rmarkdown
evidence
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rmarkdown | evidence | |
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38 | 44 | |
2,782 | 3,175 | |
0.9% | 11.2% | |
7.6 | 10.0 | |
23 days ago | about 19 hours ago | |
R | JavaScript | |
GNU General Public License v3.0 only | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
rmarkdown
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Pandoc
I'm surprised to see no one has pointed out [RMarkdown + RStudio](https://rmarkdown.rstudio.com) as one way to immediately interface with Pandoc.
I used to write papers and slides in LaTeX (using vim, because who needs render previews), then eventually switched to Pandoc (also vim). I eventually discovered RMarkdown+RStudio. I was looking for a nice way to format a simple table and discovered that rmarkdown had nice extensions of basic markdown (this was many years ago so maybe that is incorporated into vanilla markdown/pandoc).
The RMarkdown page claims:
> R Markdown supports dozens of static and dynamic output formats including HTML, PDF, MS Word, Beamer, HTML5 slides, Tufte-style handouts, books, dashboards, shiny applications, scientific articles, websites, and more.
...which I think is largely due to using pandoc as the core generator.
RStudio shows you the pandoc command it runs to generate your document, which I've used to figure out the pandoc command I want to run when I've switched to using pandoc directly.
This is a bit of a "lazy" way to interact with pandoc. Maybe the "laziest" aspect: when I get a new computer, I can install the entire stack by installing Rstudio, then opening a new rmarkdown document. Rstudio asks whether I'd like to install all the necessary libraries -- click "yes" and that's it. Maybe that sounds silly but it used to be a lot of work to manage your LaTeX install. These days I greatly favor things that save me time, which seems to get more precious every year.
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We’re Washington Post reporters who analyzed Google’s C4 data set to see which websites AI uses to make itself sound smarter. Ask us Anything!
We used R Markdown for cleaning and analysis, creating updateable web pages we could share with everyone involved. Similarweb’s categories were useful, but too niche for us. So we spent a lot of time recategorizing and redefining the groupings. We used the token count for each website — how many words or phrases — to measure it’s importance in the overall training data.
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Generating PDF 📄 with Python 🐍
R Markdown / Quarto https://quarto.org/ https://rmarkdown.rstudio.com/ ; can dynamically generate a document and compile it to HTML, PDF, others
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PYTHON CHARTS: the Python data visualization site with more than 500 different charts with reproducible code and color tools
Hi! At this moment I'm not opening the source code, but I can explain you the tech used. This site is based on another site I created before named https://r-charts.com/ and it was created with blogdown (HUGO + R Markdown). Hence, each tutorials is an R markdown file. For PYTHON CHARTS, in order to run Python within an R markdown file I had to use an R package named reticulate. In addition, the template depends on shuffle.js for filtering and fuse.js for searching
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looking for an "low dependency" or pythonesque way to generate PDF's
What you want is not Python, its R Markdown; https://rmarkdown.rstudio.com/
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LaTex alternative/replacement written in Rust?
not sure what you mean by this exactly but in my experience its far better to use Markdown + pandoc for stuff like this. Actually I use R Markdown which can compile to either HTML or PDF from the same source document, with executable code chunks embedded (to generate the document contents) ; https://rmarkdown.rstudio.com/
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Neovim support for editing Quarto (.qmd) files
Quarto is a relatively new Markdown-based file format. One of its main uses is writing reports that interleave text with code and results; it supports rendering with knitr (an engine widely used in the R community) as well as Jupyter (more popular with Python users). Since I work in data science, I use both languages regularly. For writing R reports, I've switched from R Markdown (Quarto's R-focused predecessor) to Quarto. I'd also like to start writing Python reports in Quarto using Neovim.
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How do you build and send reports to your users?
If you're not already aware of and using RMarkdown, make learning it a priority. I use both R and Python extensively. Although Jupyter Notebooks have utility, RMarkdown is the superior tool for the most flexibility in reporting.
- Ask HN: Markdown/reStructuredText to write a PhD thesis in STEM fields?
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Securing R Markdown Documents
The polished package now supports Rmarkdown documents that use the shiny runtime. This includes flexdashboard!
evidence
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SQLPage – Building a full web application with nothing but SQL queries [video]
If you are a data analyst interested in making web apps, I might point you to my own OSS project, Evidence, which is a Static Site Generator for building reports and data apps with SQL and markdown.
Repo (3K stars): https://github.com/evidence-dev/evidence
Previous discussions on HN:
https://news.ycombinator.com/item?id=28304781 - 91 comments
It’s interesting to me how far you have pushed the SQL language in this framework, such that it truly is “SQL only”.
The challenge as I see it with enabling analysts to build websites is that you need to build abstractions to get from familiar (SQL, yaml) - the language of analytics, to new (HTML, CSS, JS) - the language of the web browser
As one of the maintainers of Evidence (https://evidence.dev), one of the things I’ve often considered is how accessible our syntax is to analysts. Our syntax combines SQL and Markdown, with MDX style components e.g.
The are inherently webdev-ey, and I do think they put off potential users.
On the flip-side, by adhering to web standards, you get extensibility out of the box, and working out what to do is just a Google search away.
Anyway, thanks for the thought provoking piece.
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Blazer: Business Intelligence Made Simple
Dataclips was my first experiences writing SQL.
Writing code was a markedly better DX that building dashboards in Tableau, which is why I'm now working on https://evidence.dev - a SSG for creating data from SQL and markdown
Previous HN discussions:
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Is Tableau Dead?
I'm one of the founders of Evidence (https://evidence.dev) - would be great to hear about your experience. Reaching out now!
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Apache Superset
Full fledged BI tools like Superset and Metabase are amazing for their intended use cases.
But they may be an overkill if your primary use case is to infrequently build semi-interactive reports for non-technical end-users and your use cases are are mostly covered by standard graphs & tables. Esp. so if you are familiar with SQL and have access to the underlying data source. Two nifty utilities I have found to be very useful for latter kind of use cases are SQLPage and Evidence.
They make it very convenient to whip out some SQL and convert that to a neat professional looking web ui that can be forwarded to an end user. In case of Evidence it is a statically generated site, and in case of SQLPage it is a web app that connects to a live database.
SQLPage: https://sql.ophir.dev/
Evidence: https://evidence.dev
We use ECharts in our open source BI tool (Evidence) and it's a great library. Has helped us build a declarative syntax for viz which can be version controlled (https://evidence.dev)
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A love letter to Apache Echarts
We used ECharts to build our charting library at Evidence and it’s been a great experience overall (https://evidence.dev).
We started with D3 and a few other tools, but felt that we get a lot more out of the box with ECharts, like interactivity and an events API. ECharts is also a lot more extensible than people give it credit for.
If anyone is curious, we documented the process of selecting a charting library after assessing several options: https://github.com/evidence-dev/evidence/issues/136
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Observable 2.0, a static site generator for data apps
The new direction seems very similar to what evidence has been doing for a while
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PRQL as a DuckDB Extension
I'm quite excited about this, and would also love to have it distributed as an NPM package.
I work on an OSS web framework for reporting/ decision support applications (https://github.com/evidence-dev/evidence), and we use WASM duckDB as our query engine. Several folks have asked for PRQL support, and this looks like it could be a pretty seamless way to add it.
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Nota is a language for writing documents, like academic papers and blog posts
> Not sure the language you choose matters as much as making the API usable by a wide audience.
Fully agree with this, and having typeset my masters thesis and later my resume using LaTeX, I think that the “authoring experience” is 100% the place to focus on improving.
If you’re interested in the “markup to document publishing” space, you might also be interested in the open-source report publishing tool I’m now working on, Evidence (https://github.com/evidence-dev/evidence)
It’s similarly based on markdown, though uses code fences to execute code, HTML style tags for charts and components, and {…} for JavaScript, i.e.
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What are some alternatives?
Pluto.jl - 🎈 Simple reactive notebooks for Julia
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
metriql - The metrics layer for your data. Join us at https://metriql.com/slack
here_here - I love the here package. Here's why.
tinytex - A lightweight, cross-platform, portable, and easy-to-maintain LaTeX distribution based on TeX Live
superset - Apache Superset is a Data Visualization and Data Exploration Platform
TikZ - Complete collection of my PGF/TikZ figures.
codebraid - Live code in Pandoc Markdown
blogdown - Create Blogs and Websites with R Markdown
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
github-orgmode-tests - This is a test project where you can explore how github interprets Org-mode files
dplyr - dplyr: A grammar of data manipulation