Python Pandas - 1

 Pandas
------
-Most Popular Python library
-It is used for Data Analysis

Two Types of Data Analysis
-------------------------
1. Series - 1D (One Dimensional array or single dimensional array)
2. DataFrames - 2D(table format)

1. Series:
----------
-Series is a one Dimensional Array(1-D)
-Store any data type(int,float,char)
-data stored on seq order

Creating Series:
----------------
import pandas as pd
a = pd.Series(Data,Index)
print(a)

Note:
-----
 data - int,float,char
 Index - 0,1....9

Ex1:
---
import pandas as pd

Data =[1, 3, 4, 5, 6, 2, 9]  #Numeric data 
s = pd.Series(Data) 

print(s)

output:
------
0    1
1    3
2    4
3    5
4    6
5    2
6    9
=============================================
Ex2:
---

import pandas as pd

Data =[10.5, 30.6, 40.5, 5.5, 6.76, 2.3, 0.9] 
s = pd.Series(Data) 

print(s)

output:
------
0    10.50
1    30.60
2    40.50
3     5.50
4     6.76
5     2.30
6     0.90
=============================================
Ex3:
---
import pandas as pd

Data =[a,b,c,r,f] 
s = pd.Series(Data) 
print(s)

output:
------
 Error
=============================================
Ex4:
---
import pandas as pd

Data =['a','b','c','r','f'] 
s = pd.Series(Data) 

print(s)

output:
------
0    a
1    b
2    c
3    r
4    f
==========================================
Ex5:
---
import pandas as pd

Data =[1, 3, 4, 5, 6, 2, 9]
Index =['a', 'b', 'c', 'd', 'e', 'f', 'g']
s = pd.Series(Data,Index) 
print(s)

output:
------
a    1
b    3
c    4
d    5
e    6
f    2
g    9
=========================================
Ex6:
---
import pandas as pd

Data =[1, 3,10.5,3.14,'a','b','c']
s = pd.Series(Data)
print(s)

output:
------
0       1
1       3
2    10.5
3    3.14
4       a
5       b
6       c
===========================================
Ex7: (Data contains Dictionary(Numeric values))
---
import pandas as pd

Data ={'a':10, 'b':20, 'c':30, 'd':80, 'e':70}  
s = pd.Series(Data)  
print(s)

output:
------
a    10
b    20
c    30
d    80
e    70
================================================
Ex8: (Data contains Dictionary(Numeric values))
---
import pandas as pd

Data ={1:10, 2:20, 3:30, 4:80, 5:70}  
s = pd.Series(Data)  
print(s)

output:
------
1    10
2    20
3    30
4    80
5    70
================================================
Ex9: (Data contains Dictionary(floating point values))
---
import pandas as pd

Data ={'a':10.5, 'b':20.5, 'c':3.14,'e':12.5}
s = pd.Series(Data)  
print(s)

output:
------
a    10.50
b    20.50
c     3.14
e    12.50
==============================================
Ex10: (Data contains Dictionary(string values))
---
import pandas as pd

Data ={'a':'jahab','b':'sudhir','c':'coimbatore'}
s = pd.Series(Data)  
print(s)

output:
------
a   jahab
b   sudhir
c   coimbatore
============================================
Ex11: (Data contains Ndarray)
---
import pandas as pd

Data =[[2, 3, 4], [5, 6, 7]]  # Defining 2darray 
s = pd.Series(Data)
print(s)

output:
------
0    [2, 3, 4]
1    [5, 6, 7]
============================================


***********************************************************
2. DataFrames:
-------------
-DataFrames is a two-dimensional Array(2-D)
-Its consists of rows and columns
 
Creating DataFrames:
----------------
import pandas as pd
s = pd.DataFrames(Data)

Note:
-----
 data - one or more Series,one or more dictionaries,2D-numpy Ndarray

Ex1: (Data is Series)
---
import pandas as pd 

s1 = pd.Series([100, 101, 102])            
s2 = pd.Series(['jahab', 'sudir', 'rino'])

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

output:
------
    Roll   Name
0   100    jahab
1   101    sudir
2   102    rino
=====================================================
Ex2: (Data is Dictionaries)
---
import pandas as pd

s1={'a':100,'b':101,'c':102}
s2 ={'a':'jahab','b':'sudhir','c':'rino'}

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

output:
------
    Roll   Name
a   100    jahab
b   101    sudir
c   102    rino
======================================================
Ex3: (Data is 2D-numpy Ndarray)
---
import pandas as pd

s1 =[[2, 3, 4], [5, 6, 7]] 
s2 =[[1, 3, 5], [6, 9, 0]] 

Data ={'First':s1, 'Second':s2}
s= pd.DataFrame(Data) 
print(s)

output:
------
     First     Second
0  [2, 3, 4]  [1, 3, 5]
1  [5, 6, 7]  [6, 9, 0]
=================================================
                   
                  Practical (DataFrame)
                    =============
A) Write a python program to Display 5 roll,name,city... using DataFrame with series

output:
------
    Roll   Name     city  
0   101    jahab    Coimbatore
1   102    sudir    Coimbatore
2   103    rino     Salem
3   104    aswin    Erode
4   105    jasmine  chennai

B) Write a python program to Display 5 roll,name,city... using DataFrame with Dictionaries

output:
------
    Roll   Name     city  
a   101    jahab    Coimbatore
b   102    sudir    Coimbatore
c   103    rino     Salem
d   104    aswin    Erode
e   105    jasmine  chennai

C) Write a python program to following output using DataFrame with Ndarray

output:
------
          A                    B                    C
0  [10, 3, 5, 8, 10]  [10, 13, 50, 8, 0]  [20, 63, 80, 5, 9]
1  [5,  6, 7, 6, 13]  [68, 90, 20, 5, 2]  [78, 80, 50, 1, 8]  
2  [8,  0, 3, 2, 16]  [90, 10, 26, 2, 9]  [34, 32, 70, 3, 7]  
3  [2,  3, 5, 8, 99]  [23, 45, 67, 3, 6]  [56, 79, 12, 7, 9]  
------------------------------------------------------------------
             (Series)
             -------
D) Define series, creating series
E) Integer Value series,Floating value series,String value Series
F) Dictionary(Integer,float,string) value series
G) Ndarray value series
-------------------------------------------------------
H) Define Python pandas, use of Python Pandas
I) Difference between Series and DataFrame
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