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Plotly dash and data visualisation in Python
The document discusses various data visualization libraries in Python, including Plotly and Bokeh, highlighting their features and use cases. It compares different options for building interactive dashboards, such as Tableau, R-Shiny, and Python-based solutions, emphasizing the complexity and suitability for non-coders. Additionally, it offers tips for developing data-driven applications and outlines roles and tools in the data analytics landscape at Wooga.
Plotly dash and data visualisation in Python
- 1. Volodymyrk 1 Berlin, 16th July,2017 And Data Visualisation in Python
- 2. Volodymyrk Volodymyr ( Vlad) Kazantsev Head of Data Science @ Wooga Head of Data @ Product Madness Product Manager MBA @LBS Graphics programming Writes code for money since 2002 Math degree 2
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- 5. Volodymyrk Plotly dash ..2 minute version - Build interactive data visualisations for the Web - In Pure Python - no HTML/JavaScipt required 5
- 6. Volodymyrk What is Plotly(visualisation library)? 6 + + API bindings: - Core is 100% Open Source - Has enterprise plans (and premium plugins) - 50%+ of all devs are working on Open Source code
- 7. Volodymyrk Data Visualisation Librariesin Python 1986 - GNU Plot 2003 - Matplotlib (14 years ago!) 2012 - Bokeh 2012 - Seaborn 2014 - Plotly.py June 2017 - Dash 7
- 8. Volodymyrk What are wetrying to solve? Master Dashboard - External or internal clients - Lot’s of interactivity - Complex Layout 8 Analytics Portal - Lots of Dashboards - Many are similar - Interactive filters/selectors Report Generator - Produces HTML report - Based on inputs Interactivity/ Exploration Pre-made choices
- 9. Volodymyrk Option-1: Tableau ● AlsoLooker, Periscope, Superset, Qlick, Mode, Redash.. ● If existing functionality is enough ● If you don’t need to automate the creation ● If “creator and owner” of those dashboards is a Business Data Analyst (e.g. not code-savvy data scientist) 9
- 10. Volodymyrk Option-2: R-Shiny + Mature +Backed by RStudio (commercial company) + Looks good - R 10
- 11. Volodymyrk Option-3: Python back-end,JavaScript front-end + No middleman between browser code and you + Mature ecosystem - Too complex for a regular Data Scientist 11 Web Framework: Flask, Django, Tornado, etc. Data Layer: Numpy, Pandas, Scipy, etc HTML+JS: D3.js, NVD3, HighCharts, Plotly etc.
- 12. Volodymyrk Option-4: Bokeh Server ●Best-kept secret in Python Data Ecosystem ● Custom JavaScript library (Bokeh.js) ● Uses HTML Canvas (or WebGL) ● Historically used CoffeeScript 12
- 13. Volodymyrk Bokeh Server Bokeh.js: - HtmlCanvas, lots of custom JS code Bokeh Widgets: - Lots of custom code - Hard to style Bokeh Server: - Based on Tornado - Stateful 13 Plotly Dashvs. Plotly.js - Based on D3.js Dash Components: - All normal HTML components in Dash - Build on top of React! Plotly Server: - Just Flask - Stateless
- 14. Volodymyrk Bokeh Server Bokeh.js: - HtmlCanvas, lots of custom JS code Bokeh Widgets: - Lots of custom code - Hard to style Bokeh Server: - Based on Tornado - Stateful 14 Plotly Dashvs. Plotly.js - Based on D3.js Dash Components: - All normal HTML components in Dash - Build on top of React! Plotly Server: - Just Flask - Stateless
- 15. Volodymyrk Option-6: Jupyter Dashboards +Easy to build - Layouts/callbacks/interactivity is limited - Not suitable for building “client-facing” apps 15
- 16. Volodymyrk FrontEnd: D3, Plotly.js Highchart BackEnd: Python, Java In summary 16 ExplorationProduct For SalePrototype/Quick App Jupyter Notebook (Local) Tableau Excel Jupyter Dashboard Internal Data Product Tableau Server RShiny Bokeh Server Plotly Dash
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- 18. Volodymyrk Case Study You justget the best job in the galaxy
- 19. Volodymyrk 19 Your new BossBusiness domain Business case I love synthetic data
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- 21. Volodymyrk Jabba’s Used Droidbusiness 21 Multi Dimensional Event-level Time Series
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- 24. Volodymyrk Tip-1: truly data-drivenapps - Dynamic, data-driven, layout Def build_layout(..): app.layout = build_layout 24 - Need to pre-define all callbacks app.config.supress_callback_exceptions = True
- 25. Volodymyrk Tip-2: Caching - Appis Stateless! 25
- 26. Volodymyrk Tip-3: Production Deployment dash-project/ app1/ app.py datamodel.py app2/ app.py datamodel.py mycomponents/ ... server.py Run.py uwsgi.. --wsgi-file run.py https://community.plot.ly/t/multiple-dashboards/4656 26 Monolithic App UWSGI Emperor Mode Similar structure, but we are not there yet..
- 27. Volodymyrk Tip 4: Whereto get help? Don’t use StackOverflow yet.. however there is a #plotly-dash tag already Official forum: https://community.plot.ly/c/dash 27
- 28. ● Data Scientist ●Senior Data Scientist ● Data Engineer ● Data Engineer (intern/student) ● Game Design, Art, UX ● Product Marketer ● Game devs (Unity and iOS) ● Product Manager, Live Operations ● Senior Product Manager (x3) ● And many more! . . . check out jobs.wooga.com is HIRING! jobs.wooga.com
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- 30. Product Analytics DataScience Data Engineering Analytics is not a team, but describes the way Wooga approaches decisions Dashboards AB Tests Game Balancing Ad-hoc Insights Business reviews Deep-dive Analysis Machine Learning Data Processing: Airflow Data Pipeline: Kafka, Exasol Data Access: Periscope, Jupyter In-house Tools Infrastructure: kubernetes Stats ModellingBusiness modelling
- 31. Our Tech Stack Airflow Magic8 Ball Predictive Analytics Research Dashboards & Data Viz.