Tutorial 9- Seaborn Tutorial- Distplot, Joinplot, Pairplot Part 1
Вставка
- Опубліковано 1 жов 2019
- Hello All,
Welcome to the Python Crash Course. In this video we will understand about Seaborn
github url : github.com/krishnaik06/Machin...
Support me in Patreon: / 2340909
Connect with me here:
Twitter: / krishnaik06
Facebook: / krishnaik06
instagram: / krishnaik06
If you like music support my brother's channel
/ @ultralifeproject
Buy the Best book of Machine Learning, Deep Learning with python sklearn and tensorflow from below
amazon url:
www.amazon.in/Hands-Machine-L...
You can buy my book on Finance with Machine Learning and Deep Learning from the below url
amazon url: www.amazon.in/Hands-Python-Fi...
Subscribe my unboxing Channel
/ @krishnaikhindi
Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning!
Deep Learning Playlist: • Tutorial 1- Introducti...
Data Science Projects playlist: • Generative Adversarial...
NLP playlist: • Natural Language Proce...
Statistics Playlist: • Population vs Sample i...
Feature Engineering playlist: • Feature Engineering in...
Computer Vision playlist: • OpenCV Installation | ...
Data Science Interview Question playlist: • Complete Life Cycle of...
You can buy my book on Finance with Machine Learning and Deep Learning from the below url
amazon url: www.amazon.in/Hands-Python-Fi...
🙏🙏🙏🙏🙏🙏🙏🙏
YOU JUST NEED TO DO
3 THINGS to support my channel
LIKE
SHARE
&
SUBSCRIBE
TO MY UA-cam CHANNEL
there are many institutions including online courses charging anything more than 1 lack but not able explain concisely and clearly the you way you do it.
I like your explanation very much.
Negative correlation implies that if one is increasing other is decreasing (in reference to 11:01 )
Yes you're right it got me confused as well he should address it for future viewers
Crystal clear explanation .I bet no online courses explain it so well. Thanks a lot
This video is amazing!! I was having some issues with graphs , you just cleared every problem of mine in a single video. Thank You So much!!
This Guy is Amazing. He can teach you Data science in a very simple way. Cheers!!!!!
Thanks for this video,Krish. Very well elucidated. Request you to kindly correct your notebook and change "JoinPlot" to "JointPlot"
Like the way you explain things . So precise and clear. Kudos to you 👍👍
[On lighter note] Apart from your wonderful way to describe the complex concept to simple manner, One thing I noticed and important to note: "This is pretty much simple" :D
Inreference to 11:01 Negative correlation means those features are inversely proportional.It clearly means one increases will result into another one decreasing.
Krish sir. You are an inspiration. I am a student of upgrad but I am learning through your video about Data Analytics. Thanks a lot sir.
you really nailed..i was struggling to plot seaborn graphs..
Correction: correlation is (+) means they are directly proportional
correlation is (-) means they are inversely proportional
kdkk bhaii thankss
Thank you for all these efforts and helping people out. I am in love with you. :)
Please dont scare him with #Metoo sentiment .. :))
Bro... u r the best educator.
Hi Krish. One small suggestion. You can use
import warnings
warnings.filterwarnings("ignore")
to ignore the warnings that you are otherwise getting when plotting the distplot.
File ko kaise read kare restaurant wale data ko python me
Nice video.
Have one question, when to use dist plots?
joinplot & pairplot explained when to use.
Can't wait for EDA
Carry on sir
please next video
Thank you for clear explanantion
how can we know what is independent variable and which is dependent feature.i mean every time in the question we may not get the details of this thing? can you please explain for this
Around 11:15, you said if total bill is decreasing then tip also decreases which is negatively correlated however they should actually head in opposite directions if the total bill increases, then the tip should be decreasing, correct?
Thank you for the sharing👍
Krish it's too interesting...❤💫
It would be nice to add service quality feature like (low,medium, good, very good) to predict tip......
Keep it up
very helpful sir thank you
when i done practical in clg i just get output as some fig. and i was happy with that like i'm getting ourtput. But here i undersand the meaning behind that fig. like regression lines, heatmap and all also i understand waht really problems are and what innsigts fig are providing
i am bit confused for the x and y labels in the command " sns.jointplot(x='tip', y ='total_bill', data=df, kind='hex') " which starts some where at 13:00. the confusion is, x label should be 'total_bill' and y should be 'tip' because tip is dependent on the bill and there are many chances when there is no tip at all, customer just pay the bill it means tip is dependent not the bill. will you please clarify this doubt?
How to understand dependent and independent variable,bacause you told in this video "tips" is dependent variable,please answer the question.
@11:00 negative correlation mens as one feature value increase next feature value decreases as of i knew.
Correct me sir if m wrong.
ya its that way.
Sir why did I get an error in this statement.. df=sns.load_dataset("tips")
How do you analyse this graph 11:54 by looking at it?
Nice sir
So what type of technique we could use to find out the relationship between categorical features and the dependent variable?
Great question.
We can use bar plot to show this relationship.
sns.barplot(x='sex',y='tip',data=df)
seaborn.pydata.org/tutorial/categorical.html take a look at this, this covers most of the techniques!
you can use Predictive Power Score but with higher dimensionality, the computational power of PPS is high
Can refer this : towardsdatascience.com/rip-correlation-introducing-the-predictive-power-score-3d90808b9598
@@sashpatra88 helpfull
which correlation is good? positive or negative?
Thanks Krish
Krish my question is in join plot when you have taken two features and calling it both. bivariate and univariate. so clr that one. what we have to consider and why?
ohk i got the answer...
Hey for drawing the diagrams how do you do?
Hi Krish.. I see in Tab that u were seeing singam song .. Kadhal vandale kaal rendum song.. While recording this video
Sir I am getting confused where I have to use brackets and square brackets, While typing code and retrieving data. where exactly we use bracket and square bracket ?
we use square brackets when we wokring with pandas data frame and selecting the column like df.["ttips"] and otherwise we use round brackets.
did u complete this playlist ?
Sir how to see parameters of a function in colab shift+tab is not working
I have a question, can you tell me how to identify the dependent or independent feature.
Price is depend upon area so price become dependent variable and area become independent same like this
The 'tips' file...where it is came from.. please anyone can explain to em who can understand??
Sir i am getting while loading dataset, URLError:
Note: distpot() has been depricated use displot() instead. :)
In loading this dataset it is showing error
Where and how tips dataset
thanks
AttributeError: module 'seaborn' has no attribute 'replot' . Can someone confirm what was done to fix this error?
df.corr() showing error
It shows: could not convert string to float for the data frame in starting of video @ 10.01
Correct is df. Corr(numeric_only=True)
@@PyGeniusStudios-official Thank you. Even I got the same error
Hello sir while practicing sea born I'm getting this error(RuntimeError: In FT2Font: Can not load face.) please tell me to solve this error
I am also getting the same error
For practice
sir..what is kaggle ?
I'm getting value error when i'm trying to convert the dataset into correaltion matrix
u can try this code: df.corr(numeric_only = True)
Sir i cant run this code
Dear sir please give the link of iris data set link
Sir will you please make a video on Hypothesis testing.
+1
Can we publish this reports
Anyone can answer
what is KDE??
I'm getting error for df.corr(). How could you didn't get any error
getting valueerror when running df.corr().can anyone help
same isuue
Sir ye file restaurant wali kaise read kare python me
df.corr() is not working
it shows could not convert string to float: 'no
@prathamchauhan5140
1 second ago
for this error: could not convert string to float instead of writing dfcorr()
write this--> df.corr(numeric_only=True)
Jointplot
Sir, In kaggle which dataset are you import ? please give the URL of that dataset called tips
tips is there an in built data set of seaborn library. the data set is available in the library itself you have to read the file. hope this helps.
Can anyone resolve it, Why df.corr() is showing error of 'string can't be converted into int'
you can drop the columns that are having categorical values from dataset using df.drop(['smoker','sex','day','time'],axis=1,inplace=True)
and try
@@sainikhil6890 Thanks
from where to get tips data set
it's already inbuilt within the seaborn module
You can get the same table. Write the correct code !
@NITESH KUMAR did you get the solution...I am also facing same problem
tut9 done
14/04/2024
@KrishNaik sir
Can Any body tell me please I am getting this error
ValueError: could not convert string to float: 'No'
when I run cell with df.corr() what should I Do
my code:-
import seaborn as sns
df = sns.load_dataset("tips")
df.corr()
df_numeric = df.select_dtypes(include=['float64', 'int64'])
use this above df.corr()
@@og6265 again iam getting same error as valueError : couldn't convert string to float
@@km02editz69 i am also getting same error
for this error: could not convert string to float instead of writing dfcorr()
write this--> df.corr(numeric_only=True)
@@prathamchauhan5140 Thank you so much great help
Getting valueError: couldn't convert string to float
When iam trying to execute df.corr()
@prathamchauhan5140
1 second ago
for this error: could not convert string to float instead of writing dfcorr()
write this--> df.corr(numeric_only=True)
df =sns.load_dataset("tips")
df.head()
df.corr()
it gives an error: could not convert string to float
what we have to do? sir..
im also facing the same error how to overcome this
bro did you got any idea
@@ncerttamil7129 df_encoded = pd.get_dummies(df)
correlation_matrix = df_encoded.corr()
df_encoded.head()
Firstly import pandas as pd
@@ncerttamil7129 df_encoded = pd.get_dummies(df) # here we change strings values into int values then only we can correlate
correlation_matrix = df_encoded.corr()
correlation_matrix.head()
df_encoded = pd.get_dummies(df) # here we change strings values into int values then only we can correlate
correlation_matrix = df_encoded.corr()
correlation_matrix.head()
Then sns.heatmap(correlation_matrix)
correlation find kaise hoga?
df.corr() not working...its not creating matrix and hence fails to work
plz reply
same
@@nakulmehta8372 For the newer pandas version you need to specify: df.corr (numeric_only=True). Should work then
@prathamchauhan5140
1 second ago
for this error: could not convert string to float instead of writing dfcorr()
write this--> df.corr(numeric_only=True)
@@nakulmehta8372
@prathamchauhan5140
1 second ago
for this error: could not convert string to float instead of writing dfcorr()
write this--> df.corr(numeric_only=True)
The explanation of correlation was incorrect...if the correlation coefficient is negative then it means if total bill increases then tip decreases
if anyone cares to explain df.corr() is giving error
ValueError: could not convert string to float: 'No'
df.corr(numeric_only=True)
Hi Krish Dada
I am following your videos of python and machine learning
Till now I am into seaborn tutorial
I am from database background
Will need your help to understand once I have hands on in the topics of
Machine learning, how can I prepare for interviews and can jump to this new domain
Though its very early to ask as I have just started but your response will be highly appreciated
Thanks Dada
Day 4 - 19/02/2024
Without tips..... Any real project.... All tutorial chanel casting only tips....its Inbuild data... No need, i need real data wotk out problems
Plz help
Correction -->
df.corr(numeric_only=True)
@ 10:19