Pair Plot in Seaborn: Lecture 3 | Python Seaborn | Exploratory Data Analysis | Applied AI Course
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- Опубліковано 30 вер 2017
- Pair Plot in Seaborn: Lecture 3 | Python Seaborn | Exploratory Data Analysis | Applied AI Course
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Easiest and the most in-depth explanation of pair plots i have seen on youtube. thank you.
This is perhaps the most elaborated and clearly explained illustration that I came across about the pair plot. Thanks, man.
Jeez Man! This dude is a genius.
Insanely good!
Can't resist me from subscribing to the channel!
My god it's so simple and clear..man you are unbelievable! Thanks a million ❤❤❤❤
now I understand what pair plots are used for! thank you.
God bless you
thank you for the fantastic explanation
Thanks for your explanation!!
Good Lecture......
great sir
Thank you sir.... You are fantastic
One of the best explanation
Can't resist my self to subscribe his channel
just understand the interpretation.
thank you!!
Outstanding!
Thank you!
Wow👌
What is the importance of size attribute..in this video you have assigned 3 to size attribute...and in the 2d scatter plot video you have assigned 4 to size attribute.
can you please show how to add correlation coefficient in pairplot?
Hello Sir, Thanks for brilliant video on Pair plot ,I have some queries on these.In the last 16 graphs, we selected only one as it was showing iris-setosa in separate side and other 2 are also on other separated location (only some case are indeed mixed) .
.But if i see other graphs also similar and giving good graph prediction for example 3 column 4th graphs.
this is also giving good picture. Why we didnt use that graph. can you please brief i am still trying to understand the decision matrix here as i am new in this and still learning.
Secondly what about the second set with 6 graphs. can we use that one also .
and also can you help on the use of bar graphs .
Please drop all your queries at team@appliedaicourse.com
Hello sir,
My question is, why pair plot didnt consider the species column while it considered 1st 4 columns?
Did we specify somehow that the last column is the Class column and how do pair plot know which columns to take?
It's not numeric column so it will not be considered
here we have specified using hue parameter i.e hue = "species" so using this feature which is class label it divides points belongs to setosa,versicolor and verginica based on 4 numeric features.
God will bless.
As you dealt with me so well in this knowledge, your helper shall locate you in Jesus name.
Name Iris is not defined (my error)
Try to load the datafile first as:
iris = pd.read_csv("iris.csv")