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I'm trying to do some PairPlots using seaborn, so I can compare a bunch of features against the label I'm trying to model. There are a bunch of features though (~50). So I'm basically doing:

g = sns.pairplot(train_df,x_vars=["MoSold","GarageArea","ScreenPorch","OverallQual"],y_vars="SalePrice",size=4)

Where "SalePrice" is the label that I want to compare the others against. For now I don't care about comparing the features to each other.

The problem I'm having, though, is that when I plot this in my Jupyter notebook, it formats it as one long row.

enter image description here

I'm only doing it with 4 features here, but when I add as many as I want to, it basically makes the row thinner and longer, and impossible to read (because it's trying to make them all share the same y axis).

What I'd like is for it to automatically wrap like panda's hist does:

enter image description here

I can think of a few little hacks. I could do several individual PairPlot commands to manually do it, using a for loop or something, but that would be kind of a pain. Is there some more elegant way to do this? Something where I'd specify the number of columns it'll display with, and then it'll make a grid, where the y axis is always SalePrice?

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You should not use sns.pairplot which is for plotting all-by-all comparisons.

You should use sns.regplot which can specify particular comparisons to make. Then use subplots can control the tiling.

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  • $\begingroup$ Nowadays lmplot is the figure-level equivalent of regplot and it should be used instead - it has arguments col= and col_wrap= which should help do this relatively smoothly. $\endgroup$
    – creanion
    Oct 2, 2021 at 21:03

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