How to not share axes in FacetGrid





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I'm attempting to plot the KDE each column in a dataframe df, with the last column being a boolean with which I plot two hues on each graph, through the use of



sns.pairplot(df, hue='last', palette={True: "#FF0000", False: "#0000FF"}, diag_kind='kde')


This gives me nice KDEs for all of the columns. However, I don't really care for comparing each column pairwise; I only really want to see how the KDEs differ based on the value of last. However, no other method is that elegant. The only other option I've seen is using a FacetGrid, but that has the flaw that the axes limits are all the same. I just can't find a nice way to visualize each column and its relation to the last boolean column.










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  • 1





    Since it totally makes sense to have equal axis limits for comparisson, I don't quite understand the problem. Maybe you want to share the code you used to create the FacetGrid and state what you don't like about the result.

    – ImportanceOfBeingErnest
    Nov 27 '18 at 0:33











  • The reason why I don't want nor need equal axes is because I'm looking at each column individually compared. See my answer.

    – Sebastian
    Nov 27 '18 at 1:00


















0















I'm attempting to plot the KDE each column in a dataframe df, with the last column being a boolean with which I plot two hues on each graph, through the use of



sns.pairplot(df, hue='last', palette={True: "#FF0000", False: "#0000FF"}, diag_kind='kde')


This gives me nice KDEs for all of the columns. However, I don't really care for comparing each column pairwise; I only really want to see how the KDEs differ based on the value of last. However, no other method is that elegant. The only other option I've seen is using a FacetGrid, but that has the flaw that the axes limits are all the same. I just can't find a nice way to visualize each column and its relation to the last boolean column.










share|improve this question




















  • 1





    Since it totally makes sense to have equal axis limits for comparisson, I don't quite understand the problem. Maybe you want to share the code you used to create the FacetGrid and state what you don't like about the result.

    – ImportanceOfBeingErnest
    Nov 27 '18 at 0:33











  • The reason why I don't want nor need equal axes is because I'm looking at each column individually compared. See my answer.

    – Sebastian
    Nov 27 '18 at 1:00














0












0








0








I'm attempting to plot the KDE each column in a dataframe df, with the last column being a boolean with which I plot two hues on each graph, through the use of



sns.pairplot(df, hue='last', palette={True: "#FF0000", False: "#0000FF"}, diag_kind='kde')


This gives me nice KDEs for all of the columns. However, I don't really care for comparing each column pairwise; I only really want to see how the KDEs differ based on the value of last. However, no other method is that elegant. The only other option I've seen is using a FacetGrid, but that has the flaw that the axes limits are all the same. I just can't find a nice way to visualize each column and its relation to the last boolean column.










share|improve this question
















I'm attempting to plot the KDE each column in a dataframe df, with the last column being a boolean with which I plot two hues on each graph, through the use of



sns.pairplot(df, hue='last', palette={True: "#FF0000", False: "#0000FF"}, diag_kind='kde')


This gives me nice KDEs for all of the columns. However, I don't really care for comparing each column pairwise; I only really want to see how the KDEs differ based on the value of last. However, no other method is that elegant. The only other option I've seen is using a FacetGrid, but that has the flaw that the axes limits are all the same. I just can't find a nice way to visualize each column and its relation to the last boolean column.







python pandas numpy matplotlib seaborn






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edited Nov 27 '18 at 3:34









ImportanceOfBeingErnest

142k13170248




142k13170248










asked Nov 27 '18 at 0:00









SebastianSebastian

1,641717




1,641717








  • 1





    Since it totally makes sense to have equal axis limits for comparisson, I don't quite understand the problem. Maybe you want to share the code you used to create the FacetGrid and state what you don't like about the result.

    – ImportanceOfBeingErnest
    Nov 27 '18 at 0:33











  • The reason why I don't want nor need equal axes is because I'm looking at each column individually compared. See my answer.

    – Sebastian
    Nov 27 '18 at 1:00














  • 1





    Since it totally makes sense to have equal axis limits for comparisson, I don't quite understand the problem. Maybe you want to share the code you used to create the FacetGrid and state what you don't like about the result.

    – ImportanceOfBeingErnest
    Nov 27 '18 at 0:33











  • The reason why I don't want nor need equal axes is because I'm looking at each column individually compared. See my answer.

    – Sebastian
    Nov 27 '18 at 1:00








1




1





Since it totally makes sense to have equal axis limits for comparisson, I don't quite understand the problem. Maybe you want to share the code you used to create the FacetGrid and state what you don't like about the result.

– ImportanceOfBeingErnest
Nov 27 '18 at 0:33





Since it totally makes sense to have equal axis limits for comparisson, I don't quite understand the problem. Maybe you want to share the code you used to create the FacetGrid and state what you don't like about the result.

– ImportanceOfBeingErnest
Nov 27 '18 at 0:33













The reason why I don't want nor need equal axes is because I'm looking at each column individually compared. See my answer.

– Sebastian
Nov 27 '18 at 1:00





The reason why I don't want nor need equal axes is because I'm looking at each column individually compared. See my answer.

– Sebastian
Nov 27 '18 at 1:00












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I just needed to set sharex and sharey in the FacetGrid.__init__ to False:



sns.FacetGrid(data=df.melt(id_vars=['last']), col="variable", hue="last", 
palette={True: "#FF0000", False: "#0000FF"}, sharex=False,
sharey=False, col_wrap=4).map(sns.kdeplot, 'value', shade=True)





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    I just needed to set sharex and sharey in the FacetGrid.__init__ to False:



    sns.FacetGrid(data=df.melt(id_vars=['last']), col="variable", hue="last", 
    palette={True: "#FF0000", False: "#0000FF"}, sharex=False,
    sharey=False, col_wrap=4).map(sns.kdeplot, 'value', shade=True)





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      0














      I just needed to set sharex and sharey in the FacetGrid.__init__ to False:



      sns.FacetGrid(data=df.melt(id_vars=['last']), col="variable", hue="last", 
      palette={True: "#FF0000", False: "#0000FF"}, sharex=False,
      sharey=False, col_wrap=4).map(sns.kdeplot, 'value', shade=True)





      share|improve this answer


























        0












        0








        0







        I just needed to set sharex and sharey in the FacetGrid.__init__ to False:



        sns.FacetGrid(data=df.melt(id_vars=['last']), col="variable", hue="last", 
        palette={True: "#FF0000", False: "#0000FF"}, sharex=False,
        sharey=False, col_wrap=4).map(sns.kdeplot, 'value', shade=True)





        share|improve this answer













        I just needed to set sharex and sharey in the FacetGrid.__init__ to False:



        sns.FacetGrid(data=df.melt(id_vars=['last']), col="variable", hue="last", 
        palette={True: "#FF0000", False: "#0000FF"}, sharex=False,
        sharey=False, col_wrap=4).map(sns.kdeplot, 'value', shade=True)






        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 27 '18 at 1:00









        SebastianSebastian

        1,641717




        1,641717
































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