NCERT Class 12 Informatics Practices MCQ : Python Pandas Part 1
Embark on a strategic journey into the realm of sports planning with our specialized Multiple Choice Questions (MCQs) page on “Planning in Sports: Case-Based Questions.” Immerse yourself in real-world scenarios and strategic decision-making, featuring questions meticulously curated from the previous year papers of diverse exams, including the prestigious UPSC IAS exams.
This resource is intricately designed to provide a comprehensive understanding of the planning processes in sports, offering case-based questions that mirror the challenges faced by sports managers and planners. Whether you’re a sports management enthusiast or a student preparing for competitive exams, these MCQs offer a strategic approach to mastering the intricacies of sports planning.
Prepare with confidence, knowing that our collection mirrors the diverse question formats encountered in exams across different sectors. From analyzing case studies on sports events to understanding the strategic decisions behind successful sports programs, this page serves as a valuable tool for honing your knowledge of planning in sports.
Gain a competitive edge by accessing insights derived from real-world applications and historical perspectives embedded in our MCQs. Navigate through the complexities of sports planning confidently, armed with knowledge distilled from previous year papers and designed to help you excel in exams.
NCERT Class 12 Informatics Practices : Python Pandas Part 1 MCQ – NCERT Class 12 MCQ
Question:
To create an empty series object, you can use:
A
B
C
D
Question:
To specify datatype int 16 for a series object,you can write
A
B
C
D
Question:
To get the number of dimensions of a series object, attribute is displaye(d
A
B
C
D
Question:
To get the size of the datatype of the items in series object,
A
B
C
D
Question:
To get the number of elements in a series object, attribute may be use(d)
A
B
C
D
Question:
To check if the series object contains NaN values, attribute
is displaye(d)
A
B
C
D
Question:
To display third element of a series object S, you will write
A
B
C
D
Question:
To display first three elements of a series objects you may write
A
B
C
D
Question:
To display last five rows of a series objects you may write
A
B
C
D
Question:
Missing data in Pandas object is represented through:
A
B
C
D
Question:
Given a Pandas series called SeQuestion uences, the command which will display the
A
B
C
D
Question:
If a dataframe is created using a 2D dictionary, then the
indexes/row labels are formed from
A
B
C
D
Question:
If a dataframe is created using a 2D dictionary, then the column labels are formed from
A
B
C
D
Question:
The axis 0 identifies a dataframe's
A
B
C
D
Question:
The axis 1 identifies a dataframes
A
B
C
D
Question:
To get the number of elements in a dataframe attribute
may be use(d)
A
B
C
D
Question:
To get NumPy representation of a dataframe ……… attribute may be use(d)
A
B
C
D
Question:
To get a number representing number of axes in a
dataframe, ……….. attribute may be use(d
A
B
C
D
Question:
To get the transpose of a dataframe Dl, you can write
A
B
C
D
Question:
To extract row/column from a dataframe,……….. function may be use(d
