[Must Read] Popular Handpicked best Books for Data science

I started learning data science about a years ago..  This is mostly geared towards people who are in the same position I was in.

A lot of advice around learning data science starts with "first learn python", or "first take a linear algebra course".  This advice is fine, but if I followed it, I never would have learned any data science. Being data scientist requires a solid foundation typically in computer science and applications,  modelling, statistics, analytics and math. 
What sets the data scientist  apart is strong business acumen, coupled with the ability to communicate  findings to both business and IT leaders in a way that can influence  how an organization approaches a business challenge. Good data  scientists will not just address business problems, they will pick the  right problems that have the most value to the organization.

Here is a list of books on doing machine learning / data science in R and Python which I’ve come across in last one year. Since, …

8 Effective plots with Matplotlib and Pandas Dataframe

In the previous post we learned some matplotlib plotting techniques.This is second part of matplotlib where we are going to work with some random dataset.This post will also cover basic different type of plotting you can produce in matplotlib.This type of plotting are mostly used to understand the type of data and produce useful insights.Learning and understanding matplotlib will take some longer learning time and some patience.While we are trying to learn by creating sample random dataset in dataframe and visualizaling different kind of plots.
I have come to appreciate matplotlib because it is extremely powerful. The library allows you to create almost any visualization you could imagine. Additionally, there is a rich ecosystem of python tools built around it and many of the more advanced visualization tools use matplotlib as the base library.

In [25]: %matplotlib inline'ggplot')

The plot method on Serie…