CODEWITHSUNDEEP
pythonseaborn
Shuvayan Das
Shuvayan Das

Reputation: 1048

show metrics like kurtosis, skewness on distribution plot using seaborn in python

I have the below data:

coll_prop_tenure    coll_prop_12m   coll_prop_6m    coll_prop_3m
0.04                0.04            0.06            0.08
0                   0               0               0
0                   0               0               0
0.06                0.06            0.1             0
0.38                0.38            0.25            0
0.61                0.61            0.66            0.61
0.01                0.01            0.02            0.02
0.1                 0.1             0.12            0.16
0.04                0.04            0.04            0.09
0.22                0.22            0.22            0.22
0.72                0.72            0.73            0.72
0.39                0.39            0.45            0.64

I am using distplot from seaborn to plot the distribution as below:

######################## density plot #########################################
f, axes = plt.subplots(2, 2, figsize=(7, 7), sharex=True)
sns.distplot( data[cols_viz[0]] , color="skyblue", ax=axes[0, 0])
print("Skewness: %f" % data[cols_viz[0]].skew())
print("Kurtosis: %f" % data[cols_viz[0]].kurt())

sns.distplot( data[cols_viz[1]] , color="olive", ax=axes[0, 1])
print("Skewness: %f" % data[cols_viz[1]].skew())
print("Kurtosis: %f" % data[cols_viz[1]].kurt())
sns.distplot( data[cols_viz[2]] , color="gold", ax=axes[1, 0])
sns.distplot( data[cols_viz[3]] , color="teal", ax=axes[1, 1])
plt.show()

enter image description here

This does give me the values but I want them to appear within the corresponding plots instead.

How can I do this? Can someone please help me on this!

Upvotes: 1

Views: 10254

Answers (1)

MMelnicki
MMelnicki

Reputation: 712

You can use ax.text() to print text directly on to plots. I imported your DF as code and tweaked a few things:

  • Using for i, ax in enumerate(axes) will let you loop thru each ax in axes as well as get a number that corresponds to the column number, but you have to add .reshape(-1) to collapse a level in the ndarray in order to get i to range from 1-4.
  • using .iloc[:,i] will let you refer to proper column for each subplot
  • using 'transform=ax.transAxes as an argument for the ax.text() command will let you scale the axes so that the position of the text box can always be the same; I used x=0.97 and y=0.91 to roughly get it in the top-right

Here is the DF:

data = pd.DataFrame({'coll_prop_tenure': {0: 0.04, 1: 0.0, 2: 0.0, 3: 0.06, 4: 0.38, 5: 0.61, 6: 0.01, 7: 0.1, 8: 0.04, 9: 0.22, 10: 0.72, 11: 0.39}, \
                    'coll_prop_12m': {0: 0.04, 1: 0.0, 2: 0.0, 3: 0.06, 4: 0.38, 5: 0.61, 6: 0.01, 7: 0.1, 8: 0.04, 9: 0.22, 10: 0.72, 11: 0.39}, \
                    'coll_prop_6m': {0: 0.06, 1: 0.0, 2: 0.0, 3: 0.1, 4: 0.25, 5: 0.66, 6: 0.02, 7: 0.12, 8: 0.04, 9: 0.22, 10: 0.73, 11: 0.45}, \
                    'coll_prop_3m': {0: 0.08, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0, 5: 0.61, 6: 0.02, 7: 0.16, 8: 0.09, 9: 0.22, 10: 0.72, 11: 0.64}})

And here is the code:

f, axes = plt.subplots(2, 2, figsize=(7, 7), sharex=True)
sns.distplot(data.iloc[:,0], color="skyblue", ax=axes[0,0])
sns.distplot(data.iloc[:,1], color="olive", ax=axes[0,1])
sns.distplot(data.iloc[:,2], color="gold", ax=axes[1,0])
sns.distplot(data.iloc[:,3], color="teal", ax=axes[1,1])
for i, ax in enumerate(axes.reshape(-1)):
    ax.text(x=0.97, y=0.97, transform=ax.transAxes, s="Skewness: %f" % data.iloc[:,i].skew(),\
        fontweight='demibold', fontsize=10, verticalalignment='top', horizontalalignment='right',\
        backgroundcolor='white', color='xkcd:poo brown')
    ax.text(x=0.97, y=0.91, transform=ax.transAxes, s="Kurtosis: %f" % data.iloc[:,i].kurt(),\
        fontweight='demibold', fontsize=10, verticalalignment='top', horizontalalignment='right',\
        backgroundcolor='white', color='xkcd:dried blood')
plt.tight_layout()

plotOutputResult

Upvotes: 6

Related Questions