pandas

Series Object : one dimensional 

import pandas as pd 

data = [ [10,20,30],[40,50,60]]

series = pd.Series(data)

print("\n")

print(series) 

print("\n")

 # we can also use 

series1 = pd.Series([[10,20,30],[40,50,60]])

print(series1)

Change index name 

import pandas as pd

a = pd.Series([10,20,30,40],index=["a","b","c","d"])

print (a)

import pandas as pd

b = pd.Series([50,60,70,80],index = "a b c d".split(" "))

print (b)

Data  Frame : 2d dimension 

import pandas as pd

b = pd.DataFrame({"Name" : "apple banana mango watermelon".split(" "),"Price" : [100,200,290,800]})

print (b)

Changing index name : 

import pandas as pd

a=pd.DataFrame({"Name" : "apple banana mango watermelon".split(" "),"Price" : [100,200,290,800]})

a.rename(index ={0: "a",1:"b",2:"c ",3:"d "} , inplace = True)

print (a)

Concatenation : 

pd.concat([var, var1],axis=1)

pd.merge(var,var1,on=" ", how = " ")

import pandas as pd

df = pd.DataFrame({"name": "vishal kanchan sangita prdip abhi".split(" "),"marks_math":[80,60,70,80,80]})

print(df)

print("\n")

df1 = pd.DataFrame({"name": "vishal kanchan sangita prdip dhiraj".split(" "),"marks_sci":[80,60,70,80,67]})

print(df1)

# concatenation 

print("\n")

print(pd.concat([df, df1]))#bydefault axis0

print("\n")

print(pd.concat([df, df1],axis= 1))

Merge : 

print(pd.merge(df,df1,on= "name",how= "inner"))    ....( On= same keys in df, df1) 

print("\n")

print(pd.merge(df,df1,on="name",how="outer"))

print(pd.merge(df,df1,on= "name",how= "left")) .....also add indicator= True 

print("\n")

print(pd.merge(df,df1,on="name",how="right"))

print(pd.merge(df,df1,on= "name",how= "outer",indicator=True))