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A. import scipy.constants DataFrame.from_dict operates like the DataFrame constructor except for the orient parameter which is ‘columns’ by default. What will be output for the following code. What will be output for the following code? These Python SciPy Multiple Choice Questions (MCQ) should be practiced to improve the Data Science skills required for various interviews (campus interview, walk-in interview, company interview), placements, entrance exams and other competitive examinations. D. from scipy.constants.package. D. scientific library. (A) visual (B) matlibplot (C) matplotlib (D) matlab. Data analysis is a growing … These Python SciPy Multiple Choice Questions (MCQ) should be practiced to improve the Data Science skills required for various interviews (campus interview, walk-in interview, company interview), placements, entrance exams and other competitive examinations. 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What will be output for the following code? These topics are chosen from a collection of most authoritative and best reference books on Python. a = np.array([[3, 2, 0], [1, -1, 0], [0, 5, 1]]) Statistical Inference and Regression Models. So, prepare yourself for the rigors of interviewing and stay sharp with the nuts and bolts of data science. B. array([ 2., -2., 9.]) Data Science with Python is being utilized as a part of numerous businesses. Questions are unordered. Python MCQ Quiz & Online Test: Below is few Python MCQ test that checks your basic knowledge of Python. 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D. array([ 2., -2., 9., -9. In that spirit, here are my python interview/job preparation questions and answers. Explanation: from scipy.constants is used. MCQ No - 1. which one of these skills is not required to become a Data Scientist. These Python NumPy Multiple Choice Questions (MCQ) should be practiced to improve the Data Science skills required for various interviews (campus interview, walk-in interview, company interview), placements, entrance exams and other competitive examinations. B. source library The section contains questions and answers on raw data, processed data, tidy data, web reading, API, data summarization and merging, regular expressions and text variables. 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