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Showing below up to 50 results in range #51 to #100.

51. Set printoptions (16:32, 17 October 2025)
52. Dimensions and shape (16:33, 17 October 2025)
53. Broadcasting: Automatic adaption of dimensions​ (16:35, 17 October 2025)
54. Convert other data into numpy arrays e.g. asarray (16:35, 17 October 2025)
55. New matrix (16:36, 17 October 2025)
56. Save and load (16:36, 17 October 2025)
57. Reshape and flatten (16:36, 17 October 2025)
58. Slices and Views (16:37, 17 October 2025)
59. Concatenate Matrices and arrays (16:37, 17 October 2025)
60. Merging matrices (16:38, 17 October 2025)
61. Unique (16:39, 17 October 2025)
62. Where (16:39, 17 October 2025)
63. Piecewise (16:39, 17 October 2025)
64. Extending an existing matrix: tile, repeat, pad (16:40, 17 October 2025)
65. Boolean matricies and logic functions (16:41, 17 October 2025)
66. Advanced Indexing (16:41, 17 October 2025)
67. Ravel and UnRavel (16:42, 17 October 2025)
68. Available dtypes (16:43, 17 October 2025)
69. Constants (16:43, 17 October 2025)
70. Math functions (16:44, 17 October 2025)
71. Linear algebra (16:44, 17 October 2025)
72. Random numbers the non-legacy way (16:45, 17 October 2025)
73. Statistics (16:45, 17 October 2025)
74. FFT (16:46, 17 October 2025)
75. Rfft and spectral power (16:46, 17 October 2025)
76. Spectral power and averaging over trials (16:46, 17 October 2025)
77. Meshgrid (16:47, 17 October 2025)
78. Flip, rot90, and roll a matrix (16:48, 17 October 2025)
79. Ndenumerate (16:48, 17 October 2025)
80. Ndindex (16:48, 17 October 2025)
81. Flat (16:48, 17 October 2025)
82. Einstein summation (16:50, 17 October 2025)
83. Numba: Numpy just in time compiler -- speeding Numpy up (16:50, 17 October 2025)
84. Memory layout of Numpy matrices (16:51, 17 October 2025)
85. Stack and Split, Compress (16:52, 17 October 2025)
86. Beyond normal np.save (16:52, 17 October 2025)
87. Trim Zeros of a 1d array (16:53, 17 October 2025)
88. Nditer provides many ways to visit all the elements of one or more arrays (16:54, 17 October 2025)
89. Replacing an inner for loop with apply along axis (16:54, 17 October 2025)
90. Nested iters (16:55, 17 October 2025)
91. Manipulation of integers and their bits (16:55, 17 October 2025)
92. Numpy and JSON over Pandas (16:56, 17 October 2025)
93. Resize: Compensation for bad planning? Don't! (16:57, 17 October 2025)
94. Dealing with the main diagonal / triangles of a matrix (16:57, 17 October 2025)
95. Dealing with Matlab files (16:59, 17 October 2025)
96. Matlab is also just a Python package (16:59, 17 October 2025)
97. Running Python remotely from Matlab (16:59, 17 October 2025)
98. NumPy for MATLAB users (16:59, 17 October 2025)
99. Simple plot and imshow examples (17:02, 17 October 2025)
100. Subplot (17:04, 17 October 2025)