PYTHON CHARTS: the Python data visualization site with more than 500 different charts with reproducible code and color tools

This page summarizes the projects mentioned and recommended in the original post on /r/Python

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  • reticulate

    R Interface to Python

  • 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

  • rmarkdown

    Dynamic Documents for R

  • 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

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • Hugo

    The world’s fastest framework for building websites.

  • 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

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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