| 1 |
np.array() |
Creates an array for which the elements are given by an array-like object, which, for example, can be a (nested) Python list, a tuple, an iterable sequence, or another ndarray instance. |
| 2 |
np.zeros() |
Creates an array with the specified dimensions and data type that is filled with zeros. |
| 3 |
np.ones() |
Creates an array with the specified dimensions and data type that is filled with ones. |
| 4 |
np.diag() |
Creates a diagonal array with specified values along the diagonal and zeros elsewhere. |
| 5 |
np.arange() |
Creates an array with evenly spaced values between the specified start, end, and increment values. |
| 6 |
np.linspace() |
Creates an array with evenly spaced values between specified start and end values, using a specified number of elements. |
| 3 |
np.logspace() |
Creates an array with values that are logarithmically spaced between the given start and end values. |
| 3 |
np.meshgrid() |
Generates coordinate matrices (and higher-dimensional coordinate arrays) from one-dimensional coordinate vectors. |
| 3 |
np.fromfunction() |
Creates an array and fills it with values specified by a given function, which is evaluated for each combination of indices for the given array size. |
| 3 |
np.formfile() |
Creates an array with the data from a binary (or text) file. NumPy also provides a corresponding function np.tofile with which NumPy arrays can be stored to disk and later read back using np.fromfile. |
| 3 |
np.getfromtxt(), np.loadtxt() |
Create an array from data read from a text file, for example, a commaseparated value (CSV) file. The function np.genfromtxt also supports data files with missing values. |
| 3 |
np.random.rand() |
Generates an array with random numbers that are uniformly distributed between 0 and 1. Other types of distributions are also available in the np. random module. |
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