In [1]:

    

import pandas as pd


    

In [7]:

    

iris=pd.read_csv("http://vincentarelbundock.github.io/Rdatasets/csv/datasets/iris.csv",header=None)


    

In [8]:

    

iris.head()


    

    
Out[8]:






  

    

      

      
0
      
1
      
2
      
3
      
4
      
5
    
  
  

    

      
0
      
NaN
      
Sepal.Length
      
Sepal.Width
      
Petal.Length
      
Petal.Width
      
Species
    
    

      
1
      
1.0
      
5.1
      
3.5
      
1.4
      
0.2
      
setosa
    
    

      
2
      
2.0
      
4.9
      
3
      
1.4
      
0.2
      
setosa
    
    

      
3
      
3.0
      
4.7
      
3.2
      
1.3
      
0.2
      
setosa
    
    

      
4
      
4.0
      
4.6
      
3.1
      
1.5
      
0.2
      
setosa
    
  

In [10]:

    

iris2=iris.iloc[1:,1:]


    

In [11]:

    

iris2.head()


    

    
Out[11]:






  

    

      

      
1
      
2
      
3
      
4
      
5
    
  
  

    

      
1
      
5.1
      
3.5
      
1.4
      
0.2
      
setosa
    
    

      
2
      
4.9
      
3
      
1.4
      
0.2
      
setosa
    
    

      
3
      
4.7
      
3.2
      
1.3
      
0.2
      
setosa
    
    

      
4
      
4.6
      
3.1
      
1.5
      
0.2
      
setosa
    
    

      
5
      
5
      
3.6
      
1.4
      
0.2
      
setosa
    
  

In [12]:

    

import os as os


    

In [13]:

    

os.getcwd()


    

    
Out[13]:





'C:\\Users\\Dell\\Documents'

In [18]:

    

iris2.to_csv("iris2.csv")


    

In [4]:

    

iris.info()


    

    




<class 'pandas.core.frame.DataFrame'>
RangeIndex: 150 entries, 0 to 149
Data columns (total 6 columns):
Unnamed: 0      150 non-null int64
Sepal.Length    150 non-null float64
Sepal.Width     150 non-null float64
Petal.Length    150 non-null float64
Petal.Width     150 non-null float64
Species         150 non-null object
dtypes: float64(4), int64(1), object(1)
memory usage: 7.1+ KB

In [19]:

    

os.getcwd()


    

    
Out[19]:





'C:\\Users\\Dell\\Documents'

In [20]:

    

os.chdir('C:\\Users\\Dell\\Desktop')


    

In [21]:

    

os.listdir()


    

    
Out[21]:





['.Rhistory',
 '16508797_10155115909410362_414170078812994931_n.jpg',
 '27032014_Duplicate_Statement.pdf',
 '30072015_form_du-degree.pdf',
 'ACK.html',
 'ACK_files',
 'adult.data.txt',
 'AJAY.xps',
 'Basics of SQL & RDBMS _ Must Skills For Data Science Professionals.html',
 'Basics of SQL & RDBMS _ Must Skills For Data Science Professionals_files',
 'BigDiamonds (2).csv',
 'BigDiamonds.csv',
 'BigDiamonds.csv (2).zip',
 'BigDiamonds2.csv',
 'BLOOD REPORT.pdf',
 'CAM- Ajay Ohri.pdf',
 'cam.xps',
 'cam2.pdf',
 'cdo.jpeg',
 'clustersas.html',
 'dap class 4.R',
 'dap_class_4.html',
 'desktop.ini',
 'Dropbox.lnk',
 'dupform.pdf',
 'DVD.csv',
 'GermanCredit.csv',
 'Git Shell.lnk',
 'GitHub.appref-ms',
 'GoToMeeting.lnk',
 'groceries.csv',
 'Guidelines-CBSE.html',
 'IMS proschool',
 'iris2.csv',
 'logistic regression - script for ppt.R',
 'OnlineCardNSR.pdf',
 'PaymentForm.pdf',
 'Program 1-results.rtf',
 'Rdatasets',
 'Results_ Modeling and Forecasting.html',
 'Results_ Program 5.sas.html',
 'Results_ Time Series Exploration.ctk.html',
 'Rplot.png',
 'Rplot01.pdf',
 'Rplot02.pdf',
 'Rplot03.png',
 'rsconnect',
 'sas-university-edition-107140.pdf',
 'SQL-1.png',
 'sql.jpg',
 'sqlcheatsheet.jpg',
 'sqljoins_cheatsheet.png',
 'Sunstone - Google Docs.pdf',
 'test',
 'Trarscript_Form.pdf']

In [ ]: