#Plotly
#Python #AI #GIS #risk #climatechange #energy #safety #sustainability #datascience
We explore real-time weather data for #rainfall #forecasting and #flood de-risking using Python.
Methods: Machine Learning, Markov Chain & Geospatial #Plotly Mapping.
Day 9 of the #30DayMapChallenge was hexagons.
After an honestly pretty tiring day I opted to save some energy by recycling my day four data and plotting a hexbin map showing the worst affected areas for mass shootings in the US between January 1st and November 7th 2023. The worst area was the slot containing Chicago, with 42 incidents.
#python
#technology #investment
#trading #algorithm #fintech #finance #financial #money #business
#NVDA Live Share #Price
with moving averages
Volume, MACD, and Stochastic Oscillator
#explore
#Plotly #Dash TA #Stock #Market #App
https://wp.me/pdMwZd-7A3
Day 6 of the #30DayMapChallenge ended up taking me a couple of days due to a lot of bugs, and producing a code file too big to be committed to GitHub without being zipped first...
The theme for day 6 was #Asia, and I decided to plot the provinces of Thailand according to how much tourist revenue they pull in.
As usual you can find all my code, data and the interactive version of the map on my challenge website at the link below.
https://vikkiwalls.github.io/30-Day-Map-Challenge-2023-Live/Day%206.html
(please note - this is quite a heavy duty map, so it will probably need a few seconds for the page to load)
#Python #Pandas #Plotly #Matplotlib #Geopandas #SQL #DataScience #DataVisualisation #GIS
Running a little bit late to the party this year as I've been juggling some tough personal circumstances and a busy workload however I've decided to take part in the #30DayMapChallenge again this year, and this year I'll be sharing my maps both through Github and through a little website I built specifically for the project: https://vikkiwalls.github.io/30-Day-Map-Challenge-2023-Live/
Day 1 had the theme of points, so having felt inspired by all the travel videos I've seen on Instagram lately, I thought I'd plot the highest peaks in the Rocky Mountains.
Feels like a long week playing with #Plotly and failing - hate to give up on it, though I seem to have a talent for making things that don't quite work
Switched back to #ggplot and the Plotly wrapper with a couple of filters from crosstalk package
My brain hurts, but it's so addictive
At some point I'll invest more effort into learning #Javascript
After several days of map-making with #Plotly in #RStats, I managed to get different traces for the fill values, and a dropdown menu for each of the trace options...
But the values don't update correctly for each category selected. It seems to be a common problem.
Might have to resort to crosstalk and #ggplotly to do what I want.
#Python Friday #198: Multi-Component Dashboards with #Dash & #Plotly
https://improveandrepeat.com/2023/10/python-friday-198-multi-component-dashboards-with-dash/
Had an amazingly productive day discovering all the things I don't know about building interactive choropleth #maps with crosstalk in #RStats
Finally got something to work with #plotly but it wouldn't knit into an HTML file for pandoc reasons
There is a considerable absence of tutorials on this topic; if I figure it out I'll write my own
3/3
sources for many projects, and the amount of data (and sources) is only going to increase. Sign up here if you’re interested, and get full details, or DM me for any questions you may have:
#DataScience #Python #SEO #DigitalMarketing #advertools #pandas #plotly
Announcing a new cohort for my course:
Data Science with Python for SEO 🎉 🎉 🎉
🔵 Absolute beginners
🔵 Cohort starts October 30th
🔵 Make a leap in your data skills
🔵 Run, automate, and scale many SEO tasks with Python like crawling, analyzing XML sitemaps, text/keyword analysis
🔵 In depth intro to data manipulation and visualization skills
🔵 Get started with #advertools #pandas and #plotly
🔵 Make the transition from Excel to Python
#Python Friday #195: Customise Your #Plots in #Plotly
https://improveandrepeat.com/2023/10/python-friday-195-customise-your-plots-in-plotly/
t-SNE of #embeddings of about 15k poems scraped from poetry foundation #DataViz #InfoViz with #Plotly
#Python Friday #194: Templates for #Plotly
https://improveandrepeat.com/2023/09/python-friday-194-templates-for-plotly/
#Plotly works as expected in #SharePoint... Nice!
#Python Friday #193: Choosing Colours for #Plotly
https://improveandrepeat.com/2023/09/python-friday-193-choosing-colours-for-plotly/
Sharing the first version of an SEO audit and analysis template in #Python, #advertools, #pandas, #networkx, & #plotly
🔵 Notebook meant to be a starting point
🔵 Low code, highly customizable
🔵 Can be converted to an HTML file shareable, emailable
🔵 Interactively explore the elements you want
🔵 Expecting, hoping for suggestions, improvement (code and non-code)
Full video/explanation here (with link to the code and data):
What's the minimum number of clicks needed to go from page A to page B?
Shortest Path Length
What pages B and C, D and F, ... ?
What about all pairs of pages in the whole site?
I'm working on a new chart to evaluate this. The image shows counts for a few websites, and how they're distributed.
Does this make sense?
How would you improve it?
#techseo #linkbuilding #SEO #DataVisualization #DataScience #Python #Plotly
#Python Friday #191: Often used Diagrams for #Plotly
https://improveandrepeat.com/2023/09/python-friday-191-often-used-diagrams-for-plotly/
Happy to announce a new cohort for my course:
Data Science with Python for SEO 🎉 🎉 🎉
🔵 For absolute beginners
🔵 Run, automate, and scale many SEO tasks with Python like crawling, analyzing XML sitemaps, text/keyword analysis
🔵 Intro to data manipulation and visualization skills
🔵 Get started with #advertools #pandas and #plotly
🔵 Make the transition from #Excel to #Python
🔵 Online, live, cohort-based, interactive
🔵 Spans three days in one week
#Python Friday #190: Interactive Plots With #Plotly
https://improveandrepeat.com/2023/09/python-friday-190-interactive-plots-with-plotly/
I’ve started experimenting with interactive #DataViz using #Plotly. Here’s a “map” of different foods that I made using plotly in #RStats. The foods are embedded in two dimensions using t-SNE. I also had fun trying out {tricolore} to make the ternary colormap.
The interactive version with food labels (+ calorie and macronutrient information for each food) is on my website: https://www.gmschroeder.com/data_vis/macros-map/
1/2
Happy to announce my course:
Data Science with Python for SEO 🎉 🎉 🎉
🔵 For absolute beginners
🔵 Make a leap in your data skills
🔵 Run, automate, and scale many SEO tasks with Python like crawling, analyzing XML sitemaps, text/keyword analysis
🔵 In depth intro to data manipulation and visualization skills
🔵 Get started with #advertools #pandas and #plotly
🔵 Make the transition from Excel to Python
🔵 Online, live, cohort-based, interactive
Styling tables with #adviz
New function/chart:
🔵 Style columns as text, category, bar, or heatmap
🔵 Set table title, width, height
🔵 Set relative column widths
🔵 Hover to see long text
🔵 HTML file
https://bit.ly/style_table
#DataScience #DataVisualization #Python #Plotly
ShinyProxy now supports Dash.jl apps (for a demo: https://oa.eu/oujHVF) and #Streamlit apps (for a demo: https://oa.eu/LC8GsX).
Also, ShinyProxy’s mobile experience is improved, the support of admin users (next to admin groups) is added as well as passing of time zone information to your #datascience apps.
More information about the release: https://oa.eu/QN2Fbc
📝 "Pills dataset - Part 2"
👤 Jennifer HY Lin (@jhylin)
🔗 https://jhylin.github.io/Data_in_life_blog/posts/09_Pills/Rust_polars_pills_df.html
#pyladies #python #dataanalyticsprojects #pillsdatasetseries #polars #plotly #jupyter
Unveiling a detailed walkthrough on visualizing #SQL queries with Plotly, a versatile #visualization library, using the #Ploomber package in our latest blog post.
Gain insights into the process from ground zero- starting with package installation, #data loading, creating, and loading tables onto a Python-SQL Jupyter Notebook, to the grand finale - visualizing data via various plots.
🔗 Google Colab: https://colab.research.google.com/github/ploomber/sql/blob/main/colabs/visualizing-your-sql-queries/plotting-with-plotly.ipynb
🔗 JupyterBook: https://ploomber-sql.readthedocs.io/en/latest/visualizing-your-sql-queries/plotting-with-plotly.html
First steps at visualizing tables in a clear and (hopefully) beautiful way.
Get/edit the code here:
#DataScience #DataVisualization #Plotly #Barchart #Heatmap #Python
The importance of data storytelling is growing in today's data-driven environment, and we have just the toolset to help you become top-tier data narrators - #SQL, #Seaborn, #Plotly, and #Matplotlib!
Learn more: https://ploomber-sql.readthedocs.io/en/latest/visualizing-your-sql-queries/types-of-visualizations.html
#rstats package #ggpmisc version 0.5.3 is now on CRAN. 'ggpmisc' is now fully compatible with #gganimate and partly compatible with #plotly. A gallery of animated ggplots with code (https://www.r4photobiology.info/galleries/plot-animation.html) is now online. (https://github.com/aphalo/ggpmisc)
The Plotly Dash docs are actually really nice! It's not often you find documentation that goes beyond listing function calls but also explaining the "why" and proactively describing some potential pitfalls along the way. I'm very pleased and can't believe I haven't tried Dash until now!
@chrisremmel excellent point. To be honest, #plotly was what I initially considered, but I was open to other new alternatives. Your comment about being diffieto customise is the type of feedback I was expecting, because it is difficult to see from the documentation
Probably this is one of those questions that could be better done using a poll:
> Hi #python users. Which data visualisation library would you recommend to an #rstats user who loves #ggplot2 customisations (and #plotly for interactive plots)? I'm looking for something very customisable to produce interactive #dataviz.
Hi #python users. Which data visualisation library would you recommend to an #rstats user who loves #ggplot2 customisations (and #plotly for interactive plots)? I'm looking for something very customisable to produce interactive #dataviz. Should I go for #altair #bokeh #plotly #seaborn or none of them?
This Thursday, join us for a workshop on visualizing data with #python, #streamlit, and #plotly. We'll have facilitators from the University of #Wisconsin #DataScience Hub lead us in a participatory workshop, building and customizing a demo app deployed onto the cloud. Bring your laptop!
https://www.meetup.com/madison-python/events/293265891/
Meeting at the #Madison library central branch. (No pizza this time. Sorry!)
First post here on Mastodon!
Wanted to share some updates on my #godotengine addon here too!
Easy Charts is a plotting and data visualization library inspired by some of the major libraries (matplotlib, plotly) and frameworks for @godotengine 3 and 4.
Feel free to use it and contribute.
Neue Werkzeuge: P5, Jupyter und mehr online
Nicht nur ich bewege mich wieder zurück und weg von den reinen statischen Seiten vom Desktop ins Web. Das Neue daran ist, daß die neuen Werkzeuge (meist) ohne dedizierten Server auskommen. Der dynamische Content wird per JavaScript im Client (das ist in der Regel der Browser) erstellt. Ein paar Beispiele, die mir in den letzten Tagen untergekommen sind: https://kantel.github.io/posts/2023050402_p5_jupyter_und_mehr_online/ #P5 #Processing #Plotly #JupyterLite #Docsify #Markdown #Quarto
Announcing our June meetup!
Join us for a workshop led by our colleagues at the UW Data Science Hub. Bring your laptop & dive in on #visualization, #plotly, and #streamlit in #python. We're meeting in the downtown #Madison library. Please join us! (Still working on identifying a sponsor for pizza. Reach out if you or your company are interested in helping us out.)
This is part 5 and the final part in this series. Please enjoy, steal the code and modify for yoruself!
• Choose between entering your own data or selecting from one of several built-in functions
• Select the type of plot you want to see (density, quantile, probability, QQ, or MCMC)
• Choose to use Plotly for interactive visualizations
Post: https://www.spsanderson.com/steveondata/posts/rtip-2023-04-24/
#r #rstats #opensource #shiny #tidydensity #ggplot2 #ggplot #plotly #dt #innovation #technology #distributions
I hope to write more about some details another time but in short, several lines of thought have recently converged on the notion that #Quarto looks like an excellent tool for creating #OER.
https://quarto.org/docs/books/
It hasn't taken me long to start experimenting with this great Tufte-style template. I even added interactive plots with #Plotly in HTML and equivalent static plots in PDF!
After working with #python #plotly #dash for a few days, I'm annoyed.
It makes really cool "hello world" examples. Anything larger is extremely bulky.
It's a state-less web thing, so I need redis/whatever-the-fuck/massive time/net hits just to, like, *store information in variables*.
Except there are no non-toy examples of this. Does anyone outside of medium articles use this thing?
OK, it begins to make sense. These things just return back dictionaries. Probably to hand to the #plotly #javascript engine that actually displays in the browser.
As a bonus, if #dash can do grids of text as well as it seems to do plots, I might be able to ditch a work frenemy. And there's no reason it shouldn't--it's just #flask
Is there a simple explainer for #dash vs #plotly vs plotly express? (I already read the confusing half-truths Google finds)
In particular, why is it easy to find "hello world" graphs from dash, but impossible to find a 3d one other than plotly express?
And what am I getting into dependency-wise if I start using this thing? I don't *want* pandas.
#GameOfLife, again, this time with an 8-glider synthesis of the Gosper glider gun.
Z-axis shows time, from the starting configuration with 8 gliders (bottom) to the first three new gliders running off (top).
Rendering is done in #rstat via rgl, which for some applications seems to be easier to work with than #plotly (which I previously used).
Thanks to @jkanev & @mrdk for suggesting the idea!
__
#CellularAutomata #generative
Ref: https://conwaylife.com/wiki/Gosper_glider_gun
2D #CellularAutomata: #GameOfLife.
The Z-axis shows time, from the starting configuration at the base (an R-pentomino) up to generation t=1200 at the top.
You can see some gliders running off by t=200. By t=1103, near the top, all activity has ceased, and we are left with a few "blinkers" and "still lifes": these appear as vertical lines because they don't move anymore as time passes.
__
#generative #rstats #plotly (and wishing for a 3D update of #ggplot2)
@blub as I trained as an architect and sometimes I teach architects I'm always looking into learning #QGIS, thinking about how to write plug-ins, but failing to put the necessary hours into it :-S
Maybe something that works on #Jupyter like #Plotly will have to do.
I wish I had just a little bit more low level knowledge so I could integrate it in sketches outside Jupyter, like I used to do with unfolding on Processing. It is such a thin line to walk these things I'm wishing... I want control but not too complex and hard low level stuff... I'm sure I have a lot to learn before I can teach any of it.
This week's #TidyTuesday data is from FeederWatch, a citizen science program that asks participants to identify and count the birds that visit the area around their home.
code: https://github.com/deepshamenghani/tidytuesday/tree/master/2023/Week2_birdfeeder
🤖 I finally tried ChatGPT after some hesitation.
Here are my takeaways (so far):
1️⃣ Asking good questions is important.
2️⃣ Learning is still a rewarding journey.
3️⃣ Creativity is not automated; it’s enhanced.
4️⃣ “Output” is not the be all end all.
5️⃣ You can draw a line, or you can be open to adding any tool to the toolbox.
Blog Post & Data Viz ▶ https://lnkd.in/gGD29fZq
#ChatGPT #DataVisualization #DataViz #dataviz #RStats #Plotly #Python #Coding #Learning #AI #ArtificialIntelligence
I wrote a blog on using #ChatGPT to visualize #ransomware leak site data!
🗞️ https://www.th3protocol.com/2022/ChatGPT-LeakSite-Analysis
:python: https://github.com/colincowie/LeakSiteAnalytics
This was fun to work on :blobcatnerd:
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
plotly::ggplotly is FANTASTIC. Who could have believed transforming a plot from a png to an interactive widget could have this simple!
Revamped the whole project within a few hours:
https://github.com/Aman9das/FinalSemStatProject2022/blob/main/Formal/PPT_Reveal.html
@brandewinder this was awesome Matthias. Beautiful demo of the #plotly charting features in #fsharp , numerical differentiation and a fun Xmas themed operations challenge. Now can you get local #sf government to adopt any of these optimization techniques.
@twbrandt Yeah, makes sense. It’s not a huge deal to use d3, and might end up going that route anyway, but mostly just need quick graphs like you’d find in a math text. I’m lazy and don’t want to have to configure axes and stuff. I think I’m gonna poke around with #Plotly. Uses D3 under the hood, but seems to take care of a lot of the boilerplate.
this is surprising, is there no rabbid #plotly or #bokeh fanbase? Are you really gonna let crusty old #matplotlib win? Or is it really, even after all this time, actually good enough?
Interaktive Diagramme fürs Web sind die Spezialität von Plotly. Das Framework dient Python-Programmierern als leistungsfähiges Werkzeug.
Web-Diagramme mit Python und Plotly erzeugen
Buchbesprechung: Python Dash – interaktive Datenanalyse und -visualisierung
Wir zeigen an Beispieldaten, wie man ein Machine-Learning-Projekt in Python umsetzt. So kann etwa ein Programm sehr genau die Unterart einer Pflanze bestimmen.
scikit-learn, numpy und plotly: Einführung in Machine Learning mit Python
Rendez-vous demain à 11h pour un atelier #BlueHats 🧢 pour découvrir les usages du framework #Dash #plotly (https://plotly.com/dash) dans plusieurs administrations.
Nous vous attendrons sur https://visio.incubateur.net/b/bas-vwv-2ww 🙏
Wer in einem achtstündigen Online-Kurs praxisnah alles rund um das Thema Datenvisualisierung lernen möchte, kann für kurze Zeit 50 Prozent sparen. heise-Academy-Kurs: Jetzt Rabatt für "Datenvisualisierung mit Python" sichern!
I just rolled a die a hundred thousand times
How's your Saturday going
🤔🤓😅
Am 12. April lernen Interessierte, wie Datenvisualisierung mit Python funktioniert. Wer gleich die komplette Webinar-Serie bucht, spart ordentlich Geld.
Datenvisualisierung mit Python: Das XXL-Webinar von Heise