Data Visualisation with Python
Data Visualisation with Python course teaches you how to communicate data insights effectively through compelling visualizations with this Data Visualisation course. You will create various charts and graphs, interactive dashboards, and complete hands-on labs. The course covers tools and techniques, including Matplotlib, Seaborn, Folium, Plotly & Dash. Become proficient in data visualization using Python and its libraries and turn data into insightful stories.
per person
Level
Duration
Training Delivery Format
Face-to-face / Virtual Class
per person
Level
Duration
Training Delivery Format
Face-to-face (F2F) / Virtual Class
Class types
Public Class
Private Class
In-House Training
Bespoke
About this course
One of the most important skills of successful data scientists and data analysts is the ability to tell a compelling story by visualising data and findings in an approachable and stimulating way. In this course you will learn many ways to effectively visualise both small and large-scale data. You will be able to take data that at first glance has little meaning and present that data in a form that conveys insights.
This course will teach you to work with many Data Visualisation tools and techniques. You will learn to create various types of basic and advanced graphs and charts like: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps, and many more!
Who should attend?
The Data Visualisation with Python course is for:
- Data scientists
- Data analysts
Learning Outcome
By ends of this course,
- You will also create interactive dashboards that allow even those without any Data Science experience to better understand data,and make more effective and informed decisions.
- You will learn hands-on by completing numerous labs and a final project to practice and apply the many aspects and techniques of Data Visualization using Jupyter Notebooks and a Cloud-based IDE.
- You will use several data visualization libraries in Python, including Matplotlib, Seaborn, Folium, Plotly & Dash.
Prerequisites
This course requires a working knowledge of the Python programming language and using Jupyter Notebooks.
Course Content
Module 1: Introduction to Data Visualisation Tools
You will learn about data visualisation and some of the best practices to keep in mind when creating plots and visuals. You will also learn about the history and the architecture of Matplotlib and learn about basic plotting with Matplotlib.
You will briefly learn how to read csv files into a pandas dataframe and process and manipulate the data in the dataframe, and how to generate line plots using Matplotlib.
- Introduction to Data Visualization
- Introduction to Matplotlib
- Basic Plotting with Matplotlib
- Dataset on Immigration to Canada
- Line Plots
Module 2: Basic and Specialised Visualisation Tools
In this module, you learn about area plots and how to create them with Matplotlib, histograms and how to create them with Matplotlib, bar charts, and how to create them with Matplotlib, pie charts, and how to create them with Matplotlib, box plots and how to create them with Matplotlib, and scatter plots and bubble plots and how to create them with Matplotlib.
- Area Plots
- Histograms
- Bar Charts
- Pie Charts
- Box Plots
- Scatter Plots
- Basic Visualization Tools
- Specialized Visualization Tools
Module 3: Advanced Visualisations and Geospatial Data
In this module, you will learn about advanced visualization tools such as waffle charts and word clouds and how to create them. You will also learn about seaborn, which is another visualization library, and how to use it to generate attractive regression plots. In addition, you will learn about Folium, which is another visualization library, designed especially for visualizing geospatial data. Finally, you will learn how to use Folium to create maps of different regions of the world and how to superimpose markers on top of a map, and how to create choropleth maps.
- Waffle Charts
- Word Clouds
- Seaborn and Regression Plots
- Introduction to Folium
- Maps with Markers
- Choropleth Maps
- Advanced Visualization Tools
- Visualizing Geospatial Data
Module 4: Sequence Mutation and Accumulation Patterns
We will present deeper knowledge on using lists, strings, and python objects in general. We will also cover how to use the accumulation pattern with lists and with strings. The final assignment will test your knowledge and skills through application, much like previous assessments and assignments did, though with a more difficult set of tasks now that you have learned the basics.
- Introduction: Transforming Sequences
- Mutability
- List Element Deletion
- Objects and References
- Aliasing10m
- Cloning
- Methods on Lists
- Append vs. Concatenate
- Non-Mutating Methods on Strings
- String Format Method
- The Accumulator Pattern with Lists
- The Accumulator Pattern with Strings
- Accumulator Pattern Strategies
- Don’t Mutate A List That You Are Iterating Through
- Course Feedback
Certification
This is a non-certification course.
If you are looking for a certification, Pyhton Institute offers the best options for you to choose from.
You can start with PCEP, Certified Entry Level Python Programmer.
Then you can pursue PCAP, Certified Associate in Python Programming, and then PCPP, Certified Professional in Python Programming 1.
FAQs
Q: What is the main focus of the course “Data Visualisation with Python”?
A: The main focus of the course is to teach data visualization techniques using various tools and libraries in Python.
Q: Name three data visualisation tools covered in this course and briefly describe their significance.
A: Three data visualisation tools covered in the course are Matplotlib, Seaborn, and Folium. Matplotlib serves as the foundation for creating different types of plots, Seaborn is used for generating attractive regression plots, and Folium is designed specifically for geospatial data visualization.
Q: What are some of the advanced data visualisation techniques covered in the course?
A: Advanced data visualisation techniques covered in the course include creating waffle charts, word clouds, and choropleth maps. These techniques allow students to present data in visually compelling and informative ways.
Q: In the “Sequence Mutation and Accumulation Patterns” module, what are the key concepts covered regarding lists and strings?
A: In the “Sequence Mutation and Accumulation Patterns” module, key concepts covered include mutability, list element deletion, cloning, and the accumulator pattern with lists and strings. Students will learn how to manipulate and work with lists and strings effectively.
At this time, this course is available for private class and in-house training only. Please contact us for any inquiries.