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Python for Data Analysis - Beginner

  • Length 1 day
  • Price  NZD 775 exc GST
Course overview
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Why study this course

Python is a very versatile programming language, broad in its application due to its simplicity and power. While Python can be used for everything from developing websites to programming robots, our courses focus on using Python for data analytics.

The Python Beginner course focuses on the fundamentals of working with Python for Data Analysis. We introduce Anaconda and JupyterLab and the basics of Python syntax. You will learn how to work with objects in Python, access and manipulate dataframes, how to use functions and methods and create basic visualisations.

Nexacu Public Schedule

With Lumify Group's acquisition of Nexacu, we're pleased to now offer you the largest public schedule of end user applications training in Australia and New Zealand. As we move to consolidate our end user offering with Nexacu, as an interim measure you can now access the schedule of the most closely aligned courses and book, by clicking on the link below.

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What you’ll learn

After completing this course, students will be able to:

  • Create basic markdown files

  • Create and manipulate objects

  • Use functions and methods

  • Create basic data visualisations

  • Create and manage environments in Anaconda

  • Install packages in Anaconda environments

  • Work in JupyterLab and with Jupyter Notebooks

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Python at Lumify Work

Lumify Work's Python offering has been refreshed to include courses which fully align to certifications from the Python Institute. Our courses are delivered by Python programming experts who can structure their topic flow to your goals and functions, whether it's Python for automation or for data science or for finance.

Who is the course for?

This course is intended for those who have never used Python before.

Course subjects


  • Introduction to Python

  • Introduction to Anaconda and JupyterLab

  • The Python Standard Library

Installing Python

  • Anaconda

  • JupyterLab

  • Installing additional packages

Anaconda and JupyterLab

  • Using Anaconda

  • Working with environments

  • Launching JupyterLab

  • Working in JupyterLab

  • Using Jupyter Notebooks

  • Basics of running code

  • Markdown

  • Shutting down kernels and the Jupyter Server

Using Python as a Calculator

  • Arithmetic operators

  • Relational operators

  • Logical operators

The Python Standard Library

  • Built-in functions

  • Other functions in the standard library

Working with Objects

  • Objects in Python

  • What are objects?

  • Creating variables

  • Naming rules

  • Naming conventions for variables

Data Types and Structures

  • Built-in data types

  • Built-in data structures

  • Tuples, lists, ranges and dictionaries

  • Pandas Series and DataFrames

  • Which data structure should I use?

  • Pandas DataFrame

  • Attributes

  • Methods

Pandas functions

  • Creating DataFrames

  • Importing data into a DataFrame

  • Uploading data in JupyterLab

Accessing data within DataFrames

  • Accessing specific rows

  • Accessing specific columns

  • Accessing data subsets by name or position

Manipulating DataFrames

  • Making changes in place

  • Renaming columns and rows

  • Replace a single value

  • Replace multiple values

  • Add data to a DataFrame

  • Remove rows or columns

  • Filter based on condition

  • Sort data

Working with data in DataFrames

  • Calculating summary statistics

Evaluation in Python

  • Order of operations

Evaluation with Numpy

  • Vectorised arithmetic

  • Vectorised functions

  • Broadcasting

  • Creating new columns with vectorised arithmetic and functions

Functions vs Methods

  • What is a function?

  • Syntax for using functions in Python

  • Syntax for using methods in Python

  • Parameters and arguments

  • Getting help with a function

  • Overview of help documentation

Exporting Data

  • Export data to csv file

Basic Data Visualisation

  • Matplotlib

  • Create a scatterplot

  • Create a linechart

  • Add text

  • Add a legend

  • Exporting plots

Notebook to Markdown

  • View your completed Notebook as a rendered Markdown file


  • No specific pre-requisites for the course.

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.

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