separately and then join them to the diagonal plots
Look at the example usage here: https://seaborn.pydata.org/generated/seaborn.PairGrid.html#seaborn.PairGrid
It allows you to assign different hues, might be what you're looking for
So in this case you would assign a hue only to the off-diagonal plots
with which arguments ?
Scroll through the example usage, they show this case
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