QnA – Select Access data from Dataframe

 Q – 1 What are the way to select or access data from a dataframe?

Ans.: You can select or access data from a dataframe in following ways:

    1. Using column name(s)
    2. Using .net notation
    3. Using loc[]
    4. Using iloc[]
    5. Using slicing
    6. Individual Value using at[] & iat[]

Q -2 Consider the folloowing dataframe and do as directed:

import pandas as pd





A. Write code to access data of Mouse and Scanner columns.


B. Write code to access data of the Keyboard column using dot notation and column name.


C. Write code to access data of scanners using loc[].


D. Write code to access data of all columns where mouse data is more than 200.


E. Write code to access columns using 0 and 2.


F. Write code to access data of rows of jan and march for scanner and keyboard.


  • Consider the above dataframe and predict the output:

a)       print(df.iloc[1][2]) → 280

b)      print(df.loc[‘Feb’,’Scanner’]) →  280

c)       df1=df[df[‘Keyboard’]>190] 

       print(df1[[‘Mouse’,’Scanner’]])      Mouse  Scanner

                                                        Feb      200      280

                                                        April    400      450

d)      print(df.iat[2,1]) → 190

  •         Consider the above dataframe and find out errors in following code fragment:

a.       df[1,3] èCorrection: df.iloc[:,[1.3]]

b.       df.loc[2,2] èCorrection: loc needs index of row and column, df.loc[‘March’,’Scanner’]

c.       df.at[1][1]èCorrection: at also required coloumn name, df.at[‘Feb’,’Keyboard’]

d.       df.iloc[0;2,1] èCorrection: Semicolon will be replaced with :, df.iloc[0:2,1]

  •        Explain following code lines in your words, what it will do:

a. df.iloc[:2,] → It will access row indexes from 0:2 (exclude 2) and all columns of dataframe.

b. df.loc[:,’Mouse’] → It will access mouse data with all rows.

c. df.at[‘March’,’Scanner’] → Access Scanner details of March Month.

d. df.iloc[2,0] → Access the value located at row index 2 (‘Macrh’) and column index 0 (Mouse)

e.       df.iloc[0:2,0:1] → It will access rows ranges 0 to 2 and columns 0 to 1 excluding upper limit index number.

f.        df.iloc[:,2] → Access all rows and column index 2.

Q – 3 What is the difference between loc[] and iloc[]?

Ans.: Both are used to access data from dataframe with a list of rows and columns. Loc requires columns names whereas iloc requires index number.
Q – 4 What is the difference between at[] and iat[]?
Ans.: Similar as above only just replace the words loc[] and iloc[] with at[] and iat[].

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