Glossary

Glossary

Below is the summary of all the functions and methods that you learned in this lesson:

Category: General Purpose

Function/Method	Description
`numpy.ndarray.dtype`	Return the data-type of the elements of the array. Remember, arrays are homogeneous.
`numpy.ndarray.ndim`	Return the number of array-dimensions (rank), e.g., it will return 2 for a 4x3 array.
`numpy.ndarray.shape`	Return a tuple representing the array dimensions, e.g., it will return `(rows,columns)` for a rank 2 array.
`numpy.ndarray.size`	Return the number of elements present in the array.
`numpy.save`	Save an array to `.npy` (numpy) format.
`numpy.load`	Load array from the `.npy` files.
`numpy.random.random`	Return random floats values from the interval [0.0, 1.0), in a specified shape.
`numpy.random.randint`	Return random integers from the half-open interval [a, b), in a specified shape.
`numpy.random.normal`	Return random samples from a Gaussian (normal) distribution.
`numpy.random.permutation`	Return a randomly permuted sequence from the given list
`numpy.reshape` `numpy.ndarray.reshape`	Returns an array containing the same elements with a new shape, without affecting the the original array.

Category: Array Creation

Function/Method	Description
`numpy.ones`	Return a new array of given shape and type, filled with 1s.
`numpy.zeros`	Return a new array of given shape and type, filled with 0s.
`numpy.full`	Return a new array of given shape and type, filled with a specific value.
`numpy.eye`	Return a 2-D array with 1s on the diagonal and 0s elsewhere.
`numpy.diag`	Extract the diagonal elements.
`numpy.unique`	Return the sorted unique elements of an array.
`numpy.array`	Create an n-dimensional array.
`numpy.arange`	Return evenly spaced values within a given half-open interval [a, b).
`numpy.linspace`	Return evenly spaced numbers over a specified interval [a,b].
`numpy.ndarray.copy`	Returns a copy of the array.

Category: Operating with Elements and Indices

Function/Method	Description
`numpy.insert`	Insert values along the given axis before the specified indices.
`numpy.delete`	Return a new array, after deleting sub-arrays along a specified axis.
`numpy.append`	Append values at the end of the specified array.
`numpy.hstack`	Return a stacked array formed by stacking the given arrays in sequence horizontally (column-wise).
`numpy.vstack`	Return a stacked array formed by stacking the given arrays, will be at least 2-D, in sequence vertically (row-wise).
`numpy.sort`	Return a sorted copy of an array.
`numpy.ndarray.sort`	Sort an array in-place.

Category: Set Operations

Function/Method	Description
`numpy.intersect1d`	Find the intersection of two arrays.
`numpy.setdiff1d`	Find the set difference of two arrays.
`numpy.union1d`	Return the unique, sorted array of values that are in either of the two input arrays.

Category: Arithmetic and Statistical Operations

Function/Method	Description
`numpy.add`	Element-wise add given arrays
`numpy.subtract`	Subtract arguments of given arrays, element-wise.
`numpy.multiply`	Multiply arguments of given arrays, element-wise.
`numpy.divide`	Returns a true division of the inputs, element-wise.
`numpy.exp`	Calculate the exponential of all elements in the input array.
`numpy.power`	First array elements raised to powers from second array, element-wise.
`numpy.sqrt`	Return the non-negative square-root of an array, element-wise.
`numpy.ndarray.min`	Return the minimum along the specified axis.
`numpy.ndarray.max`	Return the maximum along a given axis.
`numpy.mean` `numpy.ndarray.mean`	Compute the arithmetic mean along the specified axis.
`numpy.median`	Compute the median along the specified axis.