"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data.
One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions.
The main goal of this Data Visualization with Python course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium.
- Introduction to Data Visualization
- Introduction to Matplotlib
- Basic Plotting with Matplotlib
- Dataset on Immigration to Canada
- Line Plots
- Lab: Introduction to Matplotlib and Line Plots
- Quiz: Introduction to Data Visualization Tools
- Area Plots
- Histograms
- Bar Charts
- Pie Charts
- Box Plots
- Scatter Plots
- Bubble Plots
- Lab: Basic Visualization Tools
- Lab: Specialized Visualization Tools
- Quiz: Basic Visualization Tools
- Quiz: Specialized Visualization Tools
- Waffle Charts
- Word Clouds
- Seaborn and Regression Plots
- Introduction to Folium and Map Styles
- Maps with Markers
- Choropleth Maps
- Lab: Advanced Visualization Tools
- Lab: Creating Maps and Visualizing Geospatial Data
- Quiz: Advanced Visualization Tools
- Quiz: Visualizing Geospatial Data
- Peer-review Assignment
This course is part of the 'IBM Data Science Professional Certificate'
