Methods for array creation in Numpy
Function | Description |
---|---|
empty() | Return a new array of given shape and type, without initializing entries |
empty_like() | Return a new array with the same shape and type as a given array |
eye() | Return a 2-D array with ones on the diagonal and zeros elsewhere. |
identity() | Return the identity array |
ones() | Return a new array of given shape and type, filled with ones |
ones_like() | Return an array of ones with the same shape and type as a given array |
zeros() | Return a new array of given shape and type, filled with zeros |
zeros_like() | Return an array of zeros with the same shape and type as a given array |
full_like() | Return a full array with the same shape and type as a given array. |
array() | Create an array |
asarray() | Convert the input to an array |
asanyarray() | Convert the input to an ndarray, but pass ndarray subclasses through |
ascontiguousarray() | Return a contiguous array in memory (C order) |
asmatrix() | Interpret the input as a matrix |
copy() | Return an array copy of the given object |
frombuffer() | Interpret a buffer as a 1-dimensional array |
fromfile() | Construct an array from data in a text or binary file |
fromfunction() | Construct an array by executing a function over each coordinate |
fromiter() | Create a new 1-dimensional array from an iterable object |
fromstring() | A new 1-D array initialized from text data in a string |
loadtxt() | Load data from a text file |
arange() | Return evenly spaced values within a given interval |
linspace() | Return evenly spaced numbers over a specified interval |
logspace() | Return numbers spaced evenly on a log scale |
geomspace() | Return numbers spaced evenly on a log scale (a geometric progression) |
meshgrid() | Return coordinate matrices from coordinate vectors |
mgrid() | nd_grid instance which returns a dense multi-dimensional “meshgrid |
ogrid() | nd_grid instance which returns an open multi-dimensional “meshgrid |
diag() | Extract a diagonal or construct a diagonal array |
diagflat() | Create a two-dimensional array with the flattened input as a diagonal |
tri() | An array with ones at and below the given diagonal and zeros elsewhere |
tril() | Lower triangle of an array |
triu() | Upper triangle of an array |
vander() | Generate a Vandermonde matrix |
mat() | Interpret the input as a matrix |
bmat() | Build a matrix object from a string, nested sequence, or array |
Numpy | Array Creation
In this article, we are going to explore numpy array creation technique.
Table of Content
- Array creation using List :
- Array creation using array functions
- Methods for array creation in Numpy
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