This post discusses two interesting post on tile grid maps and how they can be used to visualize data from India.
This post provides a quick summary of economists view of the difference between machine learning and econometrics.
The population of India is projected to reach 1.39 billion by 2026. The important issue facing India is how to sustain this?
The article provides an explanation on methodology to calculate comprehensive concentration index and entropy index using a user defined function in R.
NBER digest highlights the factors contributing to the stagnant wages in USA using HHI measure.
Understanding concentration measures such as Herfindahl-Hirschman Index (HHI) to analyze markets and horizontal mergers.
I visit various websites to collect data. Most of the sites i visit are mostly managed by various Government of India central or state departments / ministries. Given everything is digitized one realizes the extent to which this digitization has brought to light some of the issues related to quality of the websites as well... Continue Reading →
visualizing statewise murder cases in India from 2010 to 2016 using Geo Facet plot in R.
The National Crime Records Bureau (NCRB) in its yearly publication titled Accidental Deaths and Suicides in India reports 11 main causes of death in India from road accidents. The total deaths in India from road accidents is 148707. The top 4 causes of road accidents are dangerous/careless/ overtaking, speeding, other causes and weather. These 4... Continue Reading →
This article shows how business cycles time periods in India can be shaded to enhance the interpretability of economic indicators. This article also serves as an introduction to creating rectangles in R to identify recessionary time frames.
This article tries to explore the possibility of adopting open source technology like R by Government of India. This article is a beginners step to understanding the endless possibilities of combining the open data initiative with open source technology.
The post introduces generating line chart in R. Using the googleVis package allows us to generate interactive plot in R. The data used for generating the plot is based on FDI inflows in the auto industry.
This post shows how one can use RInno package to share a shiny application within an organization without hosting it on a server.
The plot is generated as a part of Makeover Monday. The data comprises of close to 1000 observations. The original story was published here. The plot is inspired from New York Times post on Gender Wage gap in USA. The data for the post is available on MakeoverMonday. The plot was generated using R and inkscape was... Continue Reading →