markdown guide

I think that really depends; where is your data coming from?

When I'm playing around with data mining in Python, I'm often using pandas, so it's quite natural to use seaborn. I like how little work I need to put into it to make nice looking graphs. Gallery.

At work I use Excel for graphs. It's not very sexy, and the defaults are plain terrible but it is dead simple for ad hoc graphs. As a bonus, every business analyst knows how to work with it, so it's easy to share "source" files across the company.


Naturally this depends on the task:

Plotting Simple Formulae: Wolfram Alpha

If I just want to see the shape of a simple mathematical expression I will just use Wolfram Alpha. It has great natural language support, doesn't require installation or startup, and accepts Mathematica expressions for more complicated stuff.

Plotting Simple Data: Matlab

Whenever I have a quick series I just generated or data from some sort of simple process I will reach for Matlab. I would rather use an OSS solution like Python for this but Matlab is already on my computer and it is pretty good at making simple visualizations.

Plotting Slices of Structured Data: R

R is my first choice whenever I have a structured dataset or need to do anything fancy. I am particularly fond of ggplot2: it looks great by default, can generate tons of different types of plots, and makes slicing and reorganizing the data extremely easy.

Quick #ShowDev: visualization of my 2017 Fantasy Football Draft using R w/ ggplot2 and R markdown.

Classic DEV Post from Mar 29

Speed of Voice - The Pace of Your Presentation Can Heavily Impact How Well it Lands

Learn how to control the pace of your voice in your presentation to land your message

Mazhar Naqvi profile image
CS PhD student, building fast storage systems that will support future applications with stringent latency and throughput demands.

Sore eyes? now has dark mode.

Go to the "misc" section of your settings and select night theme ❤️