plotnine VS plotly

To your last point, have you tried plotnine? It's meant to be ggplot2 for python.

https://github.com/has2k1/plotnine

plotnine - A grammar of graphics for Python based on ggplot2.

Github: https://github.com/has2k1/plotnine

This seems quite similar to plotnine [0], which also provides a grammar of graphics interface for Python. That said, I love ggplot and I can't wait to use this in my research! I hope we can port/re-implement ggthemes, scientificplots [1], and other ggplot libraries for lets-plot.

0: https://plotnine.readthedocs.io/en/stable/

1: https://github.com/garrettj403/SciencePlots

There is [plotnine](https://plotnine.readthedocs.io/en/stable/) which tries to implement ggplot in Python.

You could use plotnine if you like the grammar of graphics concept: https://plotnine.readthedocs.io/en/stable/

> Python doesn’t yet have anything remotely close to ggplot for rapidly making exploratory graphics, for example.

Plug for plotnine (https://plotnine.readthedocs.io/en/stable/). I don't know R but use ggplot indirectly through this library for exploratory data analysis, and comparing the experience to any other python plotting library, I understand why R folks are usually so sad to be using Python.

They have, https://plotnine.readthedocs.io/en/stable/

Plotly brings D3.js-level interactivity to Python:

Plotly Python Documentation

# import plotly import plotly.express as px # create your chart type, for more chart types: https://plotly.com/python/ fig = px.bar(df, x = letter, y = frequency) # make chart prettier fig.update_layout( plot_bgcolor="White", height=700 ) # display chart fig.show()

Right off the bat, there’s a massive spike around early 2024–03 that stands out — yet, it’s hard to pinpoint which specific article triggered this rush just by looking at this static chart. To dig deeper and see if a particular article caused this jump, I decided to try something more interactive with Plotly for a clearer view.

plotly

Github: https://github.com/plotly/plotly.py

First we need to install the Plotly. To create some very dynamic graphics, this tool helps a lot.

my good dude wake up and smell the plotly. Knowing the ins and outs of matplotlib is helpful but doing interactive stuff with jupyter I always use plotly.