Data Viz with Python: How to Create Valuable Visual Representation

Sometimes we make an ineffective or excessive, or even wrong choice to present our data to the audience. We can make positive impacts not only on our business but also on our communities, if we draw and use graphs and charts successfully. Why not learn new skill and do good for our communities?

Power of data visualisation is used for social good as well as decision making. Python has many libraries for those missions and there are many types of graphs and charts to choose. To data visualisation beginners, I will explain basic concepts of data visualisation, introduce frequently used graphs such as scatter plot, bar chart, heat map and some of Python libraries such as pandas, matplotlib, bokeh, show how we can work on open data viz projects.

1. What is Data Visualisation?
   • Brief History
   • Business and social impacts
2. Frequently Used Graphs
   • Scatter plot, box plot
   • Bar chart, histgram, line chart
   • Heat map
   • Word cloud
3. Python Libraries
   • pandas functions
   • matplotlib, bokeh, plotly, seaborn
   • WordCloud

4. Examples (to be shown and provided as Jupiter notebooks)

5. Open Projects
   • Viz for Social Good
   • Makeover Monday

Language: English or Japanese