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  1. sudodoki revised this gist Jul 26, 2021. 1 changed file with 4 additions and 0 deletions.
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    # Полуночный Трёп №13: Визуализация данных

    [Ссылки на прослушивание](https://anchor.fm/polunochnii-trep/episodes/--Episode-13-e1514n9)

    1. 00:00-00:50 Интро, дисклеймер и прочая.
    1. 00:50-03:53 Что изучить по теме визуализации.
    * The Visual Display of Quantitative Information, Edward Tufte ([amazon](https://www.amazon.com/Visual-Display-Quantitative-Information/dp/1930824130), и ссылка на его [новую книга](https://www.edwardtufte.com/tufte/seeing-with-fresh-eyes)).
  2. sudodoki revised this gist Jul 26, 2021. 1 changed file with 3 additions and 1 deletion.
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    * [3b1b/manim](https://github.com/3b1b/manim)
    * [Xenographics](https://xeno.graphics/)
    * Визуализация инфрастуктуры [diagrams](https://diagrams.mingrammer.com/) ([код](https://github.com/mingrammer/diagrams)), [cloudcraft](https://www.cloudcraft.co/)
    1. 1:10:18-1:12:17 Outro, и призыв присылать ужасные визуализации.
    1. 1:10:18-1:12:17 Outro, и призыв присылать ужасные визуализации.

    [Телеграм канал](https://t.me/midnight_chatter)
  3. sudodoki revised this gist Jul 26, 2021. 1 changed file with 45 additions and 45 deletions.
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    1. 00:00-00:50 Интро, дисклеймер и прочая.
    1. 00:50-03:53 Что изучить по теме визуализации.
    * The Visual Display of Quantitative Information, Edward Tufte ([amazon](https://www.amazon.com/Visual-Display-Quantitative-Information/dp/1930824130), и ссылка на его [новую книга](https://www.edwardtufte.com/tufte/seeing-with-fresh-eyes)).
    * The Grammar of Graphics, Wilkinson ([springer](https://www.springer.com/gp/book/9780387245447)). [Ggplot2](https://ggplot2.tidyverse.org/).
    * [Статья-путеводитель](https://www.researchgate.net/publication/220457627_Guidelines_for_Presenting_Quantitative_Data_in_HFES_Publications) по внятным графикам
    * Подкаст [Data Stories](https://datastori.es/)
    * The Visual Display of Quantitative Information, Edward Tufte ([amazon](https://www.amazon.com/Visual-Display-Quantitative-Information/dp/1930824130), и ссылка на его [новую книга](https://www.edwardtufte.com/tufte/seeing-with-fresh-eyes)).
    * The Grammar of Graphics, Wilkinson ([springer](https://www.springer.com/gp/book/9780387245447)). [Ggplot2](https://ggplot2.tidyverse.org/).
    * [Статья-путеводитель](https://www.researchgate.net/publication/220457627_Guidelines_for_Presenting_Quantitative_Data_in_HFES_Publications) по внятным графикам
    * Подкаст [Data Stories](https://datastori.es/)
    1. 03:53-13:31 Кейс №1: EDA, графики метрик и прочая.
    * [Квартет Энскомба](https://ru.wikipedia.org/wiki/%D0%9A%D0%B2%D0%B0%D1%80%D1%82%D0%B5%D1%82_%D0%AD%D0%BD%D1%81%D0%BA%D0%BE%D0%BC%D0%B1%D0%B0) (и [гифка](https://i2.wp.com/blog.revolutionanalytics.com/downloads/DataSaurus%20Dozen.gif?w=450) с динозавром, взятая из [блог-поста](https://blog.revolutionanalytics.com/2017/05/the-datasaurus-dozen.html)).
    * [matplotlib](https://matplotlib.org/), [визуализация созвездий](https://eleanorlutz.com/constellations-from-around-the-world) с помощью него ([код](https://github.com/eleanorlutz/western_constellations_atlas_of_space), и ее [сайт](https://eleanorlutz.com/) с другими интересными работами)
    * [seaborn](https://seaborn.pydata.org/)
    * [plotly](https://plotly.com/), [dash](https://plotly.com/dash/)
    * утилиты [CV2](https://pypi.org/project/opencv-python/) для рисования поверх картинок (матплотлиб тоже это умеет)
    * [bokeh](https://docs.bokeh.org/en/latest/index.html)
    * [Altair](https://altair-viz.github.io/) (➡️ [vega-lite](https://vega.github.io/vega-lite/) ➡️ [vega](https://vega.github.io/vega/))
    * [Квартет Энскомба](https://ru.wikipedia.org/wiki/%D0%9A%D0%B2%D0%B0%D1%80%D1%82%D0%B5%D1%82_%D0%AD%D0%BD%D1%81%D0%BA%D0%BE%D0%BC%D0%B1%D0%B0) (и [гифка](https://i2.wp.com/blog.revolutionanalytics.com/downloads/DataSaurus%20Dozen.gif?w=450) с динозавром, взятая из [блог-поста](https://blog.revolutionanalytics.com/2017/05/the-datasaurus-dozen.html)).
    * [matplotlib](https://matplotlib.org/), [визуализация созвездий](https://eleanorlutz.com/constellations-from-around-the-world) с помощью него ([код](https://github.com/eleanorlutz/western_constellations_atlas_of_space), и ее [сайт](https://eleanorlutz.com/) с другими интересными работами)
    * [seaborn](https://seaborn.pydata.org/)
    * [plotly](https://plotly.com/), [dash](https://plotly.com/dash/)
    * утилиты [CV2](https://pypi.org/project/opencv-python/) для рисования поверх картинок (матплотлиб тоже это умеет)
    * [bokeh](https://docs.bokeh.org/en/latest/index.html)
    * [Altair](https://altair-viz.github.io/) (➡️ [vega-lite](https://vega.github.io/vega-lite/) ➡️ [vega](https://vega.github.io/vega/))
    1. 13:31-25:38 Кейс №2: визуализация эмбедингов
    * [Tensorboard Projector](https://www.tensorflow.org/tensorboard/tensorboard_projector_plugin) ([standalone версия](https://github.com/tensorflow/embedding-projector-standalone)). Упоминаем [PCA](https://en.wikipedia.org/wiki/Principal_component_analysis), [UMAP](https://arxiv.org/abs/1802.03426) & [T-SNE](https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding) для сведения всего в малоразмерное пространство и дальнейшего отображения.
    * [3D Scatter Plots](https://plotly.com/python/3d-scatter-plots/) в plotly
    * [helboukkouri/embedding-visualization](https://github.com/helboukkouri/embedding-visualization) (по мотивам [anvaka/pm](https://github.com/anvaka/pm))
    * [mera-company/nlp-embeddings-visualizer](https://github.com/mera-company/nlp-embeddings-visualizer)
    * [Tensorboard Projector](https://www.tensorflow.org/tensorboard/tensorboard_projector_plugin) ([standalone версия](https://github.com/tensorflow/embedding-projector-standalone)). Упоминаем [PCA](https://en.wikipedia.org/wiki/Principal_component_analysis), [UMAP](https://arxiv.org/abs/1802.03426) & [T-SNE](https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding) для сведения всего в малоразмерное пространство и дальнейшего отображения.
    * [3D Scatter Plots](https://plotly.com/python/3d-scatter-plots/) в plotly
    * [helboukkouri/embedding-visualization](https://github.com/helboukkouri/embedding-visualization) (по мотивам [anvaka/pm](https://github.com/anvaka/pm))
    * [mera-company/nlp-embeddings-visualizer](https://github.com/mera-company/nlp-embeddings-visualizer)
    1. 25:38-28:41 Кейс №3: картинки
    * matplotlib
    * [PIL](http://www.pythonware.com/products/pil/) (💀) / [Pillow](https://pillow.readthedocs.io/en/stable/)
    * [cv2.Image](https://docs.opencv.org/master/d3/df2/tutorial_py_basic_ops.html). CV2 конечно может [больше](https://docs.opencv.org/3.4/d2/d64/tutorial_table_of_content_objdetect.html) (не забывайте про [BGR](https://learnopencv.com/why-does-opencv-use-bgr-color-format/))
    * matplotlib
    * [PIL](http://www.pythonware.com/products/pil/) (💀) / [Pillow](https://pillow.readthedocs.io/en/stable/)
    * [cv2.Image](https://docs.opencv.org/master/d3/df2/tutorial_py_basic_ops.html). CV2 конечно может [больше](https://docs.opencv.org/3.4/d2/d64/tutorial_table_of_content_objdetect.html) (не забывайте про [BGR](https://learnopencv.com/why-does-opencv-use-bgr-color-format/))
    1. 28:41-29:58 Кейс №4: визуализация аудио
    * [waveform'ы](https://en.wikipedia.org/wiki/Waveform), [спектрограммы](https://en.wikipedia.org/wiki/Spectrogram)
    * matplotlib, [pywavelet](https://pywavelets.readthedocs.io/en/latest/), [wave](https://docs.python.org/3/library/wave.html), [pyaudio](https://pypi.org/project/PyAudio/), [audiopy](https://github.com/aszkid/audiopy)
    * [waveform'ы](https://en.wikipedia.org/wiki/Waveform), [спектрограммы](https://en.wikipedia.org/wiki/Spectrogram)
    * matplotlib, [pywavelet](https://pywavelets.readthedocs.io/en/latest/), [wave](https://docs.python.org/3/library/wave.html), [pyaudio](https://pypi.org/project/PyAudio/), [audiopy](https://github.com/aszkid/audiopy)
    1. 29:58-32:10 Кейс №5: загружаем и рисуем видео
    * [ffmpeg](http://ffmpeg.org/) ([python-ffmpeg](https://github.com/kkroening/ffmpeg-python))
    * [moviepy](https://zulko.github.io/moviepy/)
    * (не говорили в выпуске, но достойно внимания) [dmlc/decord](https://github.com/dmlc/decord)
    * [ffmpeg](http://ffmpeg.org/) ([python-ffmpeg](https://github.com/kkroening/ffmpeg-python))
    * [moviepy](https://zulko.github.io/moviepy/)
    * (не говорили в выпуске, но достойно внимания) [dmlc/decord](https://github.com/dmlc/decord)
    1. 32:12-34:25 Кейс №6: рисуем графы
    * [dot](https://graphviz.org/doc/info/lang.html) (часть [graphviz](https://graphviz.org/)), [pydot](https://pypi.org/project/pydot/)
    * [networkx](https://networkx.org/)
    * [neo4j](https://neo4j.com/) имеют UI для визуализации графов
    * [dot](https://graphviz.org/doc/info/lang.html) (часть [graphviz](https://graphviz.org/)), [pydot](https://pypi.org/project/pydot/)
    * [networkx](https://networkx.org/)
    * [neo4j](https://neo4j.com/) имеют UI для визуализации графов
    1. 34:35-35:27 Кейс №7: автоматический EDA
    * [pandas-profiling](https://github.com/pandas-profiling/pandas-profiling)
    * [dataprep](https://github.com/sfu-db/dataprep)
    * и другие: [sweetviz](https://pypi.org/project/sweetviz/), [autoviz](https://github.com/AutoViML/AutoViz), [dtale](https://github.com/man-group/dtale)
    * [pandas-profiling](https://github.com/pandas-profiling/pandas-profiling)
    * [dataprep](https://github.com/sfu-db/dataprep)
    * и другие: [sweetviz](https://pypi.org/project/sweetviz/), [autoviz](https://github.com/AutoViML/AutoViz), [dtale](https://github.com/man-group/dtale)
    1. 35:27-49:25 Кейс №8: визуализируем непосредственно работу (моделей/кода etc)
    * опять же, plotly dash
    * [streamlit](https://streamlit.io/) (не забудьте [spacy-streamlit](https://spacy.io/universe/project/spacy-streamlit/) если юзаете spacy)
    * [jupyter](https://jupyter.org/) ([виджеты](https://ipywidgets.readthedocs.io/))
    * [datapane](https://datapane.com/)
    * "почти продакшен деплой": [seldon](https://www.seldon.io/), [sagemaker](https://aws.amazon.com/sagemaker/), [mlflow run](https://www.mlflow.org/docs/latest/projects.html#running-projects)
    * опять же, plotly dash
    * [streamlit](https://streamlit.io/) (не забудьте [spacy-streamlit](https://spacy.io/universe/project/spacy-streamlit/) если юзаете spacy)
    * [jupyter](https://jupyter.org/) ([виджеты](https://ipywidgets.readthedocs.io/))
    * [datapane](https://datapane.com/)
    * "почти продакшен деплой": [seldon](https://www.seldon.io/), [sagemaker](https://aws.amazon.com/sagemaker/), [mlflow run](https://www.mlflow.org/docs/latest/projects.html#running-projects)
    1. 49:25-50:49 Кейс №9: делаем репорты
    * [Tableau](https://www.tableau.com/)
    * [MS Power BI](https://powerbi.microsoft.com/en-us/)
    * [Metabase](https://metabase.com/)
    * [Tableau](https://www.tableau.com/)
    * [MS Power BI](https://powerbi.microsoft.com/en-us/)
    * [Metabase](https://metabase.com/)
    1. 50:49-52:49 Если ничего не подошло
    * [d3](https://d3js.org/) (идейный наследник [protovis](https://mbostock.github.io/protovis/) от [Mike Bostock](https://mbostock.github.io/))
    * [p5py/p5](https://github.com/p5py/p5) / [p5js](https://p5js.org/) / [processing](https://processing.org/)
    * [d3](https://d3js.org/) (идейный наследник [protovis](https://mbostock.github.io/protovis/) от [Mike Bostock](https://mbostock.github.io/))
    * [p5py/p5](https://github.com/p5py/p5) / [p5js](https://p5js.org/) / [processing](https://processing.org/)
    1. 52:49-1:10:18 Странные и интересные визуализации
    * [Лица Чернова](https://ru.wikipedia.org/wiki/%D0%9B%D0%B8%D1%86%D0%B0_%D0%A7%D0%B5%D1%80%D0%BD%D0%BE%D0%B2%D0%B0)
    * [be my eyes](https://www.bemyeyes.com/), [vOICe](https://www.seeingwithsound.com/)
    * [matplotlib + xkcd](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xkcd.html)
    * [3b1b/manim](https://github.com/3b1b/manim)
    * [Xenographics](https://xeno.graphics/)
    * Визуализация инфрастуктуры [diagrams](https://diagrams.mingrammer.com/) ([код](https://github.com/mingrammer/diagrams)), [cloudcraft](https://www.cloudcraft.co/)
    * [Лица Чернова](https://ru.wikipedia.org/wiki/%D0%9B%D0%B8%D1%86%D0%B0_%D0%A7%D0%B5%D1%80%D0%BD%D0%BE%D0%B2%D0%B0)
    * [be my eyes](https://www.bemyeyes.com/), [vOICe](https://www.seeingwithsound.com/)
    * [matplotlib + xkcd](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xkcd.html)
    * [3b1b/manim](https://github.com/3b1b/manim)
    * [Xenographics](https://xeno.graphics/)
    * Визуализация инфрастуктуры [diagrams](https://diagrams.mingrammer.com/) ([код](https://github.com/mingrammer/diagrams)), [cloudcraft](https://www.cloudcraft.co/)
    1. 1:10:18-1:12:17 Outro, и призыв присылать ужасные визуализации.
  4. sudodoki revised this gist Jul 26, 2021. 1 changed file with 45 additions and 45 deletions.
    90 changes: 45 additions & 45 deletions Episode_13_shownotes.md
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    1. 00:00-00:50 Интро, дисклеймер и прочая.
    1. 00:50-03:53 Что изучить по теме визуализации.
    * The Visual Display of Quantitative Information, Edward Tufte ([amazon](https://www.amazon.com/Visual-Display-Quantitative-Information/dp/1930824130), и ссылка на его [новую книга](https://www.edwardtufte.com/tufte/seeing-with-fresh-eyes)).
    * The Grammar of Graphics, Wilkinson ([springer](https://www.springer.com/gp/book/9780387245447)). [Ggplot2](https://ggplot2.tidyverse.org/).
    * [Статья-путеводитель](https://www.researchgate.net/publication/220457627_Guidelines_for_Presenting_Quantitative_Data_in_HFES_Publications) по внятным графикам
    * Подкаст [Data Stories](https://datastori.es/)
    * The Visual Display of Quantitative Information, Edward Tufte ([amazon](https://www.amazon.com/Visual-Display-Quantitative-Information/dp/1930824130), и ссылка на его [новую книга](https://www.edwardtufte.com/tufte/seeing-with-fresh-eyes)).
    * The Grammar of Graphics, Wilkinson ([springer](https://www.springer.com/gp/book/9780387245447)). [Ggplot2](https://ggplot2.tidyverse.org/).
    * [Статья-путеводитель](https://www.researchgate.net/publication/220457627_Guidelines_for_Presenting_Quantitative_Data_in_HFES_Publications) по внятным графикам
    * Подкаст [Data Stories](https://datastori.es/)
    1. 03:53-13:31 Кейс №1: EDA, графики метрик и прочая.
    * [Квартет Энскомба](https://ru.wikipedia.org/wiki/%D0%9A%D0%B2%D0%B0%D1%80%D1%82%D0%B5%D1%82_%D0%AD%D0%BD%D1%81%D0%BA%D0%BE%D0%BC%D0%B1%D0%B0) (и [гифка](https://i2.wp.com/blog.revolutionanalytics.com/downloads/DataSaurus%20Dozen.gif?w=450) с динозавром, взятая из [блог-поста](https://blog.revolutionanalytics.com/2017/05/the-datasaurus-dozen.html)).
    * [matplotlib](https://matplotlib.org/), [визуализация созвездий](https://eleanorlutz.com/constellations-from-around-the-world) с помощью него ([код](https://github.com/eleanorlutz/western_constellations_atlas_of_space), и ее [сайт](https://eleanorlutz.com/) с другими интересными работами)
    * [seaborn](https://seaborn.pydata.org/)
    * [plotly](https://plotly.com/), [dash](https://plotly.com/dash/)
    * утилиты [CV2](https://pypi.org/project/opencv-python/) для рисования поверх картинок (матплотлиб тоже это умеет)
    * [bokeh](https://docs.bokeh.org/en/latest/index.html)
    * [Altair](https://altair-viz.github.io/) (➡️ [vega-lite](https://vega.github.io/vega-lite/) ➡️ [vega](https://vega.github.io/vega/))
    * [Квартет Энскомба](https://ru.wikipedia.org/wiki/%D0%9A%D0%B2%D0%B0%D1%80%D1%82%D0%B5%D1%82_%D0%AD%D0%BD%D1%81%D0%BA%D0%BE%D0%BC%D0%B1%D0%B0) (и [гифка](https://i2.wp.com/blog.revolutionanalytics.com/downloads/DataSaurus%20Dozen.gif?w=450) с динозавром, взятая из [блог-поста](https://blog.revolutionanalytics.com/2017/05/the-datasaurus-dozen.html)).
    * [matplotlib](https://matplotlib.org/), [визуализация созвездий](https://eleanorlutz.com/constellations-from-around-the-world) с помощью него ([код](https://github.com/eleanorlutz/western_constellations_atlas_of_space), и ее [сайт](https://eleanorlutz.com/) с другими интересными работами)
    * [seaborn](https://seaborn.pydata.org/)
    * [plotly](https://plotly.com/), [dash](https://plotly.com/dash/)
    * утилиты [CV2](https://pypi.org/project/opencv-python/) для рисования поверх картинок (матплотлиб тоже это умеет)
    * [bokeh](https://docs.bokeh.org/en/latest/index.html)
    * [Altair](https://altair-viz.github.io/) (➡️ [vega-lite](https://vega.github.io/vega-lite/) ➡️ [vega](https://vega.github.io/vega/))
    1. 13:31-25:38 Кейс №2: визуализация эмбедингов
    * [Tensorboard Projector](https://www.tensorflow.org/tensorboard/tensorboard_projector_plugin) ([standalone версия](https://github.com/tensorflow/embedding-projector-standalone)). Упоминаем [PCA](https://en.wikipedia.org/wiki/Principal_component_analysis), [UMAP](https://arxiv.org/abs/1802.03426) & [T-SNE](https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding) для сведения всего в малоразмерное пространство и дальнейшего отображения.
    * [3D Scatter Plots](https://plotly.com/python/3d-scatter-plots/) в plotly
    * [helboukkouri/embedding-visualization](https://github.com/helboukkouri/embedding-visualization) (по мотивам [anvaka/pm](https://github.com/anvaka/pm))
    * [mera-company/nlp-embeddings-visualizer](https://github.com/mera-company/nlp-embeddings-visualizer)
    * [Tensorboard Projector](https://www.tensorflow.org/tensorboard/tensorboard_projector_plugin) ([standalone версия](https://github.com/tensorflow/embedding-projector-standalone)). Упоминаем [PCA](https://en.wikipedia.org/wiki/Principal_component_analysis), [UMAP](https://arxiv.org/abs/1802.03426) & [T-SNE](https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding) для сведения всего в малоразмерное пространство и дальнейшего отображения.
    * [3D Scatter Plots](https://plotly.com/python/3d-scatter-plots/) в plotly
    * [helboukkouri/embedding-visualization](https://github.com/helboukkouri/embedding-visualization) (по мотивам [anvaka/pm](https://github.com/anvaka/pm))
    * [mera-company/nlp-embeddings-visualizer](https://github.com/mera-company/nlp-embeddings-visualizer)
    1. 25:38-28:41 Кейс №3: картинки
    * matplotlib
    * [PIL](http://www.pythonware.com/products/pil/) (💀) / [Pillow](https://pillow.readthedocs.io/en/stable/)
    * [cv2.Image](https://docs.opencv.org/master/d3/df2/tutorial_py_basic_ops.html). CV2 конечно может [больше](https://docs.opencv.org/3.4/d2/d64/tutorial_table_of_content_objdetect.html) (не забывайте про [BGR](https://learnopencv.com/why-does-opencv-use-bgr-color-format/))
    * matplotlib
    * [PIL](http://www.pythonware.com/products/pil/) (💀) / [Pillow](https://pillow.readthedocs.io/en/stable/)
    * [cv2.Image](https://docs.opencv.org/master/d3/df2/tutorial_py_basic_ops.html). CV2 конечно может [больше](https://docs.opencv.org/3.4/d2/d64/tutorial_table_of_content_objdetect.html) (не забывайте про [BGR](https://learnopencv.com/why-does-opencv-use-bgr-color-format/))
    1. 28:41-29:58 Кейс №4: визуализация аудио
    * [waveform'ы](https://en.wikipedia.org/wiki/Waveform), [спектрограммы](https://en.wikipedia.org/wiki/Spectrogram)
    * matplotlib, [pywavelet](https://pywavelets.readthedocs.io/en/latest/), [wave](https://docs.python.org/3/library/wave.html), [pyaudio](https://pypi.org/project/PyAudio/), [audiopy](https://github.com/aszkid/audiopy)
    * [waveform'ы](https://en.wikipedia.org/wiki/Waveform), [спектрограммы](https://en.wikipedia.org/wiki/Spectrogram)
    * matplotlib, [pywavelet](https://pywavelets.readthedocs.io/en/latest/), [wave](https://docs.python.org/3/library/wave.html), [pyaudio](https://pypi.org/project/PyAudio/), [audiopy](https://github.com/aszkid/audiopy)
    1. 29:58-32:10 Кейс №5: загружаем и рисуем видео
    * [ffmpeg](http://ffmpeg.org/) ([python-ffmpeg](https://github.com/kkroening/ffmpeg-python))
    * [moviepy](https://zulko.github.io/moviepy/)
    * (не говорили в выпуске, но достойно внимания) [dmlc/decord](https://github.com/dmlc/decord)
    * [ffmpeg](http://ffmpeg.org/) ([python-ffmpeg](https://github.com/kkroening/ffmpeg-python))
    * [moviepy](https://zulko.github.io/moviepy/)
    * (не говорили в выпуске, но достойно внимания) [dmlc/decord](https://github.com/dmlc/decord)
    1. 32:12-34:25 Кейс №6: рисуем графы
    * [dot](https://graphviz.org/doc/info/lang.html) (часть [graphviz](https://graphviz.org/)), [pydot](https://pypi.org/project/pydot/)
    * [networkx](https://networkx.org/)
    * [neo4j](https://neo4j.com/) имеют UI для визуализации графов
    * [dot](https://graphviz.org/doc/info/lang.html) (часть [graphviz](https://graphviz.org/)), [pydot](https://pypi.org/project/pydot/)
    * [networkx](https://networkx.org/)
    * [neo4j](https://neo4j.com/) имеют UI для визуализации графов
    1. 34:35-35:27 Кейс №7: автоматический EDA
    * [pandas-profiling](https://github.com/pandas-profiling/pandas-profiling)
    * [dataprep](https://github.com/sfu-db/dataprep)
    * и другие: [sweetviz](https://pypi.org/project/sweetviz/), [autoviz](https://github.com/AutoViML/AutoViz), [dtale](https://github.com/man-group/dtale)
    * [pandas-profiling](https://github.com/pandas-profiling/pandas-profiling)
    * [dataprep](https://github.com/sfu-db/dataprep)
    * и другие: [sweetviz](https://pypi.org/project/sweetviz/), [autoviz](https://github.com/AutoViML/AutoViz), [dtale](https://github.com/man-group/dtale)
    1. 35:27-49:25 Кейс №8: визуализируем непосредственно работу (моделей/кода etc)
    * опять же, plotly dash
    * [streamlit](https://streamlit.io/) (не забудьте [spacy-streamlit](https://spacy.io/universe/project/spacy-streamlit/) если юзаете spacy)
    * [jupyter](https://jupyter.org/) ([виджеты](https://ipywidgets.readthedocs.io/))
    * [datapane](https://datapane.com/)
    * "почти продакшен деплой": [seldon](https://www.seldon.io/), [sagemaker](https://aws.amazon.com/sagemaker/), [mlflow run](https://www.mlflow.org/docs/latest/projects.html#running-projects)
    * опять же, plotly dash
    * [streamlit](https://streamlit.io/) (не забудьте [spacy-streamlit](https://spacy.io/universe/project/spacy-streamlit/) если юзаете spacy)
    * [jupyter](https://jupyter.org/) ([виджеты](https://ipywidgets.readthedocs.io/))
    * [datapane](https://datapane.com/)
    * "почти продакшен деплой": [seldon](https://www.seldon.io/), [sagemaker](https://aws.amazon.com/sagemaker/), [mlflow run](https://www.mlflow.org/docs/latest/projects.html#running-projects)
    1. 49:25-50:49 Кейс №9: делаем репорты
    * [Tableau](https://www.tableau.com/)
    * [MS Power BI](https://powerbi.microsoft.com/en-us/)
    * [Metabase](https://metabase.com/)
    * [Tableau](https://www.tableau.com/)
    * [MS Power BI](https://powerbi.microsoft.com/en-us/)
    * [Metabase](https://metabase.com/)
    1. 50:49-52:49 Если ничего не подошло
    * [d3](https://d3js.org/) (идейный наследник [protovis](https://mbostock.github.io/protovis/) от [Mike Bostock](https://mbostock.github.io/))
    * [p5py/p5](https://github.com/p5py/p5) / [p5js](https://p5js.org/) / [processing](https://processing.org/)
    * [d3](https://d3js.org/) (идейный наследник [protovis](https://mbostock.github.io/protovis/) от [Mike Bostock](https://mbostock.github.io/))
    * [p5py/p5](https://github.com/p5py/p5) / [p5js](https://p5js.org/) / [processing](https://processing.org/)
    1. 52:49-1:10:18 Странные и интересные визуализации
    * [Лица Чернова](https://ru.wikipedia.org/wiki/%D0%9B%D0%B8%D1%86%D0%B0_%D0%A7%D0%B5%D1%80%D0%BD%D0%BE%D0%B2%D0%B0)
    * [be my eyes](https://www.bemyeyes.com/), [vOICe](https://www.seeingwithsound.com/)
    * [matplotlib + xkcd](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xkcd.html)
    * [3b1b/manim](https://github.com/3b1b/manim)
    * [Xenographics](https://xeno.graphics/)
    * Визуализация инфрастуктуры [diagrams](https://diagrams.mingrammer.com/) ([код](https://github.com/mingrammer/diagrams)), [cloudcraft](https://www.cloudcraft.co/)
    * [Лица Чернова](https://ru.wikipedia.org/wiki/%D0%9B%D0%B8%D1%86%D0%B0_%D0%A7%D0%B5%D1%80%D0%BD%D0%BE%D0%B2%D0%B0)
    * [be my eyes](https://www.bemyeyes.com/), [vOICe](https://www.seeingwithsound.com/)
    * [matplotlib + xkcd](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xkcd.html)
    * [3b1b/manim](https://github.com/3b1b/manim)
    * [Xenographics](https://xeno.graphics/)
    * Визуализация инфрастуктуры [diagrams](https://diagrams.mingrammer.com/) ([код](https://github.com/mingrammer/diagrams)), [cloudcraft](https://www.cloudcraft.co/)
    1. 1:10:18-1:12:17 Outro, и призыв присылать ужасные визуализации.
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    1. 00:00-00:50 Интро, дисклеймер и прочая.
    1. 00:50-03:53 Что изучить по теме визуализации.
    * The Visual Display of Quantitative Information, Edward Tufte ([amazon](https://www.amazon.com/Visual-Display-Quantitative-Information/dp/1930824130), и ссылка на его [новую книга](https://www.edwardtufte.com/tufte/seeing-with-fresh-eyes)).
    * The Grammar of Graphics, Wilkinson ([springer](https://www.springer.com/gp/book/9780387245447)). [Ggplot2](https://ggplot2.tidyverse.org/).
    * [Статья-путеводитель](https://www.researchgate.net/publication/220457627_Guidelines_for_Presenting_Quantitative_Data_in_HFES_Publications) по внятным графикам
    * Подкаст [Data Stories](https://datastori.es/)
    1. 03:53-13:31 Кейс №1: EDA, графики метрик и прочая.
    * [Квартет Энскомба](https://ru.wikipedia.org/wiki/%D0%9A%D0%B2%D0%B0%D1%80%D1%82%D0%B5%D1%82_%D0%AD%D0%BD%D1%81%D0%BA%D0%BE%D0%BC%D0%B1%D0%B0) (и [гифка](https://i2.wp.com/blog.revolutionanalytics.com/downloads/DataSaurus%20Dozen.gif?w=450) с динозавром, взятая из [блог-поста](https://blog.revolutionanalytics.com/2017/05/the-datasaurus-dozen.html)).
    * [matplotlib](https://matplotlib.org/), [визуализация созвездий](https://eleanorlutz.com/constellations-from-around-the-world) с помощью него ([код](https://github.com/eleanorlutz/western_constellations_atlas_of_space), и ее [сайт](https://eleanorlutz.com/) с другими интересными работами)
    * [seaborn](https://seaborn.pydata.org/)
    * [plotly](https://plotly.com/), [dash](https://plotly.com/dash/)
    * утилиты [CV2](https://pypi.org/project/opencv-python/) для рисования поверх картинок (матплотлиб тоже это умеет)
    * [bokeh](https://docs.bokeh.org/en/latest/index.html)
    * [Altair](https://altair-viz.github.io/) (➡️ [vega-lite](https://vega.github.io/vega-lite/) ➡️ [vega](https://vega.github.io/vega/))
    1. 13:31-25:38 Кейс №2: визуализация эмбедингов
    * [Tensorboard Projector](https://www.tensorflow.org/tensorboard/tensorboard_projector_plugin) ([standalone версия](https://github.com/tensorflow/embedding-projector-standalone)). Упоминаем [PCA](https://en.wikipedia.org/wiki/Principal_component_analysis), [UMAP](https://arxiv.org/abs/1802.03426) & [T-SNE](https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding) для сведения всего в малоразмерное пространство и дальнейшего отображения.
    * [3D Scatter Plots](https://plotly.com/python/3d-scatter-plots/) в plotly
    * [helboukkouri/embedding-visualization](https://github.com/helboukkouri/embedding-visualization) (по мотивам [anvaka/pm](https://github.com/anvaka/pm))
    * [mera-company/nlp-embeddings-visualizer](https://github.com/mera-company/nlp-embeddings-visualizer)
    1. 25:38-28:41 Кейс №3: картинки
    * matplotlib
    * [PIL](http://www.pythonware.com/products/pil/) (💀) / [Pillow](https://pillow.readthedocs.io/en/stable/)
    * [cv2.Image](https://docs.opencv.org/master/d3/df2/tutorial_py_basic_ops.html). CV2 конечно может [больше](https://docs.opencv.org/3.4/d2/d64/tutorial_table_of_content_objdetect.html) (не забывайте про [BGR](https://learnopencv.com/why-does-opencv-use-bgr-color-format/))
    1. 28:41-29:58 Кейс №4: визуализация аудио
    * [waveform'ы](https://en.wikipedia.org/wiki/Waveform), [спектрограммы](https://en.wikipedia.org/wiki/Spectrogram)
    * matplotlib, [pywavelet](https://pywavelets.readthedocs.io/en/latest/), [wave](https://docs.python.org/3/library/wave.html), [pyaudio](https://pypi.org/project/PyAudio/), [audiopy](https://github.com/aszkid/audiopy)
    1. 29:58-32:10 Кейс №5: загружаем и рисуем видео
    * [ffmpeg](http://ffmpeg.org/) ([python-ffmpeg](https://github.com/kkroening/ffmpeg-python))
    * [moviepy](https://zulko.github.io/moviepy/)
    * (не говорили в выпуске, но достойно внимания) [dmlc/decord](https://github.com/dmlc/decord)
    1. 32:12-34:25 Кейс №6: рисуем графы
    * [dot](https://graphviz.org/doc/info/lang.html) (часть [graphviz](https://graphviz.org/)), [pydot](https://pypi.org/project/pydot/)
    * [networkx](https://networkx.org/)
    * [neo4j](https://neo4j.com/) имеют UI для визуализации графов
    1. 34:35-35:27 Кейс №7: автоматический EDA
    * [pandas-profiling](https://github.com/pandas-profiling/pandas-profiling)
    * [dataprep](https://github.com/sfu-db/dataprep)
    * и другие: [sweetviz](https://pypi.org/project/sweetviz/), [autoviz](https://github.com/AutoViML/AutoViz), [dtale](https://github.com/man-group/dtale)
    1. 35:27-49:25 Кейс №8: визуализируем непосредственно работу (моделей/кода etc)
    * опять же, plotly dash
    * [streamlit](https://streamlit.io/) (не забудьте [spacy-streamlit](https://spacy.io/universe/project/spacy-streamlit/) если юзаете spacy)
    * [jupyter](https://jupyter.org/) ([виджеты](https://ipywidgets.readthedocs.io/))
    * [datapane](https://datapane.com/)
    * "почти продакшен деплой": [seldon](https://www.seldon.io/), [sagemaker](https://aws.amazon.com/sagemaker/), [mlflow run](https://www.mlflow.org/docs/latest/projects.html#running-projects)
    1. 49:25-50:49 Кейс №9: делаем репорты
    * [Tableau](https://www.tableau.com/)
    * [MS Power BI](https://powerbi.microsoft.com/en-us/)
    * [Metabase](https://metabase.com/)
    1. 50:49-52:49 Если ничего не подошло
    * [d3](https://d3js.org/) (идейный наследник [protovis](https://mbostock.github.io/protovis/) от [Mike Bostock](https://mbostock.github.io/))
    * [p5py/p5](https://github.com/p5py/p5) / [p5js](https://p5js.org/) / [processing](https://processing.org/)
    1. 52:49-1:10:18 Странные и интересные визуализации
    * [Лица Чернова](https://ru.wikipedia.org/wiki/%D0%9B%D0%B8%D1%86%D0%B0_%D0%A7%D0%B5%D1%80%D0%BD%D0%BE%D0%B2%D0%B0)
    * [be my eyes](https://www.bemyeyes.com/), [vOICe](https://www.seeingwithsound.com/)
    * [matplotlib + xkcd](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xkcd.html)
    * [3b1b/manim](https://github.com/3b1b/manim)
    * [Xenographics](https://xeno.graphics/)
    * Визуализация инфрастуктуры [diagrams](https://diagrams.mingrammer.com/) ([код](https://github.com/mingrammer/diagrams)), [cloudcraft](https://www.cloudcraft.co/)
    1. 1:10:18-1:12:17 Outro, и призыв присылать ужасные визуализации.