Data Visualization with Python
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Master data visualization in Python. Learn to create informative and interactive plots using libraries like Matplotlib, Seaborn, and Plotly to visualize complex datasets and present them effectively for analysis and decision-making.
At a Glance
Data visualization is the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general. It is a way to summarize your findings and display it in a form that facilitates interpretation and can help in identifying patterns or trends. In this course you will learn how to create interesting graphics and charts and customize them to make them more effective and more pleasing to your audience.
“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 data sets. 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.
- Introduction to Data Visualization
- Introduction to Matplotlib
- Basic Plotting with Matplotlib
- Dataset on Immigration to Canada
- Line Plots
- Area Plots
- Histograms
- Bar Charts
- Pie Charts
- Box Plots
- Scatter Plots
- Bubble Plots
- Waffle Charts
- Word Clouds
- Seaborn and Regression Plots
- Introduction to Folium
- Maps with Markers
- Choropleth Maps
- This course is self-paced.
- It can be taken at any time.
- It can be audited as many times as you wish.
- Python 101
- Data Analysis with Python
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