NumPy is the fundamental package for scientific computing with Python. This cheat sheet is a quick reference f.
You’ll also need to import numpy to get started:
import numpy as np
np.loadtxt('file.txt') — From a text file
np.genfromtxt('file.csv',delimiter=',') — From a CSV file
np.savetxt('file.txt',arr,delimiter=' ') — Writes to a text file
np.savetxt('file.csv',arr,delimiter=',') — Writes to a CSV file
np.array([1,2,3]) — One dimensional array
np.array([(1,2,3),(4,5,6)]) — Two dimensional array
np.zeros(3) — 1D array of length 3 all values 0
np.ones((3,4)) — 3x4 array with all values 1
np.eye(5) — 5x5 array of 0 with 1 on diagonal (Identity matrix)
np.linspace(0,100,6) — Array of 6 evenly divided values from 0 to 100
np.arange(0,10,3) — Array of values from 0 to less than 10 with step 3 (eg [0,3,6,9])
np.full((2,3),8) — 2x3 array with all values 8
np.random.rand(4,5) — 4x5 array of random floats between 0–1
np.random.rand(6,7)*100 — 6x7 array of random floats between 0–100
np.random.randint(5,size=(2,3)) — 2x3 array with random ints between 0–4
arr.size — Returns number of elements in arr
arr.shape — Returns dimensions of arr (rows,columns)
arr.dtype — Returns type of elements in arr
arr.astype(dtype) — Convert arr elements to type dtype
arr.tolist() — Convert arr to a Python list
np.info(np.eye) — View documentation for np.eye
np.copy(arr) — Copies arr to new memory
arr.view(dtype) — Creates view of arr elements with type dtype
arr.sort() — Sorts arr
arr.sort(axis=0) — Sorts specific axis of arr
two_d_arr.flatten() — Flattens 2D array two_d_arr to 1D
arr.T — Transposes arr (rows become columns and vice versa)
arr.reshape(3,4) — Reshapes arr to 3 rows, 4 columns without changing data
arr.resize((5,6)) — Changes arr shape to 5x6 and fills new values with 0
np.append(arr,values) — Appends values to end of arr
np.insert(arr,2,values) — Inserts values into arr before index 2
np.delete(arr,3,axis=0) — Deletes row on index 3 of arr
np.delete(arr,4,axis=1) — Deletes column on index 4 of arr
np.concatenate((arr1,arr2),axis=0) — Adds arr2 as rows to the end of arr1
np.concatenate((arr1,arr2),axis=1) — Adds arr2 as columns to end of arr1
np.split(arr,3) — Splits arr into 3 sub-arrays
np.hsplit(arr,5) — Splits arr horizontally on the 5th index
arr[5] — Returns the element at index 5
arr[2,5] — Returns the 2D array element on index [2][5]
arr[1]=4 — Assigns array element on index 1 the value 4
arr[1,3]=10 — Assigns array element on index [1][3] the value 10
arr[0:3] — Returns the elements at indices 0,1,2 (On a 2D array: returns rows 0,1,2)
arr[0:3,4] — Returns the elements on rows 0,1,2 at column 4
arr[:2] — Returns the elements at indices 0,1 (On a 2D array: returns rows 0,1)
arr[:,1] — Returns the elements at index 1 on all rows
arr<5 — Returns an array with boolean values
(arr1<3) & (arr2>5) — Returns an array with boolean values
~arr — Inverts a boolean array
arr[arr<5] — Returns array elements smaller than 5
np.add(arr1,arr2) — Elementwise add arr2 to arr1
np.subtract(arr1,arr2) — Elementwise subtract arr2 from arr1
np.multiply(arr1,arr2) — Elementwise multiply arr1 by arr2
np.divide(arr1,arr2) — Elementwise divide arr1 by arr2
np.power(arr1,arr2) — Elementwise raise arr1 raised to the power of arr2
np.array_equal(arr1,arr2) — Returns True if the arrays have the same elements and shape
np.sqrt(arr) — Square root of each element in the array
np.sin(arr) — Sine of each element in the array
np.log(arr) — Natural log of each element in the array
np.abs(arr) — Absolute value of each element in the array
np.ceil(arr) — Rounds up to the nearest int
np.floor(arr) — Rounds down to the nearest int
np.round(arr) — Rounds to the nearest int
np.add(arr,1) — Add 1 to each array element
np.subtract(arr,2) — Subtract 2 from each array element
np.multiply(arr,3) — Multiply each array element by 3
np.divide(arr,4) — Divide each array element by 4 (returns np.nan for division by zero)
np.power(arr,5) — Raise each array element to the 5th power
np.mean(arr,axis=0) — Returns mean along specific axis
arr.sum() — Returns sum of arr
arr.min() — Returns minimum value of arr
arr.max(axis=0) — Returns maximum value of specific axis
np.var(arr) — Returns the variance of array
np.std(arr,axis=1) — Returns the standard deviation of specific axis
arr.corrcoef() — Returns correlation coefficient of array