Class 12 Python Pandas 1 MCQ | Python Pandas 1 Quiz Class 12 Preview Class 12 Python Pandas 1 MCQ | Python Pandas 1 Quiz Class 12 0% Multiple Choice Questions Class 12 Python Pandas 1 Informatics Practices 1 / 34 1. Which of the following is not true about Dataframe? a. None of these b. Dataframe index can be a string c. Dataframe can be created using dictionaries d. Dataframe is size immutable 2 / 34 2. To change 2nd row ānd 4th column's value 50 in dataframe D1, we can write _____. a. D1.iat[2, 4] = 50 b. D1.iat[3, 4] = 50 c. D1.iat[3, 5] = 50 3 / 34 3. To create an empty Series object, we can use a. pd.series(np.NaN) b. pd.series(empty) c. pd.series() d. All of these 4 / 34 4. To get the number of elements in a series object, _____ attribute can be used. a. itemsize b. size c. ndim d. index 5 / 34 5. Which of the following statements is false? a. Dataframe is immutable. b. Dataframe is capable of holding multiple types of data. c. Dataframe is size-mutable. d. Dataframe is values-mutable. 6 / 34 6. To access value of dataframe using column label we can use ________ a. loc b. All of these c. dataframe_object.column_label 7 / 34 7. To delete a row from a DataFrame, we can use _____ statement. a. drop b. remove c. del d. cancel 8 / 34 8. To get a number representing number of axes in a Dataframe, _____ attribute may be used. a. values b. ndim c. shape d. size 9 / 34 9. Which among the following options can be used to create a DataFrame in Pandas? a. Dictionary b. All of these c. Scalar value d. ndarray 10 / 34 10. To specify datatype int16 for a series object, we can write _______ a. All of the above b. pd.series(data = array, dtype = numpy.int16 ) c. pd.Series(data = array.dtype = pandas.int16) d. pd.Series(data = array, dtype = int16) 11 / 34 11. The axis 0(Zero) specifies Dataframe's _____. a. values b. datatype c. rows d. columns 12 / 34 12. The axis 1 specifies Dataframe's _____. a. Rows b. Columns c. Values d. Datatype 13 / 34 13. To get the size of the datatype of the items in series object, we can use _____ attribute. a. size b. itemsize c. index d. ndim 14 / 34 14. To access sname column from 'Student' DataFrame we can use _________ a. All of these b. Student.sname c. Student['sname'] 15 / 34 15. To display the 3rd and 4th columns from the 6th to 8th rows of a Dataframe D1, we can use _____. a. D1.iloc[6:9, 3:5] b. D1.iloc[6:8, 3:4] c. D1.iloc[6:8, 3:5] 16 / 34 16. Identify the correct statement : a. NaN is used for missing data in Pandas b. All of the mentioned c. Series works similar to an array 17 / 34 17. Which attribute of DataFrame is used to retrieve its shape? a. Empty b. T c. Shape d. Ndim 18 / 34 18. Which of the following commands is used to install Pandas? a. python install pandas b. pip install python-pandas c. pip install pandas d. python install python 19 / 34 19. To get the number of bytes of the series data, _____ attribute is used. a. dtype b. ndim c. hasnans d. nbytes 20 / 34 20. Which of the following is not an attribute of Dataframe? a. transponse b. Size c. axes d. empty 21 / 34 21. what is the output of following:print(D1.loc[:]) a. All columns b. All rows and columns c. None of these d. All rows 22 / 34 22. To check if the series object contains NaN values, _____ attribute is used. a. ndim b. nbytes c. dtype d. hasnans 23 / 34 23. Full form of CSV is ____________ a. Column Separated Variable b. Comma Separated Values c. Comma Separated Variables d. Column Separated Values 24 / 34 24. Missing data in Pandas object is represented as a. Null b. None c. NaN d. Missing 25 / 34 25. Command to display both row and column index label of dataframe D1 __________ a. D1.index( ) b. D1.axes( ) c. D1.axis( ) 26 / 34 26. Which attribute of DataFrame is used to perform the transpose operation on a DataFrame? a. Shape b. T c. Ndim d. Empty 27 / 34 27. How many axis does a Dataframe have? a. None of these b. One c. Two d. Three 28 / 34 28. Which of the following is a valid statement to create a data frame. a. DF=pd.dataframe(dictionary1) b. DF=pd.DataFrame(dictionary1) c. DF=pd.Dataframe(dictionary1) d. All of these 29 / 34 29. To display third element of a series object S1, you can write _____. a. S1[:3] b. S1[3] c. S1[:2] d. S1[2] 30 / 34 30. A two-dimensional labelled array that is an ordered collection of columns to store heterogeneous data types is: a. DataFrame b. Panel c. Series d. NumPy array 31 / 34 31. To get the number of dimensions of a series object, _____ attribute is used. a. itemsize b. size c. ndim d. index 32 / 34 32. To display last five rows of a Series object S1, you can write _____. a. S1.tail() b. S1.head() c. S1.head(5) d. S1.tail (5) 33 / 34 33. To get the transpose of a Dataframe D1, you can write _____. a. All of these b. D1.Transpose c. D1.Swap d. D1.T 34 / 34 34. To display first three elements of a Series object S1, you can write _____. a. S1[3rd] b. S1[:3] c. All of these d. S1[3] Your score is The average score is 65% LinkedIn Facebook Twitter VKontakte 0% Restart quiz Spread the love Lesson tags: Class 12 Python Pandas 1 MCQ, Python Pandas 1 Quiz Class 12 Python Pandas 2 Class 12 Informatics Practices Multiple Choice Questions 2023 Back to: CBSE class 12 Informatics Practices notesSpread the love