ggplot
Apache Superset
Our great sponsors
| ggplot | Apache Superset | |
|---|---|---|
| 3 | 3 | |
| 3,682 | 34,745 | |
| 0.2% | - | |
| 0.0 | 9.9 | |
| over 1 year ago | about 3 years ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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.
ggplot
-
Best tools for good looking tables and piecharts
Seaborn is based on matplotlib and quite modern. Coming from R and used to ggplot (which is also available in python) I really like it.
-
Which Python visualization module to use for research-quality graphs?
If you're familiar with R, there's always ggplot.
-
Plotting in R's ggplot2 vs Python's Matplotlib: Is it just me or is ggplot2 WAY smoother of an experience than Matplotlib?
I'd agree in that it's a well-specified language for defining graphics; it's not very good with rendering performance. There are packages which try to achieve similar goals in Python as well (ggplot / ggpy) and packages like Seaborn. Though, like you, I use R for lots of EDA. Hard to beat data.table and R graphics for speed and expressiveness. I prefer base graphics though; ggplot2 tends to render too slowly for any data sets I work with.
Apache Superset
-
Using KeyCloak(OpenID Connect) with Apache SuperSet
The first difference is that after pull request 4565 was merged, you can no longer do:
-
Open Source Analytics Stack: Bringing Control, Flexibility, and Data-Privacy to Your Analytics
Open-source BI platforms such as Metabase (website, GitHub) and Apache SuperSet (website, GitHub) are easy to deploy without IT involvement. Metabase lets you build dashboards from the data in your warehouse easily, with no SQL, or, if you have data engineering or science know-how, inside more powerful and flexible notebooks or with SQL itself. Similarly, Apache SuperSet helps businesses explore and visualize data from simple line charts to detailed geospatial charts.
-
Ask HN: What low-code “dashboarding“ SaaS would you recommend in 2021?
Check out Superset. https://github.com/apache/incubator-superset
It’s modern, easy to extend. From the same author of apache airflow.
What are some alternatives?
seaborn - Statistical data visualization in Python
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
Altair - Declarative statistical visualization library for Python
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
matplotlib - matplotlib: plotting with Python
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
plotnine - A Grammar of Graphics for Python
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
bokeh - Interactive Data Visualization in the browser, from Python
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
Flask JSONDash - :snake: :bar_chart: :chart_with_upwards_trend: Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go.
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications