#plotly — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #plotly, aggregated by home.social.
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Анализируем MLP сообщество на Пикабу или как я спарсил 65 тысяч постов с Pikabu и построил интерактивный дашборд
Дело было вечером, делать было нечего... Я, как и многие в IT, периодически просматриваю вакансии, чтобы держать руку на пульсе рынка. И знаете, что бросается в глаза? Огромное количество позиций "Аналитик данных". Хоть это и не моя основная специализация (я больше по ML), теоретическая база у меня есть. И вот я подумал: а как бы мне сделать интересный пет-проект в этой области, чтобы и навыки прокачать, и самому не заскучать?
https://habr.com/ru/articles/968106/
#python #парсинг #data_analysis #streamlit #дэшборд #пикабу #aiohttp #визуализация_данных #петпроект #plotly
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[Перевод] Топ-6 Python-библиотек для визуализации
Команда Python for Devs подготовила перевод статьи о шести библиотеках Python для визуализации данных. Matplotlib, seaborn, Plotly, Altair, Pygal и Bokeh — у каждой свои сильные и слабые стороны: от академических статичных графиков до интерактивных дашбордов для бизнеса. Выбираем самую подходящую для различных кейсов.
https://habr.com/ru/articles/946750/
#визуализация_данных #Matplotlib #seaborn #Plotly #Altair #Pygal #Bokeh #интерактивные_графики
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Enteric Fermentation in 2022
Livestock digestion emits too much methane:
* Too many bovines in India, Pakistan, Brazil, United States, China;
* Too many sheep and pigs in China.(The bubble sizes depend on the amount of methane sent in 2022.)
#GreenhouseForcing #methane #emissions #climateChange #climateBreakdown #climateCollapse #dataViz #bubbleChart #dataMining #plotly #featureEngineering #featureSelection #dataDon
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Enteric Fermentation in 2022
Livestock digestion emits too much methane:
* Too many bovines in India, Pakistan, Brazil, United States, China;
* Too many sheep and pigs in China.(The bubble sizes depend on the amount of methane sent in 2022.)
#GreenhouseForcing #methane #emissions #climateChange #climateBreakdown #climateCollapse #dataViz #bubbleChart #dataMining #plotly #featureEngineering #featureSelection #dataDon
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Enteric Fermentation in 2022
Livestock digestion emits too much methane:
* Too many bovines in India, Pakistan, Brazil, United States, China;
* Too many sheep and pigs in China.(The bubble sizes depend on the amount of methane sent in 2022.)
#GreenhouseForcing #methane #emissions #climateChange #climateBreakdown #climateCollapse #dataViz #bubbleChart #dataMining #plotly #featureEngineering #featureSelection #dataDon
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Enteric Fermentation in 2022
Livestock digestion emits too much methane:
* Too many bovines in India, Pakistan, Brazil, United States, China;
* Too many sheep and pigs in China.(The bubble sizes depend on the amount of methane sent in 2022.)
#GreenhouseForcing #methane #emissions #climateChange #climateBreakdown #climateCollapse #dataViz #bubbleChart #dataMining #plotly #featureEngineering #featureSelection #dataDon
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Enteric Fermentation in 2022
Livestock digestion emits too much methane:
* Too many bovines in India, Pakistan, Brazil, United States, China;
* Too many sheep and pigs in China.(The bubble sizes depend on the amount of methane sent in 2022.)
#GreenhouseForcing #methane #emissions #climateChange #climateBreakdown #climateCollapse #dataViz #bubbleChart #dataMining #plotly #featureEngineering #featureSelection #dataDon
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#DataViz on two requirements:
* zooming, panning and rescaling
* shareable dashboards"Plotly vs. Bokeh: Interactive Python Visualisation Pros and Cons", by Dr Paul Iacomi: https://pauliacomi.com/2020/06/07/plotly-v-bokeh.html
#dataDev #retrieval #dataMining #plotly #Dash #Bokeh #python #dataInteraction #data #dataDon #widgets #ipython #jupyter #dashboards #businessIntelligence
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Looking at it first time today. (svg so responds to [ Ctrl + '+' ] didnt think to zoom it before)
Wow! percentages on everything.
I'm amazed! Astounded truly. 140 lines to achieve all of that? And I'm sure I'm doing it all sorts of wrong. But that's a genuine task solved w/ Python in basically a day, but i've been tweeking around w/ the filesystem stuff.
On the data-science bandwagon of course.
Thought I'd re-do my ⇨ *OLD* ⇦ php static cms (did i meantion it's old?) as a python app to learn from that perspective.
see:
https://statecollegeguitarlessons.com/adbI dunno why i want to start by learning how to mess with the filesystem. probably some kind of psychosis. someone has a name for that.
traverse the dirs w/ tuple os.walk i think at that time, abandoned for pathlib - thought, okay: this is pretty easy w/ python! let's try counting file-types, etc. clearly abandoning the cms idea by that time. Also, i see Jupyter Notebook is basically already the thing. so. ha!
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Looking at it first time today. (svg so responds to [ Ctrl + '+' ] didnt think to zoom it before)
Wow! percentages on everything.
I'm amazed! Astounded truly. 140 lines to achieve all of that? And I'm sure I'm doing it all sorts of wrong. But that's a genuine task solved w/ Python in basically a day, but i've been tweeking around w/ the filesystem stuff.
On the data-science bandwagon of course.
Thought I'd re-do my ⇨ *OLD* ⇦ php static cms (did i meantion it's old?) as a python app to learn from that perspective.
see:
https://statecollegeguitarlessons.com/adbI dunno why i want to start by learning how to mess with the filesystem. probably some kind of psychosis. someone has a name for that.
traverse the dirs w/ tuple os.walk i think at that time, abandoned for pathlib - thought, okay: this is pretty easy w/ python! let's try counting file-types, etc. clearly abandoning the cms idea by that time. Also, i see Jupyter Notebook is basically already the thing. so. ha!
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Looking at it first time today. (svg so responds to [ Ctrl + '+' ] didnt think to zoom it before)
Wow! percentages on everything.
I'm amazed! Astounded truly. 140 lines to achieve all of that? And I'm sure I'm doing it all sorts of wrong. But that's a genuine task solved w/ Python in basically a day, but i've been tweeking around w/ the filesystem stuff.
On the data-science bandwagon of course.
Thought I'd re-do my ⇨ *OLD* ⇦ php static cms (did i meantion it's old?) as a python app to learn from that perspective.
see:
https://statecollegeguitarlessons.com/adbI dunno why i want to start by learning how to mess with the filesystem. probably some kind of psychosis. someone has a name for that.
traverse the dirs w/ tuple os.walk i think at that time, abandoned for pathlib - thought, okay: this is pretty easy w/ python! let's try counting file-types, etc. clearly abandoning the cms idea by that time. Also, i see Jupyter Notebook is basically already the thing. so. ha!
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Looking at it first time today. (svg so responds to [ Ctrl + '+' ] didnt think to zoom it before)
Wow! percentages on everything.
I'm amazed! Astounded truly. 140 lines to achieve all of that? And I'm sure I'm doing it all sorts of wrong. But that's a genuine task solved w/ Python in basically a day, but i've been tweeking around w/ the filesystem stuff.
On the data-science bandwagon of course.
Thought I'd re-do my ⇨ *OLD* ⇦ php static cms (did i meantion it's old?) as a python app to learn from that perspective.
see:
https://statecollegeguitarlessons.com/adbI dunno why i want to start by learning how to mess with the filesystem. probably some kind of psychosis. someone has a name for that.
traverse the dirs w/ tuple os.walk i think at that time, abandoned for pathlib - thought, okay: this is pretty easy w/ python! let's try counting file-types, etc. clearly abandoning the cms idea by that time. Also, i see Jupyter Notebook is basically already the thing. so. ha!
-
Looking at it first time today. (svg so responds to [ Ctrl + '+' ] didnt think to zoom it before)
Wow! percentages on everything.
I'm amazed! Astounded truly. 140 lines to achieve all of that? And I'm sure I'm doing it all sorts of wrong. But that's a genuine task solved w/ Python in basically a day, but i've been tweeking around w/ the filesystem stuff.
On the data-science bandwagon of course.
Thought I'd re-do my ⇨ *OLD* ⇦ php static cms (did i meantion it's old?) as a python app to learn from that perspective.
see:
https://statecollegeguitarlessons.com/adbI dunno why i want to start by learning how to mess with the filesystem. probably some kind of psychosis. someone has a name for that.
traverse the dirs w/ tuple os.walk i think at that time, abandoned for pathlib - thought, okay: this is pretty easy w/ python! let's try counting file-types, etc. clearly abandoning the cms idea by that time. Also, i see Jupyter Notebook is basically already the thing. so. ha!
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Did you miss the #PyData #Pittsburgh event about building a modern #data analysis and #visualization pipeline for the @codeandsupply Compensation Survey Report with #Polars, #Jupyter, #papermill, #Plotly, and more? Now you can catch a recording of the presentation here!
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Join us *tonight* for a talk from @colindean about how @codeandsupply used #Polars, #Jupyter, #papermill, #Plotly, and other open source tools to generate the C&S Compensation Survey Report, a 100+ page research paper chock full of data analysis and visualization.
See you there!
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Want to learn about how to use #Polars, #Jupyter, #papermill, #Plotly, and other open source tools to create a modern, reproducible data analysis and visualization pipeline?
Join #PyData #Pittsburgh on Wednesday, January 17 for the talk "Data Engineering: The Code & Supply Compensation Survey Report" from @colindean, managing director at @codeandsupply!
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How To Create A Simple GIS Map With Plotly And Streamlit [overview and tutorial]
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https://towardsdatascience.com/how-to-create-a-simple-gis-map-with-plotly-and-streamlit-7732d67b84e2 <-- shared tutorial
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#GIS #spatial #mapping #Plotly #streamlit #overview #tutorial #mapfunctions #dashboards #graphs #datapresentation #datasummary #spatialdata #alldataisspatial #geography -
How To Create A Simple GIS Map With Plotly And Streamlit [overview and tutorial]
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https://towardsdatascience.com/how-to-create-a-simple-gis-map-with-plotly-and-streamlit-7732d67b84e2 <-- shared tutorial
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#GIS #spatial #mapping #Plotly #streamlit #overview #tutorial #mapfunctions #dashboards #graphs #datapresentation #datasummary #spatialdata #alldataisspatial #geography -
How To Create A Simple GIS Map With Plotly And Streamlit [overview and tutorial]
--
https://towardsdatascience.com/how-to-create-a-simple-gis-map-with-plotly-and-streamlit-7732d67b84e2 <-- shared tutorial
--
#GIS #spatial #mapping #Plotly #streamlit #overview #tutorial #mapfunctions #dashboards #graphs #datapresentation #datasummary #spatialdata #alldataisspatial #geography -
How To Create A Simple GIS Map With Plotly And Streamlit [overview and tutorial]
--
https://towardsdatascience.com/how-to-create-a-simple-gis-map-with-plotly-and-streamlit-7732d67b84e2 <-- shared tutorial
--
#GIS #spatial #mapping #Plotly #streamlit #overview #tutorial #mapfunctions #dashboards #graphs #datapresentation #datasummary #spatialdata #alldataisspatial #geography -
How To Create A Simple GIS Map With Plotly And Streamlit [overview and tutorial]
--
https://towardsdatascience.com/how-to-create-a-simple-gis-map-with-plotly-and-streamlit-7732d67b84e2 <-- shared tutorial
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#GIS #spatial #mapping #Plotly #streamlit #overview #tutorial #mapfunctions #dashboards #graphs #datapresentation #datasummary #spatialdata #alldataisspatial #geography -
Today I learned how to create an interactive HTML report for gene-set enrichment analysis in R. It allows readers to examine set-level results & drill down into the underlying gene-level statistics interactively.
https://tomsing1.github.io/blog/posts/interactive-gene-set-results/
It's a static HTML page, e.g. no server (#shiny, #dash, etc) needed. Thanks a lot to the authors of the #plotly #reactable #crosstalk and #htmlwidget tools for making this so easy #til #rstats #bioconductor #gsea #compbio #visualization @lianos -
#TidyTuesday US Monthly retail sales was extra fun to analyze with #Plotly in #rstats #QuartoPub #Quarto
Detailed article on #datacleaning #plotting and using #crosstalk to add interactivity in visualization is here: https://medium.com/@menghani.deepsha/tidytuesday-retail-sales-data-analysis-with-plotly-in-r-c8ca605d4d0