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