Assume that required libraries (panda and numpy) are imported and dataframe df2 has been created as per questions 17 and 18 above. Predict the output produced by following code fragment :

print(df2.loc["Jiya"])
print(df2.loc["Jiya", "IQ"])
print(df2.loc["Jiya":"Tim", "IQ":"College"]) 
print(df2.iloc[0])
print(df2.iloc[0, 5])
print(df2.iloc[0:2, 5:8])

name        Jiya
age           10
weight        75
height       4.5
siblings       1
gender         M
IQ           130
College      NaN
Name: Jiya, dtype: object
130
       IQ College
Jiya  130     NaN
Tim   105     NaN
name        Jiya
age           10
weight        75
height       4.5
siblings       1
gender         M
IQ           130
College      NaN
Name: Jiya, dtype: object
M
     gender   IQ College
Jiya      M  130     NaN
Tim       M  105     NaN

Working

1. print(df2.loc["Jiya"]) — This line prints all columns of the row with the index "Jiya".
2. print(df2.loc["Jiya", "IQ"]) — This line prints the value of the "IQ" column for the row with the index "Jiya".
3. print(df2.loc["Jiya":"Tim", "IQ":"College"]) — This line prints a subset of rows and columns using labels, from "Jiya" to "Tim" for rows and from "IQ" to "College" for columns.
4. print(df2.iloc[0]) — This line prints all columns of the first row using integer-based indexing (position 0).
5. print(df2.iloc[0, 5]) — This line prints the value of the 6th column for the first row using integer-based indexing.
6. print(df2.iloc[0:2, 5:8]) — This line prints a subset of rows and columns using integer-based indexing, selecting rows from position 0 to 1 and columns from position 5 to 7.