Which charting library to use?

Here are three links you should go through this week.

  1. What I learned re­cre­at­ing one chart us­ing 24 tools is an ex­cel­lent com­par­is­on by Lisa of 12 visu­al­isa­tion ap­plic­a­tions and 12 lib­rar­ies, with a good sum­mary of which tool to use when.
  2. Can we pre­dict flu deaths with ML and R? Read this R note­book for a step-by-step walk-through of pre­dict­ing wheth­er a pa­tient will sur­vive or not. (There’s also a part 2 that im­proves on this mod­el.)
  3. One of our col­leagues nearly lost a piece of ana­lys­is re­cently. Here’s the most bor­ing / valu­able ad­vice she can get on how to or­gan­ise ana­lys­is — or any form of work for that mat­ter. Of course, you could al­ways learn git.

    If that doesn’t fix it, git.txt con­tains the phone num­ber of a friend of mine who un­der­stands git. Just wait through a few minutes of ‘It’s really pretty sim­ple, just think of branches as…’ and even­tu­ally you’ll learn the com­mands that will fix everything.

Introduction to Exploratory Data Analysis – A video lesson

It’s al­ways not ne­ces­sary to use ma­chine learn­ing al­gorithm for ex­tract­ing in­ter­est­ing stor­ies from data. Here is a video by Kathirmani Sukumar, Data Scientist at Gramener, which ex­plains data ana­lys­is sans com­plic­ated ma­chine learn­ing tech­niques. The video les­son will help in learn­ing how to ana­lyse data us­ing a few sim­ple (but power­ful) tech­niques based on Exploratory Data Analysis (EDA) us­ing data from the sport of Cricket. It is use­ful for those who want to do data ana­lys­is, but are not sure of where to start and what to learn from. It also dis­cusses about ba­sics of data types, data muta­tion and uni­vari­ate ana­lys­is, and these tech­niques are do­main ag­nostic. One can ap­ply the same tech­niques on any data from any do­main. It fo­cuses on us­ing Pandas lib­rary for data pro­cessing and plot­ting the res­ults. The Jupyter note­book can be down­loaded from http://bit.ly/2hCJrqY. The next video in the series will be a les­son on uni­vari­ate and bivari­ate ana­lys­is.