Jake VanderPlas The Python Visualization Landscape PyCon 2017

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  • Опубликовано: 9 сен 2024
  • "Speaker: Jake VanderPlas
    So you want to visualize some data in Python: which library do you choose? From Matplotlib to Seaborn to Bokeh to Plotly, Python has a range of mature tools to create beautiful visualizations, each with their own strengths and weaknesses. In this talk I’ll give an overview of the landscape of dataviz tools in Python, as well as some deeper dives into a few, so that you can intelligently choose which library to turn to for any given visualization task.
    Slides can be found at: speakerdeck.co... and github.com/PyC..."

Комментарии • 22

  • @youknowmyname12345
    @youknowmyname12345 Год назад +1

    Jake’s PyCon talks are the best primers to any Python topic. He’s a great teacher!

  • @MarkusEicher70
    @MarkusEicher70 13 дней назад

    Thanks for this overview of the Python visualization tool landscape. Has a few years but is still a good overview. Love the way you perform on the stage. Very professional but still enjoyable. A speaker who knows the field he is talking about. Was a pleasure to follow this. Doing my DYOR what has changed in the meantime.

  • @Actanonverba01
    @Actanonverba01 6 лет назад +5

    Interesting idea:
    -Andrew Curves @ 8:35
    -Seaborn @ 9:18
    -Bokeh @ 11:06
    -DataShader @ 15:43
    -Holoviews @ 17:50
    -Altair @ 19:43

  • @SHONNER
    @SHONNER 7 лет назад +4

    25:47 Genius. So glad things have come to this. So math-array-oriented before. More JSON-oriented now. And still done using a simple Python format.

  • @cosmicallyderived
    @cosmicallyderived 7 лет назад +3

    20:49 submitting data and rendering specifications for generating interactive plots, I like that notion of declarative visualization. Keep up those efforts, I'd love things to get to that dimension.

  • @ramav87
    @ramav87 7 лет назад +1

    Thanks. It's nice to have an overview like this!

  • @MrCirorockert
    @MrCirorockert 6 лет назад +2

    Great presentation and organization of the (vast) field of Data Visualization.

  • @bluelight9421
    @bluelight9421 7 лет назад +3

    Nice presentation

  • @JonathanObise
    @JonathanObise 4 года назад

    Beautiful

  • @gappyp3851
    @gappyp3851 6 лет назад

    great overview.

  • @dormannd2861
    @dormannd2861 4 года назад

    Thank you! Sir

  • @waats
    @waats 7 лет назад +4

    My two favorite plotting lib are missing in this talk which goes in the declarative type
    I'll put a link there just in case :
    plotnine.readthedocs.io/en/stable/
    yhat.github.io/ggpy/

    • @jakevanderplas2418
      @jakevanderplas2418 7 лет назад +2

      Thanks - I hadn't seen plotnine... but I did mention ggpy in the talk.

  • @9assahrasoum3asahboou87
    @9assahrasoum3asahboou87 2 года назад

    fathi medos fez said thank you so much

  • @cosmicallyderived
    @cosmicallyderived 7 лет назад +2

    We've been heavily porting to Bokeh at work, especially an embedded bokeh server to serve up cool dashboard navigational stuff in Flask. Does plotly have anything comparable to bokeh server?

  • @antoni2nguyen
    @antoni2nguyen 7 лет назад

    Thank you sir!

  • @GUAGUAGE
    @GUAGUAGE 7 лет назад

    Thank you Sir.

  • @Rene-tu3fc
    @Rene-tu3fc 7 лет назад

    So what do you recommend to someone new to plotting in python trying to focus on engineering?