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Seaborn jointplot show annotation

0

I have plotted a jointplot of two variables. I have passed values to the annot_kws argument but nothing is showing in my plot.

import numpy as np
import seaborn as sns

d1 = np.random.normal(10,1,100)
d2 = np.random.gamma(1,2,100)
col1 = sns.color_palette()[0]
col2 = sns.color_palette()[1]
col3 = sns.color_palette()[2]

def hexbin_jointplot_sns(d1, d2, col1, col2, bins='log'):
 """ """
 jp = sns.jointplot(d1, d2, kind="hex", annot_kws=dict(stat="r"), joint_kws=dict(bins=bins))

 # plot the 1:1 line
 ax = jp.ax_joint
 ax.plot(ax.get_xlim(), ax.get_ylim(), ls="--", c=".3", label="1:1")

 # color the marginal distributions separately
 for patch in jp.ax_marg_x.patches:
 patch.set_facecolor(col1)

 for patch in jp.ax_marg_y.patches:
 patch.set_facecolor(col2)

 return jp

hexbin_jointplot_sns(d1, d2, col1, col2, bins='log')

How do I show the annotation in my plot?

python python-3.x matplotlib seaborn

share|improve this question

edited Mar 21 at 17:15

Tommy Lees

asked Mar 21 at 17:05

Tommy LeesTommy Lees

16811

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  It seems that annotation is deprecated as written here in the "API changes" section
  
  – Bazingaa
  Mar 21 at 17:13
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Ah okay so it has to be computed separately and put into a title or a text object! Thanks very much
  
  – Tommy Lees
  Mar 21 at 17:14
  

  
  
  
  


• 
  
  
  

  
  1
  

  
  
  
  
  
  

  
  
  Try putting this after jp = sns.jointplot: jp = jp.annotate(stats.pearsonr, fontsize=18, loc=(0.1, 0.8)). You will have to do from scipy import stats. I found the solution here
  
  – Bazingaa
  Mar 21 at 17:18
  
  

  
  
  
  

add a comment | 

0

I have plotted a jointplot of two variables. I have passed values to the annot_kws argument but nothing is showing in my plot.

import numpy as np
import seaborn as sns

d1 = np.random.normal(10,1,100)
d2 = np.random.gamma(1,2,100)
col1 = sns.color_palette()[0]
col2 = sns.color_palette()[1]
col3 = sns.color_palette()[2]

def hexbin_jointplot_sns(d1, d2, col1, col2, bins='log'):
 """ """
 jp = sns.jointplot(d1, d2, kind="hex", annot_kws=dict(stat="r"), joint_kws=dict(bins=bins))

 # plot the 1:1 line
 ax = jp.ax_joint
 ax.plot(ax.get_xlim(), ax.get_ylim(), ls="--", c=".3", label="1:1")

 # color the marginal distributions separately
 for patch in jp.ax_marg_x.patches:
 patch.set_facecolor(col1)

 for patch in jp.ax_marg_y.patches:
 patch.set_facecolor(col2)

 return jp

hexbin_jointplot_sns(d1, d2, col1, col2, bins='log')

How do I show the annotation in my plot?

python python-3.x matplotlib seaborn

share|improve this question

edited Mar 21 at 17:15

Tommy Lees

asked Mar 21 at 17:05

Tommy LeesTommy Lees

16811

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  It seems that annotation is deprecated as written here in the "API changes" section
  
  – Bazingaa
  Mar 21 at 17:13
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Ah okay so it has to be computed separately and put into a title or a text object! Thanks very much
  
  – Tommy Lees
  Mar 21 at 17:14
  

  
  
  
  


• 
  
  
  

  
  1
  

  
  
  
  
  
  

  
  
  Try putting this after jp = sns.jointplot: jp = jp.annotate(stats.pearsonr, fontsize=18, loc=(0.1, 0.8)). You will have to do from scipy import stats. I found the solution here
  
  – Bazingaa
  Mar 21 at 17:18
  
  

  
  
  
  

add a comment | 

I have plotted a jointplot of two variables. I have passed values to the annot_kws argument but nothing is showing in my plot.

import numpy as np
import seaborn as sns

d1 = np.random.normal(10,1,100)
d2 = np.random.gamma(1,2,100)
col1 = sns.color_palette()[0]
col2 = sns.color_palette()[1]
col3 = sns.color_palette()[2]

def hexbin_jointplot_sns(d1, d2, col1, col2, bins='log'):
 """ """
 jp = sns.jointplot(d1, d2, kind="hex", annot_kws=dict(stat="r"), joint_kws=dict(bins=bins))

 # plot the 1:1 line
 ax = jp.ax_joint
 ax.plot(ax.get_xlim(), ax.get_ylim(), ls="--", c=".3", label="1:1")

 # color the marginal distributions separately
 for patch in jp.ax_marg_x.patches:
 patch.set_facecolor(col1)

 for patch in jp.ax_marg_y.patches:
 patch.set_facecolor(col2)

 return jp

hexbin_jointplot_sns(d1, d2, col1, col2, bins='log')

How do I show the annotation in my plot?

python python-3.x matplotlib seaborn

share|improve this question

edited Mar 21 at 17:15

Tommy Lees

asked Mar 21 at 17:05

Tommy LeesTommy Lees

16811

import numpy as np
import seaborn as sns

d1 = np.random.normal(10,1,100)
d2 = np.random.gamma(1,2,100)
col1 = sns.color_palette()[0]
col2 = sns.color_palette()[1]
col3 = sns.color_palette()[2]

def hexbin_jointplot_sns(d1, d2, col1, col2, bins='log'):
 """ """
 jp = sns.jointplot(d1, d2, kind="hex", annot_kws=dict(stat="r"), joint_kws=dict(bins=bins))

 # plot the 1:1 line
 ax = jp.ax_joint
 ax.plot(ax.get_xlim(), ax.get_ylim(), ls="--", c=".3", label="1:1")

 # color the marginal distributions separately
 for patch in jp.ax_marg_x.patches:
 patch.set_facecolor(col1)

 for patch in jp.ax_marg_y.patches:
 patch.set_facecolor(col2)

 return jp

hexbin_jointplot_sns(d1, d2, col1, col2, bins='log')

share|improve this question

edited Mar 21 at 17:15

Tommy Lees

asked Mar 21 at 17:05

Tommy LeesTommy Lees

16811

share|improve this question

edited Mar 21 at 17:15

Tommy Lees

asked Mar 21 at 17:05

Tommy LeesTommy Lees

16811

asked Mar 21 at 17:05

Tommy LeesTommy Lees

16811

asked Mar 21 at 17:05

Tommy LeesTommy Lees

16811