Introduction to NumPy Maryam Tavakol Machine Learning Group Winter - - PowerPoint PPT Presentation

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Introduction to NumPy Maryam Tavakol Machine Learning Group Winter - - PowerPoint PPT Presentation

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Introduction to NumPy Maryam Tavakol Machine Learning Group Winter semester 2016/17 1 What is NumPy? Short for Numerical Python Wikipedia : NumPy is an extension to the Python programming language, adding support for large,

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Introduction to NumPy

Maryam Tavakol

Machine Learning Group

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Winter semester 2016/17

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What is NumPy?

  • Short for Numerical Python
  • Wikipedia: NumPy is an extension to the Python

programming language, adding support for large, multi-dimensional arrays and matrices, along with a large library of high-level mathematical functions to

  • perate on these arrays

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Properties

  • A fast and efficient multidimensional array object

ndarray

  • Functions for performing element-wise

computations with arrays or mathematical

  • perations between arrays
  • Tools for reading and writing array-based data sets

to disk

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Properties

  • Linear algebra operations, Fourier transform, and

random number generation

  • Tools for integrating connecting C, C++, and

Fortran code to Python

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Areas of Functionality

  • Fast vectorized array operations for data munging

and cleaning, subsetting and filtering, transformation, and any other kinds of computations

  • Common array algorithms like sorting, unique, and

set operations

  • Efficient descriptive statistics and aggregating/

summarizing data

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Areas of Functionality

  • Data alignment and relational data manipulations

for merging and joining together heterogeneous data sets

  • Expressing conditional logic as array expressions

instead of loops with if-elif-else branches

  • Group
  • wise data manipulations (aggregation,

transformation, function application)

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ndarrays

  • At the core of the NumPy package, is the ndarray
  • bject which encapsulates n-dimensional arrays of

homogeneous data.

  • Many operations performed using ndarray objects

execute in compiled code for performance

  • The standard scientific packages use ndarray

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Creating ndarray

  • The easiest way to create an array is to use the

array function

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Creating ndarray

  • Nested sequences, like a list of equal-length lists,

will be converted into a multidimensional array

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Creating ndarray

  • In addition to np.array, there are a number of
  • ther functions for creating new arrays

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Creating ndarray

  • It is not safe to assume that np.empty will return

an array of all zeros

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Functions

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Functions (cont.)

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Example

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Data Types

  • The data type or dtype is a special object

containing the information the ndarray needs to interpret

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Data Types

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Data Types

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Data Types

  • You can convert or cast an array from one dtype to

another using ndarray’s astype method

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Array Attributes

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Operations on Arrays

  • Any arithmetic operations between equal-size

arrays applies the operation element-wise

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Operations on Arrays

  • Arithmetic operations with scalars are as you would

expect, propagating the value to each element

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Example

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Indexing & Slicing

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Indexing & Slicing

  • Indexing on a 2D array

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Indexing & Slicing

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Example

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More Example

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Boolean Indexing

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Boolean Indexing

  • To select all the rows with corresponding name

“Bob”

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Boolean Indexing

  • You can mix that with other indexing

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Fancy Indexing

  • A way of indexing using integer arrays

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Transposing Arrays

  • Transposing is a special form of reshaping which

similarly returns a view on the underlying data without copying anything: arr.T

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Transposing Arrays

  • When doing matrix computations, you will do this

very often, like for example computing the inner matrix product using np.dot

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Universal Functions

  • A function that performs element-wise operations
  • n data in ndarrays

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Universal Functions

  • Unary functions: take one argument
  • Binary functions: take 2 arrays and return a single

array as the result

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Unary Functions

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Unary Functions

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Binary Functions

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Binary Functions

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Data Processing

  • Expressing many kinds of data processing tasks as

concise array expressions rather than writing loops

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Conditional Logic

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Statistical Methods

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Array I/O

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Other Methods

  • Boolean arrays
  • Sorting
  • Set Operations
  • Linear Algebra
  • Matrix multiplication, decompositions,

determinants, and other square matrix math

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Linear Algebra

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