Data, Analytics & AI Category Banner Image

Python for Data Analysis - Intermediate

  • Length 1 day
Course overview
View dates &
book now

Why study this course

Following on from the Python Beginner course, Python Intermediate will build on your foundational knowledge of Python and pandas. You will learn how to manipulate data, create custom functions, plot with Matplotlib and display visualisations.

Understanding how to use Python for Data Analysis, empowers you to be much more efficient and opens up the possibility of using a wide array of freely available tools.

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.

Nexacu powered by Lumify - master logo

Request Course Information


What you’ll learn

After completing this course, students will be able to:

  • Use the extensive data manipulation capabilities of pandas DataFrames

  • Customise the display of the output in Jupyter Notebooks

  • Use the plotting capabilities of Matplotlib to plot distributions and bar charts

  • Use the data visualisation library, Seaborn

  • Fit a basic model using scikit-learn


Python Logo

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 want to build on their foundational knowledge of Python and pandas.


Course subjects

Introduction

  • Python Intermediate

User-Defined Functions in Python

  • Function basics

  • Parameters

  • Positional vs keyword arguments

  • Defining a function

  • Indentation

  • Scope

  • *args and **kwargs

  • Unpacking operators

  • Lambda expressions

  • Conditional expressions

  • List comprehensions

Modify the DataFrame Display

  • pandas options

  • Working with pandas styles

  • Applying a style that is not dependent on values

  • Formatting values

  • String formats

  • Applying a style that is dependent on values

  • Built-in conditional formatting

Export Notebook as

  • Export to PDF or HTML

  • Create slides

Copy vs View

  • Setting with copy warning

Working with Missing Values

  • Missing values

  • inf and -inf

  • Removing missing values

  • Replacing missing values

Importing Data

  • Importing into a pandas DataFrame

Manipulating Data

  • Summarise a dataset

  • Report and display multiple summary statistics

  • Ordering data

  • Working with dates

  • Add columns with assign()

  • Working with strings

  • Reordering and dropping columns

  • Selecting rows based on values

  • Grouping and summarising data

  • Replacing values

  • Concatenate data

  • Bin continuous variables into categories

Working with Relational Data

  • Joining data from two DataFrames

Visualising Distributions

  • Visual representation of distributions with Matplotlib and Seaborn

  • Histograms

  • Boxplots

  • Bar and column charts

Multivariate Analysis

  • Scatterplot matrix

  • Bar and column charts

Basic Modelling

  • Create a linear model with scikit-learn


Prerequisites

Students should have attended the Python for Data Analysis - Beginner course or have a foundational knowledge of Python and pandas.


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.


Request Course Information

Personalise your schedule with Lumify USchedule

Interested in a course that we have not yet scheduled? Get in touch, and ask for your preferred date and time. We can work together to make it happen.