Section: Regplot et Lmplot | Data Visualization on Seaborn

Section outline

If you want to perform linear regressions, Seaborn provides a dedicated function: regplot().

Parameter name	Description	Format	Example
data	The dataframe you are working on	DataFrame, Series, dict, array, or list of arrays	data=table
x	Variable for the x-axis	String corresponding to a variable	x="weight"
y	Variable for the y-axis	String corresponding to a variable	y=”height”
ci	Variable allowing to control the confidence interval displayed	Integer between 1 and 100	ci=99
nboot	Variable indicating the number of bootstrap resampling that will be done	Integer	nboot=100
seed	Variable to indicate a seed for the resampling, allows reproductibility	Integer	seed=42
logistic	Variable allowing to do a logistic regression	Boolean	logistic=True
lowess	Variable allowing to do a lowess regression	Boolean	lowess=True
robust	Variable allowing to do a robust regression	Boolean	robust=True

regplot() also allows you to display the confidence interval, which is set to 95% by default.

Here is an example of code:

sns.regplot(data=data, x="bill_length_mm",y="bill_depth_mm", ci=70)
plt.show()

regplot simple

We can change the type by selecting a parameter, for example the lowess parameter, and setting it to True:

sns.regplot(data=data, x="bill_length_mm", y="bill_depth_mm",
 ci=99, lowess=True)
plt.show()

lowess regplot

The confidence interval is not displayed when using LOWESS.

Another option is lmplot(), which is more suitable for performing regressions across multiple plots.

signature lmplot

Parameter name	Description	Format	Example
data	The dataframe you are working on	DataFrame, Series, dict, array, or list of arrays	data=table
x	Variable for the x-axis	String corresponding to a variable	x="weight"
y	Variable for the y-axis	String corresponding to a variable	y=”height”
hue	Allows to add a variable as different colors	String corresponding to a variable	hue=”age”
row	Allows to create a table of plots, controling the number of rows	String corresponding to a variable	row=”category”
col	Allows to create a table of plots, controling the number of columns	String corresponding to a variable	col=”job”
ci	Variable allowing to control the confidence interval displayed	Integer between 1 and 100	ci=99
nboot	Variable indicating the number of bootstrap resampling that will be done	Integer	nboot=100
lowess	Variable allowing to do a lowess regression	Boolean	lowess=True

Here is an example of code:

sns.lmplot(data=data, x="bill_length_mm", y="bill_depth_mm", ci=95, hue="island", robust=True, col="sex")
plt.show()

lmplot

Robust and logistic regressions are also available, as with regplot(). nboot and seed are also available.