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07_13.py
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# Section 7.13 snippets
# reshape vs. resize
import numpy as np
grades = np.array([[87, 96, 70], [100, 87, 90]])
grades
grades.reshape(1, 6)
grades
grades.resize(1, 6)
grades
# flatten vs. ravel
grades = np.array([[87, 96, 70], [100, 87, 90]])
grades
flattened = grades.flatten()
flattened
grades
flattened[0] = 100
flattened
grades
raveled = grades.ravel()
raveled
grades
raveled[0] = 100
raveled
grades
# Transposing Rows and Columns
grades.T
grades
# Horizontal and Vertical Stacking
grades2 = np.array([[94, 77, 90], [100, 81, 82]])
np.hstack((grades, grades2))
np.vstack((grades, grades2))
##########################################################################
# (C) Copyright 2019 by Deitel & Associates, Inc. and #
# Pearson Education, Inc. All Rights Reserved. #
# #
# DISCLAIMER: The authors and publisher of this book have used their #
# best efforts in preparing the book. These efforts include the #
# development, research, and testing of the theories and programs #
# to determine their effectiveness. The authors and publisher make #
# no warranty of any kind, expressed or implied, with regard to these #
# programs or to the documentation contained in these books. The authors #
# and publisher shall not be liable in any event for incidental or #
# consequential damages in connection with, or arising out of, the #
# furnishing, performance, or use of these programs. #
##########################################################################