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.

About the Author

XFish

Fisher不钓鱼 川大21级在读 网络空间安全专业 7年前的围棋业余5段 素描彩铅水粉国画书法童子功拥有者 PG13?? Mamba4ever✊? ?Beginner Mahomes/KC Chiefs/NFL 爱好者? nparadigm申工智能yyds?️ 飞禽岛少年Lee Sedol’s fan?

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