Numpy and Pandas Interview Questions

S.No Question
1. What is NumPy, and what are its main features?
2. Explain the concept of an ndarray in NumPy.
3. What are the different types of arrays in NumPy?
4. How do you create an array in NumPy?
5. What are the commonly used data types in NumPy arrays?
6. Explain some of the array attributes in NumPy.
7. What are the different array creation patterns in NumPy?
8. How do you perform indexing and slicing on NumPy arrays?
9. What is broadcasting in NumPy?
10. How can you iterate over elements in a NumPy array?
11. Explain some common array manipulation techniques in NumPy.
12. What are some string functions available in NumPy?
13. What mathematical functions are available in NumPy?
14. What are some arithmetical functions provided by NumPy?
15. How do you perform statistical calculations on NumPy arrays?
16. Explain some sort, search, and counting functions in NumPy.
17. What additional functionality does NumPy provide for matrices?
18. What is Pandas, and why is it used?
19. What are the main data structures in Pandas?
20. Explain the Series and DataFrame objects in Pandas.
21. What are the basic functionalities of a Series in Pandas?
22. How do you perform descriptive statistics on Pandas Series?
23. Explain function application in Pandas.
24. What is reindexing in Pandas?
25. How can you iterate over elements in a Pandas Series or DataFrame?
26. How do you sort data in a Pandas DataFrame?
27. What are the different methods for indexing and selecting data in Pandas?
28. How do you perform statistical calculations on Pandas data structures?
29. What are some common aggregation functions in Pandas?
30. How do you handle missing data in Pandas?
31. Explain the concept of the groupby function in Pandas.
32. What are the different methods for merging and joining data in Pandas?
33. How do you work with categorical data in Pandas?
34. What is the purpose of the dtype parameter in NumPy arrays?
35. Explain the difference between shape and reshape in NumPy.
36. How can you convert a NumPy array to a list?
37. What is the purpose of the ndim attribute in NumPy arrays?
38. How do you create an identity matrix using NumPy?
39. Explain the purpose of the .shape attribute in NumPy.
40. How can you reverse the order of elements in a NumPy array?
41. What is the purpose of the np.where() function in NumPy?
42. How do you calculate the sum of all elements in a NumPy array?
43. Explain the difference between np.dot() and np.matmul() in NumPy.
44. How do you calculate the standard deviation of a NumPy array?
45. What is the purpose of the np.unique() function in NumPy?
46. Explain the concept of axis in NumPy.
47. How do you perform element-wise multiplication of two NumPy arrays?
48. What is the purpose of the np.zeros() function in NumPy?
49. How can you concatenate two NumPy arrays vertically?
50. Explain the concept of strides in NumPy arrays.
51. What is the purpose of the np.full() function in NumPy?
52. How do you calculate the transpose of a NumPy array?
53. Explain the difference between shallow copy and deep copy in NumPy.
54. What is the purpose of the np.diag() function in NumPy?
55. How can you generate random numbers using NumPy?
56. Explain the concept of broadcasting in NumPy.
57. How do you calculate the mean of a specific axis in a NumPy array?
58. What is the purpose of the np.linspace() function in NumPy?
59. How can you find the maximum value in a NumPy array?
60. Explain the np.expand_dims() function in NumPy.
61. What is the purpose of the np.argmax() function in NumPy?
62. How do you convert a NumPy array to a Pandas DataFrame?
63. Explain the difference between loc and iloc in Pandas.
64. How can you read a CSV file into a Pandas DataFrame?
65. What is the purpose of the .head() method in Pandas?
66. How do you calculate the mean of a specific column in a Pandas DataFrame?
67. Explain the .apply() function in Pandas.
68. What is the purpose of the .sort_values() method in Pandas?
69. How can you select rows based on a condition in a Pandas DataFrame?
70. Explain the concept of hierarchical indexing in Pandas.
71. How do you handle missing data in a Pandas DataFrame?
72. What is the purpose of the .groupby() method in Pandas?
73. How can you merge two Pandas DataFrames based on a common column?
74. Explain the concept of outer join in Pandas merging.
75. How do you select specific columns from a Pandas DataFrame?
76. What is the purpose of the .value_counts() method in Pandas?
77. How can you replace missing values in a Pandas DataFrame?
78. Explain the .pivot() method in Pandas.
79. What is the purpose of the pd.cut() function in Pandas?
80. How do you convert categorical data into numerical values in Pandas?
81. Explain the concept of one-hot encoding in Pandas.
82. How do you calculate the sum of a specific column in a Pandas DataFrame?
83. What is the purpose of the .fillna() method in Pandas?
84. How can you group data by multiple columns in a Pandas DataFrame?
85. Explain the difference between merge() and join() in Pandas.
86. How do you convert a Pandas DataFrame to a NumPy array?
87. What is the purpose of the .to_csv() method in Pandas?
88. How can you drop duplicate rows from a Pandas DataFrame?
89. Explain the .idxmax() method in Pandas.
90. How do you rename columns in a Pandas DataFrame?
91. What is the purpose of the .iterrows() method in Pandas?
92. How can you select rows based on multiple conditions in a Pandas DataFrame?
93. Explain the concept of multi-indexing in Pandas.
94. How do you calculate the median of a Pandas Series?
95. What is the purpose of the .clip() method in Pandas?
96. How can you handle time series data in Pandas?
97. Explain the .nunique() method in Pandas.
98. How do you calculate the correlation between two columns in a Pandas DataFrame?
99. What is the purpose of the .str.contains() method in Pandas?
100. How can you convert a Pandas Series to a Python list?

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