Plotly

My personal note on Kaggle:

Plotly Note and Samples

Processing

• df.sort_values(by=' ')
• px.data.gapminder().query
• .query
• fig = go.Figure()
• fig.update_traces
• fig.update_layout
• fig.add_trace
• fig.show()

Types

• Line Plots
• Bar Charts
• Scatter Plots
  scattergl
• Pie Charts
• Histograms
• Box Plots
• Violin Plot
• Density Heatmap
• 3D Scatter Plots
• 3D Line Plots
• Scatter Matrix
• Map Scatter Plots
• Choropleth Maps
• Polar Chart
• Ternary Plot
• Facets
  subplots
• Animated Plots
  add parameter “animation_frame”, “animation_group”

Conclusion

I personally think that plotly got the most beautiful series of charts among all of those python data visualiazation package. Actually, the reason why I get to learn these stuff because of the urgent need in NFL Big Data Bowl. But undoubtfully, it will be a useful tool for me in the future, and I really hoping to have a good grasp on this field.

This is just a simple list of plotly’s tools, which is taken down in my process of get familar with all of these usage. Master comes from practice.

Later, after finishing the competition in 2 months, I will be making a summary about how to use plotly in data visualization of American football, and probably also contains other sports.