Python Pandas - 2

 DataFrame
---------
Functions:
--------
1. head()   - select row(top based)
2. tail()   - Select row(bottom based)
3. loc()    - select row(label based)
4. iloc()   - select row (index based)
5. ix()     - select row both label & index based
6. sort_values() - sort values
7. drop()   - delete both row and column
8. del()    - delete column
9. pop()    - delete column
10. rename() - rename column name
11. Boolean Index
12. merge()   - merge two dataframes based on left,right,outer,inner
13. concate() - combine dataframes
================================================
Ex1: (Creating a DataFrame using Dictionary)
----
import pandas as pd

s1 ={0:100,1:101,2:102}
s2 ={0:'jahab',1:'sudhir',2:'rino'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}
s= pd.DataFrame(Data) 
print(s)

output:
------
    Roll   Name     City
0   100    jahab    Salem
1   101    sudhir   coimbatore
2   102    rino     chennai
=======================================================
Ex3: (using head function)
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
print(s.head(2))

output:
------
    Roll    Name    City
0   100     jahab   Salem
1   101     sudhir  coimbatore
=======================================================
Ex4: (using tail function)
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
print(s.tail(2))

output:
------
    Roll    Name    City
2   102     rino    chennai
3   103     Jasmine chennai
=======================================================
Ex5: (Selecting Data using loc function) - Label based
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
print(s.loc[1])      

output:
------
 Roll           101
 Name        sudhir
 City    coimbatore
=======================================================
Ex6: (Selecting Data using loc function) - Label based(select Column)
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
print(s.loc[:,'Roll'])      

output:
------
0 100
1 101
2 102
3 103
===============================================
Ex7: (Selecting Data using iloc function) - Integer based
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
print(s.iloc[2])      

output:
------
 Roll        102
 Name       rino
 City    chennai
=========================================================
Ex8: (Selecting Data using sorting_values() function)
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
print(s.sort_values(by='Name'))

output:
------
    Roll    Name    City
0   100     jahab   Salem
3   103     Jasmine chennai
2   102     rino    chennai
1   101     sudhir  coimbatore
===========================================================
Ex9: (Deleting Data using drop() function) - delete row
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
print(s.drop(0))

output:
------
    Roll    Name    City
1   101     sudhir  coimbatore
2   102     rino    chennai
3   103     Jasmine chennai
=================================================================
Ex10: (Deleting Data using drop() function) - delete column
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
print(s.drop('Name',axis=1))

output:
------
    Roll  City
0   100   Salem
1   101   coimbatore
2   102   chennai
3   103   chennai
====================================================================
Ex11: (Deleting Data using del() function) - delete column
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
del s['Name']
print(s)

output:
------
    Roll  City
0   100   Salem
1   101   coimbatore
2   102   chennai
3   103   chennai
==============================================================
Ex12: (Deleting Data using pop() function) - delete column
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
s.pop('Name')
print(s)

output:
------
    Roll  City
0   100   Salem
1   101   coimbatore
2   102   chennai
3   103   chennai
==============================================================
Ex13: (Rename column using rename() function)
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
s=s.rename(columns={'Name':'First'})
print(s)

output:
------
    Roll    First    City
0   100     jahab   Salem
1   101     sudhir  coimbatore
2   102     rino    chennai
3   103     Jasmine chennai
==============================================================
Ex14: (Boolean index)
---
import pandas as pd

s1 ={0:100,1:101,2:102,3:103}
s2 ={0:'jahab',1:'sudhir',2:'rino', 3:'jasmine'}
s3 ={0:'Salem',1:'coimbatore',2:'chennai', 3:'chennai'}

Data ={'Roll':s1, 'Name':s2, 'City':s3}

s= pd.DataFrame(Data)
s= pd.DataFrame(Data,index=[True,False,True,True])
print(s)

output:
------
        Roll  Name    City
True    101   sudhir  coimbatore
False   100   jahab   Salem
True    101   sudhir  coimbatore
True    101   sudhir  coimbatore
=========================================================
Ex15: (merge() function)
----
import pandas as pd
s1 ={0:100,1:101}
s2 ={0:'jahab',1:'sudhir'}
s3 ={0:'Salem',1:'coimbatore'}
Data ={'Roll':s1, 'Name':s2, 'City':s3}
s= pd.DataFrame(Data)

s4 ={0:100,1:101}
s5 ={0:'Jasmine',1:'Rino'}
s6 ={0:'Salem',1:'coimbatore'}
Data1 ={'Roll':s4, 'Name':s5, 'City':s6}
s1= pd.DataFrame(Data1)
print(pd.merge(s,s1,on='Roll'))

output:
------
    Roll  Name_x      City_x      Name_y   City_y
0   100   jahab       Salem       Jasmine  Salem
1   101   sudhir      coimbatore  Rino     coimbatore
=======================================================================
Ex16: (using Concat function)
----
import pandas as pd

s1 ={0:100,1:101}
s2 ={0:'jahab',1:'sudhir'}
s3 ={0:'Salem',1:'coimbatore'}
Data ={'Roll':s1, 'Name':s2, 'City':s3}
s= pd.DataFrame(Data)

s4 ={0:100,1:101}
s5 ={0:'Jasmine',1:'Rino'}
s6 ={0:'Salem',1:'coimbatore'}
Data1 ={'Roll':s4, 'Name':s5, 'City':s6}
s1= pd.DataFrame(Data1)
print(pd.concat([s,s1]))

output:
------
    Roll   Name    City
0   100    jahab   Salem
1   101    sudhir  coimbatore
0   100    Jasmine Salem
1   101    Rino    coimbatore   
===================================================================
      (Binary Operator Functions)
      -----------------------------
-Combine two values to produce a new value.
1. add() - Adding of two DataFrames
2. sub() - subtracting DataFrame from another DataFrame
3. mul() - multiplying DataFrame with another DataFrame
4. div() - divison DataFrame from another DataFrame
5. mod() - modulo divison DataFrame from another DataFrame(get remainder value)

Ex17: Adding of two DataFrames using add()
====
import pandas as pd

s1 =[[2, 3, 4]] 
Data1 =s1
res1= pd.DataFrame(Data1) 

s2 =[[1, 3, 5]] 
Data2=s2
res2=pd.DataFrame(Data2)

res=res1.add(res2)

print('Output')
print(res)

output:
------
   0  1  2
0  3  6  9
========================================
Ex18: subtracting DataFrame from another DataFrame using sub()
====
import pandas as pd

s1 =[[2, 3, 4]] 
Data1 =s1
res1= pd.DataFrame(Data1) 

s2 =[[1, 3, 5]] 
Data2=s2
res2=pd.DataFrame(Data2)

res=res1.sub(res2)

print('Output')
print(res)

output:
------
   0  1  2
0  1  0 -1
============================================
Ex19: multiplying DataFrame with another DataFrame using mul()
====
import pandas as pd

s1 =[[2, 3, 4]] 
Data1 =s1
res1= pd.DataFrame(Data1) 

s2 =[[1, 3, 5]] 
Data2=s2
res2=pd.DataFrame(Data2)

res=res1.mul(res2)

print('Output')
print(res)

output:
------
   0  1   2
0  2  9  20
==============================================
Ex20: divison DataFrame from another DataFrame using div()
====
import pandas as pd

s1 =[[2, 3, 4]] 
Data1 =s1
res1= pd.DataFrame(Data1) 

s2 =[[1, 3, 5]] 
Data2=s2
res2=pd.DataFrame(Data2)

res=res1.div(res2)

print('Output')
print(res)

output:
------
    0    1    2
0  2.0  1.0  0.8
==========================================
Ex21: modulo divison DataFrame from another DataFrame using mod()
====
import pandas as pd

s1 =[[2, 3, 4]] 
Data1 =s1
res1= pd.DataFrame(Data1) 

s2 =[[1, 3, 5]] 
Data2=s2
res2=pd.DataFrame(Data2)

res=res1.mod(res2)

print('Output')
print(res)

output:
------
   0  1  2
0  0  0  4
===========================================