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NumPy CheatSheet for Developers

Introduction-What-is-NumPy?​

A library consisting of multidimensional array objects and a collection of routines for processing those arrays.

Key and Imports​

We use following shorthand in the cheat sheet:

CommandDescription
npimport numpy library
np.arrayThe array object in NumPy
np.array.shapeThe shape of an array is the number of elements in each dimension.
np.array.reshapeReshaping means changing the shape of an array(Example 1-D to 2-D)
np.zeros(3)1D array of length 3 all zeros
np.zeros((2,3))2D array of all zeros
np.zeros((3,2,4))3D array of all zeros
np.full((3,4),2)3x4 array with all values 2
np.random.rand(3,5)3x5 array of random floats between 0 and 1
np.ones((3,4))3x4 array with all values 1
np.eye(4)4x4 array of 0 with 1 on diagonal

Data Types In NumPy​

NumPy has some extra data types, and refer to data types with one character, like i for integers, u for unsigned integers etc.

Below is a list of all data types in NumPy and the characters used to represent them.

CommandDescription
iinteger
b boolean
uunsigned integer
ffloat
ccomplex float
mtimedelta
Mdatetime
Oobject
Sstring
U unicode string
Vfixed chunk of memory for other type ( void )

Save And Load Data​

Text/CSV files:​

CommandDescription
np.loadtxt('New_file.txt')From a text file
np.genfromtxt('New_file.csv',delimiter=',') From a CSV file
np.savetxt('New_file.txt',arr,delimiter=' ') Writes to a text file
np.savetxt('New_file.csv',arr,delimiter=',') Writes to a CSV file

Properties:​

CommandDescription
array.sizeReturns number of elements in array
array.shapeReturns dimensions of array(rows,columns)
array.dtypeReturns type of elements in array

Operations​

KeywordsDescriptionAction
np.copy(array)Copies array to new memory array.Copying
view(dtype)Creates view of array elements with type dtypeCopying
array.sort()Sorts arraySorting
array.sort(axis=0)Sorts specific axis of arraySorting
array.reshape(2,3)Reshapes array to 2 rows, 3 columns without changing data.Sorting
np.append(array,values)Appends values to end of arrayAdding
np.insert(array,4,values)Inserts values into array before index 4Adding
np.delete(array,2,axis=0)Deletes row on index 2 of arrayRemoving
np.delete(array,3,axis=1)Deletes column on index 3 of arrayRemoving
np.concatenate((array1,array2),axis=0)Adds array2 as rows to the end of array1Combining
np.concatenate((array1,array2),axis=1)Adds array2 as columns to end of array1Combining
np.split(array,3)Splits array into 3 subarrays
a[0]=5Assigns array element on index 0 the value 5Indexing
a[2,3]=1Assigns array element on index [2][3] the value 1Indexing
a[2]Returns the element of index 2 in array a.Subseting
a[3,5]Returns the 2D array element on index [3][5]Subseting
a[0:4]Returns the elements at indices 0,1,2,3Slicing
a[0:4,3]Returns the elements on rows 0,1,2,3 at column 3Slicing
a[:2]Returns the elements at indices 0,1Slicing
a[:,1]Returns the elements at index 1 on all rowsSlicing

Array Mathematics​

Operation typeSyntaxAction
Additionnp.add(a,b)Arithmetic Operations
Subtractionnp.subtract(a,b)Arithmetic Operations
Multiplicationnp.multiply(a,b)Arithmetic Operations
Divisionnp.divide(a,b)Arithmetic Operations
Exponentiationnp.exp(a)Arithmetic Operations
Square Rootnp.sqrt(b)Arithmetic Operations
Element-wisea==bComparison
Array-wisenp.array_equal(a,b)Comparison

Functions​

Operation TypeSyntax
Array-wise Suma.sum()
Array-wise min valuea.min()
Array row max valuea.max(axis=0)
Meana.mean()
Mediana.median()