Numpy functions cheat sheet pdf

ndarray.shape

Tuple of array shape

ndarra­y.ndim

Number of array dimensions as interger

ndarra­y.size

Number of elements in the array

ndarra­y,dtype

Data type of array’s elements

ndarra­y.base

To check if object has its own memory

arr[0]

Returns the element at index 0

arr[1,2]

Returns array element on index [1][2]

arr[0:3]

Returns the elements at indices on outer dimension

arr[0:3,2]

Returns the elements on rows 0,1,2 at column 2

arr<n

Returns an array with boolean values

~arr

Returns an array with boolean values

np.mean(arr,axis=0/1)

Compute the arithmetic mean along the specified axis.

arr.sum()

Sum of array elements over a given axis

arr.min()

Return the minimum along a given axis

arr.max()

Return the maximum along a given axis

np.var­(arr)

Compute the variance along the specified axis

np.std­(arr)

Compute the standard deviation along the specified axis.

arr.co­rrc­oef()

Return Pearson produc­t-m­oment correl­ation coeffi­cients

np.arr­ay(­object)

Creates an array

np.arr­ay(­[1,­2,3])

1D array

np.array([(1,2,3),(4,5,6)])

2D array

np.zer­os(­shape)

Return a new array of given shape and type, filled with zeros

np.one­s(s­hape)

Return a new array of given shape and type, filled with ones

np.eye(no. of rows)

Return a 2-D array with ones on the diagonal and zeros elsewhere

np.ara­nge­(st­art­,st­op,­step)

Return evenly spaced values within a given interval.

np.ran­dom.ra­nd(­shape)

Return array of random floats between 0–1 of fiven shape

np.random.randint(low,high)

Return random integers from low (inclu­sive) to high (exclu­sive)

np.linspace(start, stop, n)

Returns n evenly spaced numbers over a specified interval

np.sor­t(arr)

Returns a sorted copy of the array

np.arg­sor­t(arr)

Returns the indices that would sort an array

np.res­ize(a, new_shape)

Return a new array with the specified shape

np.dot­(arr1, arr2)

Dot product of two arrays

arr.copy()

Returns a copy of the array

arr.view()

New view of array with the same data

arr.fl­atten()

Return a copy of the array collapsed into 1D

arr.re­sha­pe(­new­_shape)

Returns an array containing the same data with a new shape

np.add(arr_1, arr_2)

Add arguments elemen­t-wise

np.subtract(arr_1, arr_2)

Subtract arguments, elemen­t-wise

np.multiply(arr_1, arr_2)

Multiply arguments, elemen­t-wise

np.divide(arr_1, arr_2)

Divide arguments, elemen­t-wise

np.power(arr_1, arr_2)

First array elements raised to powers from second array, elemen­t-wise

np.sqr­t(arr)

Return the non-ne­gative square­-root of an array, elemen­t-wise

np.log­(arr)

Natural logarithm, elemen­t-wise

np.cei­l(arr)

Rounds up to the nearest int , elemen­t-wise

np.flo­or(arr)

Rounds down to the nearest int ,eleme­nt-wise

np.abs­(arr)

Absolute value of each element in the array

np.rou­nd(arr)

Rounds to the nearest int