sns.set_style("whitegrid") for i in np.array(['SepalLengthCm', 'SepalWidthCm', 'PetalLengthCm', 'PetalWidthCm']): abcd=sns.FacetGrid(iris,hue="Species",size=4)\ .map(sns.distplot,i) \ .add_legend() plt.show()
Hi! Really liked the concept explanation. I have a question. Ques: As we have only 4 columns to do Uni-variate analysis, it is easier. How about scenarios where we have 100 variables. Should we only use uni-variate analysis on selected variables or is there any alternate option? Kindly help. Thanks
I am going through the playlist and I just pressed back button not because I had a doubt, I wanted to like the video.
You're really helpful!
Nice explanation
for i in column:
abcd=sns.FacetGrid(iris,hue="Typeofflower",size=4)\
.map(sns.distplot,i) \
.add_legend()
plt.show()
sns.set_style("whitegrid")
for i in np.array(['SepalLengthCm', 'SepalWidthCm', 'PetalLengthCm', 'PetalWidthCm']):
abcd=sns.FacetGrid(iris,hue="Species",size=4)\
.map(sns.distplot,i) \
.add_legend()
plt.show()
Hi! Really liked the concept explanation. I have a question.
Ques: As we have only 4 columns to do Uni-variate analysis, it is easier. How about scenarios where we have 100 variables. Should we only use uni-variate analysis on selected variables or is there any alternate option?
Kindly help. Thanks