“A picture is worth a thousand words”. This course provides all familiarities 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.

Introduction to Visualization Tools

If you are an academic, it is great essential in the data visualization to show your readers more clear in your expression. That’s why I learn and post this! For long time, one may use Microsoft Excel or more professional Origin to plot the data to convey the meaning. Not enough, the data visualization with Python is introduced right now! That is a useful and powerful programming language to interact the data expression with human.

Most inspiring: top 5 map visualizations see video and top 5 physical visualizations see video

• Introduce the importance of data visualization with python
• Apply Matplotlib to create plots using Jupyter notebooks
• Read CSV files into a Pandas DataFrame
• Process and manipulate the data in the DataFrame

Basic, Specialized and Advanced Visualization Tools

After diving in, this course introduces how to make basic, specialized and advanced plots with Matplotlib library

• Area Plots, Histograms, Bar Charts
• Pie Charts, Box Plots, Scatter Plots
• Waffle Charts, Seaborn and Regression Plots

Creating Maps and Visualizing Geospatial Data

• Folium, a data visualization library in Python
• Creating maps of different regions of the world
• Creating Choropleth maps with Folium

See valid certificate