- Data Analysis
- Box Plots
- Scatter Plots
- Plotly
- Heat Maps
- Histogram
- Data Presentation
- Seaborn
- Pandas (Python Package)
- Matplotlib
- Geospatial Information and Technology
- Interactive Data Visualization
Data Visualization with Python
Completed by Márton Tamás Molnár
September 12, 2020
20 hours (approximately)
Márton Tamás Molnár's account is verified. Coursera certifies their successful completion of Data Visualization with Python
What you will learn
Implement data visualization techniques and plots using Python libraries, such as Matplotlib, Seaborn, and Folium to tell a stimulating story
Create different types of charts and plots such as line, area, histograms, bar, pie, box, scatter, and bubble
Create advanced visualizations such as waffle charts, word clouds, regression plots, maps with markers, & choropleth maps
Generate interactive dashboards containing scatter, line, bar, bubble, pie, and sunburst charts using the Dash framework and Plotly library
Skills you will gain
