Python-DATAFRAME Basic Functions and Operations

Python DATAFRAME Basic Functions and Operations

CREATING DATAFRAME

 import pandas as pd

a= {'PNAME':['TV','AC','TV','WM','AC','TV'], 'COMP':['LG','WIRLPOOL','SONY','WIRLPOOL','LG','LG'], 'PRICE':[10000,25000,15000,12000,28000,15000],'QTY':[2,5,15,8,12,5]} df = pd.DataFrame(a,index=['P1','P2','P3','P4','P5','P6']) 

********************************************* FETCH SINGLE COLUMN

 print(df['PNAME'])ORprint(df.PNAME)

OUTPUT

 

 

 

 

 

 

********************************************* FETCH MULTIPLE COLUMNS

 print(df[['PNAME','PRICE']])

OUTPUT

 

 

 

 

 

 

 

 

********************************************* FETCH SINGLE ROW

 

 print(df.loc['P2'])
ORprint(df.iloc[1])

OUTPUT

  *********************************************

 FETCH MULTIPLE ROWS

 print(df.loc[['P2','P5']])

OUTPUT

 

 

 

 

*********************************************

 FETCH SOME ROWS, SOME COLUMNS

 print(df.loc[['P2','P5'],['PNAME','PRICE']])

OUTPUT

 

 

 

 

*********************************************

 FETCH SINGLE VALUE 

print(df['COMP']['P3'])

OUTPUT

 

  

*********************************************

 FETCH ALL VALUES HAVING QTY>5

 print(df[ (df['QTY']>5) ])

OUTPUT

 

 

 

 

*********************************************

 FETCH TOP 3 ROWS

print(df.head(3))

OUTPUT

 

 

 

 

 

 

*********************************************

 FETCH LAST 3 ROWS

 print(df.tail(3))

 OUTPUT

 

 

 

 

 

*********************************************

 ADDING NEW COLUMN 
df['DISCOUNT'] = [1,4,2,6,8,3]OR
df.loc[:,'DISCOUNT'] = [1,4,2,6,8,3] OR 
df.at[:,'DISCOUNT'] = [1,4,2,6,8,3]  

 OUTPUT

********************************************* ADDING NEW ROW

df.loc['P10',:] = ['OS', 'ANDROID', 5000, 6]  OR df.at['P10',:] = ['OS', 'ANDROID', 5000, 6]

 OUTPUT

********************************************* DELETING A COLUMN  

 del df['COMP']  
OR df.drop(['COMP'],axis=1,inplace=True)  
OR df.drop(df.columns[1],axis=1,inplace=True)

 OUTPUT

 ********************************************* DELETING MULTIPLE COLUMNS

 df.drop(['PNAME','PRICE'],axis=1,inplace=True) OUTPUT

********************************************* DELETING A ROW

 
 df.drop(['P1'],axis=0,inplace=True)ORdf.drop(df.index[0],axis=0,inplace=True)

 OUTPUT

********************************************* DELETING MULTIPLE ROWS 

 df.drop(['P1','P2'],axis=0,inplace=True)
 OUTPUT

********************************************* UPDATE COLUMN VALUES  

 df['PRICE'] = [1,2,3,4,5,6]
 

********************************************* UPDATE COLUMN WITH A SINGLE VALUE  
df['PRICE'] = 5

********************************************* UPDATE A ROW WITH A SINGLE VALUE 
 df.loc['P1',:] = 5 

********************************************* UPDATE A ROW WITH DIFFERENT VALUES   
df.loc['P1',:] = [1,2,3,4]

********************************************* UPDATE A SPECIFIC RECORD 

 df['PRICE']['P1'] = 5
OR

df.loc['P1','PRICE'] = 5

OR

df.at['P1','PRICE'] = 5

********************************************* MISC FUNCTIONS

*********************************************

INCREASE VALUE OF QTY COLUMN BY 10  

df['QTY'] += 10

  

*********************************************SORT DATAFRAME BY QTY

 df.sort_values(axis=0,ascending=False,inplace=True,by=['QTY'])
 

*********************************************SUM OF QTY COLUMN

 print('SUM OF COLUMN IS = ', df['QTY'].sum())

*********************************************MINIMUM AND MAXIMUM VALUE FROM QTY COLUMN

print('MINIMUM QTY IS = ', df['QTY'].min())
print('MAXIMUM QTY IS = ', df['QTY'].max())

*********************************************MINIMUM AND MAXIMUM VALUE FROM EACH COLUMN 

print('MINIMUM IS = \n', df.min())
print('MAXIMUM IS = \n', df.max()) 

AS 

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