Course Python NumPy

In the course Python NumPy the Python packages NumPy en MatplotLib are discussed. These Python add-on libraries are very useful for the creation of data analysis and data processing applications.

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  • Course Python NumPy : Content

    Overview NumPy and SciPy

    The course starts with an overview of NumPy and its sister library SciPy and how we can install these libraries.

    NumPy ndarray

    Next the NumPy's ndarray object and its methods are discussed. Attention is paid to many different array manipulation techniques. These methods process large data sets very efficiently.

    Matrix Handling

    Next matrix handling with Numpy is treated and attention is paid to special routines for ordening, searching and comparing data in matrices.


    Finally the MatplotLib library is discussed. This library is closely integrated with NumPy and SciPy and this makes it a very powerful tool to create and plot complex figures. The course uses real world examples to visualize of one- and two dimensional data.

  • Course Python NumPy : Training

    Audience Python NumPy Course

    The course Python NumPy is intended for scientists and Big Data analysts who want to use Python with NumPy and MatPlotLib for data analysis and data processing.

    Prerequisites Course Python NumPy

    To participate in this course prior knowledge of Python programming is necessary. Knowledge of numerical methods is beneficial for the understanding.

    Realization Training Python NumPy

    The theory is dealt with on the basis of presentation slides. The concepts are illustrated with demos. The theory is interspersed with exercises. The course times are from 9.30 to 16.30.

    Certification Python NumPy

    The participants receive an official certificate Numerical Python after succesful completion of the course.

    Course Numerical Python
  • Course Python NumPy : Modules

    Module 1 : Numpy Intro

    Module 2 : Common Functions

    Module 3 : Matrices

    What is NumPy?
    What is SciPy?
    Installing NumPy
    NumPy array object
    Selecting elements
    NumPy numerical types
    Data type objects
    dtype constructors
    dtype attributes
    Onedimensional slicing and indexing
    Multidimensional slicing and indexing
    Array comparisons
    any(),all(), slicing, reshape()
    Manipulating array shapes
    Stacking and Splitting arrays
    Converting arrays
    Methods of ndarray
    Clipping arrays
    Compressing arrays
    Views versus copies
    Missing values
    Handling NaNs
    nanmean(), nanvar() and nanstd()
    File I/O
    Loading from CSV files
    mean() function
    Value range
    full() and full_like() functions
    Working with Matrices
    Creating matrices
    Universal functions
    Arithmetic functions
    Modulo operation
    Fibonacci numbers
    Bitwise functions
    Comparison functions
    Fancy indexing
    at() method
    Inverting matrices
    Finding eigenvalues
    Singular value decomposition
    Pseudo inverse

    Module 4 : Special Routines

    Module 5 : Plotting with MathplotLib

    partition() function
    Complex numbers
    Array elements extraction
    Assert functions
    Almost equal arrays
    Equal arrays
    Ordering arrays
    Object comparison
    String comparison
    Floating point comparisons
    Unit tests
    Simple plots
    Plot format string
    Logarithmic plots
    Scatter plots
    Fill between
    Legend and annotations
    Threedimensional plots
    Contour Plots
  • Course Python NumPy : General

    Read general course information
  • Course Python NumPy : Reviews

  • Course Python NumPy : Certificate