Thursday, April 16, 2020

CREATE DataFrame AND ACCESSING THE SUBSET OF DataFrame


CREATE DataFrame  AND ACCESSING THE SUBSET OF DataFrame
Creating a Pandas DataFrame
 A Pandas DataFrame will be created by loading the datasets from existing storage, storage can be SQL Database, CSV file, and Excel file. Pandas DataFrame can be created from the lists, dictionary, and from a list of dictionary etc. Dataframe can be created in different ways here are some ways by which we create a dataframe:
1.Create a Pandas DataFrame from Lists
CODE1:
import pandas as pd
import numpy as np
# intialise data of lists of Samsung Products.
data = {
            'ITEM NAME':['Galaxy 5G', 'GALAXY S', 'GALAXY TAB S6', 'GALAXY A', 'QLED 8K'],
            'EXPENDITURE':[25000, 28000, 32000, 29500,45000],
            'ITEM CATEGORY':['SMART PHONE','SMART PHONE','TABLET','SMART PHONE','TV']                     
       }   
# Create DataFrame  #df is the object
df = pd.DataFrame(data)   
# Print the output.
df
output:
          ITEM NAME   EXPENDITURE ITEM CATEGORY                                      COLUMN NAME
____________________________________________
0
Galaxy 5G
25000
SMART PHONE
1
GALAXY S
28000
SMART PHONE
2
GALAXY TAB S6
32000
TABLET
3
GALAXY A
29500
SMART PHONE
4
QLED 8K
45000
TV




·         IF WE DONOT DECLARE INDEXES NAME THEN IT SHOWS BY DEFAULT STARTS FROM 0 TO ONWARDS




Code #2: Dataframe using list with index and column names:
import pandas as pd
import numpy as np
# intialise data of lists of Samsung Products.
data = { 'ITEM NAME':['Galaxy 5G', 'GALAXY S', 'GALAXY TAB S6', 'GALAXY A',
                      'QLED 8K'],
        'EXPENDITURE':[25000, 28000, 32000, 29500,45000],
       'ITEM CATEGORY':['SMART PHONE','SMART PHONE','TABLET','SMART PHONE','TV']
                       
       }
# Create DataFrame
df = pd.DataFrame(data,index=['a','b','c','d','e'])   
# Print the output.
df
output
          ITEM NAME   EXPENDITURE ITEM CATEGORY                                      COLUMN NAME
____________________________________________
a
Galaxy 5G
25000
SMART PHONE
b
GALAXY S
28000
SMART PHONE
c
GALAXY TAB S6
32000
TABLET
d
GALAXY A
29500
SMART PHONE
e
QLED 8K
45000
TV




Selecting/accessing a column:
v  Select one column using this syntax:
           <DataFrame object> [<column name>]
                             Or
           <DataFrame object>.<column name>
v  Select multiple  column using this syntax:
            <DataFrame object> [[<column name>,<column name>,……]]
Example:
From code#2
df [‘ITEM NAME’]
                             ITEM NAME
a
Galaxy 5G
b
GALAXY S
c
GALAXY TAB S6
d
GALAXY A
e
QLED 8K

df[[‘ITEM NAME’,’EXPENDITURE’]]
          ITEM NAME  EXPENDITURE
a
Galaxy 5G
25000
b
GALAXY S
28000
c
GALAXY TAB S6
32000
d
GALAXY A
29500
e
QLED 8K
45000
Selecting/accessing a subset from a DataFrame using Row/Columns Names
We can to select/acess a subset from a dataframe object:
syntax
<DataFrameObject>.loc[<startrow>:<endrow>,<startcolumn>:<endcolumn>]
v  To acess a single row,just give the row name/label at this
Syntax
df object.loc[<row label>,:]
Examples:
df.loc[‘d’]
v  To acess multiple rows
Syntax
<Dfobject>.loc[<start row>:<end row>, :]
Example
df.loc[‘a’:’b’, : ]
v  To acess selective columns
Syntax:
df.loc [:,<start column>:<end column>]
example:
df.loc[: ,’ITEM NAME’:’EXPENDITURE’]
v  To acess range of columns from a range of rows
Syntax:
<df object>.loc[<start column>:<end row>,<start column>:<end column>]
Example:
Df.loc [‘a’: ’b’,’ ITEM NAME’:’EXPENDITURE’]







Obtaining a subset/slice from a DataFrame using Row/Colmun Numeric Index/position
We can extract subset from dataframe using the row and column numeric index/position,but this time we will use iloc instead of loc means integer location.
Syntax:
           <df object>.iloc[<start row index>:<end row index>,<start col index>:<end col index>]
           Example:
         df.iloc[0:2,0:2]
v  Selecting/accessing Individual Value
Syntax
<dfobject>.<column>[<row name or numeric index>]
Example:
Df.ITEMNAME[‘a’]
     Questions:
v Create a DataFrame  object  df1 having an column name rollno, class, phone    number and indexes is Name of the students.

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