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Plotting graph For IRIS Dataset Using Seaborn And Matplotlib

Last Updated : 25 Apr, 2025
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Matplotlib.pyplot library is most commonly used in Python in the field of machine learning. It helps in plotting the graph of large dataset. Not only this also helps in classifying different dataset. It can plot graph both in 2d and 3d format. It has a feature of legend, label, grid, graph shape, grid and many more that make it easier to understand and classify the dataset.
 

Seaborn provides a beautiful with different styled graph plotting that make our dataset more distinguishable and attractive.
 

Installation

To install the package write the below code in terminal of ubuntu/Linux or Window Command prompt. 

pip install matplotlib
pip install seaborn


Attribute Information about data set: 

Attribute Information:
   -> sepal length in cm
   -> sepal width in cm
   -> petal length in cm
   -> petal width in cm
   -> class: 
              Iris Setosa
              Iris Versicolour
              Iris Virginica

Number of Instances: 150 

Summary Statistics:
             Min  Max   Mean    SD   Class Correlation
   sepal length: 4.3  7.9   5.84  0.83    0.7826   
    sepal width: 2.0  4.4   3.05  0.43   -0.4194
   petal length: 1.0  6.9   3.76  1.76    0.9490  (high!)
    petal width: 0.1  2.5   1.20  0.76    0.9565  (high!)

Class Distribution: 33.3% for each of 3 classes.

Plotting graph For IRIS Dataset Using Seaborn Library And matplotlib.pyplot library


Loading data 

Python3

import numpy as np 
import pandas as pd 
import matplotlib.pyplot as plt 
  
data = pd.read_csv("Iris.csv") 
    
print (data.head(10)) 

                    

                    

                        
                        
 
                    

                

                





Output:
 


iris-data



Plotting Using Matplotlib 






Python3




                

                    

                        

                            

                                

                                    
                                    

                                    
                                    
                                    

                                    
                                    

                                    
                                    
                                    
                                

                            

                        

                    

                    
import pandas as pd 
import matplotlib.pyplot as plt 
iris = pd.read_csv("Iris.csv") 
  
plt.plot(iris.Id, iris["SepalLengthCm"], "r--") 
plt.show 

                    
    
                    

                

                

                    

                        
                        

                    

                    

                        
                        
 
                    

                

                

photo 6


Scatter Plot 






Python3




                

                    

                        

                            

                                

                                    
                                    

                                    
                                    
                                    

                                    
                                    

                                    
                                    
                                    
                                

                            

                        

                    

                    
iris.plot(kind ="scatter", 
          x ='SepalLengthCm', 
          y ='PetalLengthCm') 
plt.grid() 

                    
    
                    

                

                

                    

                        
                        

                    

                    

                        
                        
 
                    

                

                

photo 7


Plotting using Seaborn 






Python3




                

                    

                        

                            

                                

                                    
                                    

                                    
                                    
                                    

                                    
                                    

                                    
                                    
                                    
                                

                            

                        

                    

                    
import seaborn as sns 
  
iris = sns.load_dataset('iris') 
  
# style used as a theme of graph  
# for example if we want black  
# graph with grid then write "darkgrid" 
sns.set_style("whitegrid") 
  
# sepal_length, petal_length are iris 
# feature data height used to define 
# Height of graph whereas hue store the 
# class of iris dataset. 
sns.FacetGrid(iris, hue ="species",  
              height = 6).map(plt.scatter,  
                              'sepal_length',  
                              'petal_length').add_legend() 

                    
    
                    

                

                

                    

                        
                        

                    

                    

                        
                        
 
                    

                

                

photo 8



                            
                            
                        


                                                                              

                                        

                                                                                

                                                                

                            

                                  
                                

                                                              

                                
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                                                    karnalrohit                                                

                                                

                                                

            
                                            

                                            
                                        

                                        

                                            
                                            

                                                
                                                
                                            

                                            

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