Strategic petroleum reserves: India

Hello,

Some time back, I had written an article on nature of Strategic Petroleum Reserves.
You can read it here:
STRATEGIC PETROLEUM RESERVES AND ‘UN-FLAT’ NESS OF THE WORLD

Today, I have read another article related to growth of Strategic Petroleum Reserves in India.
Read it here: India responds to growth in oil imports

Currently, a 13 day reserve for India is being planned which is proposed to be increased to 90 days worth. So, which are the countries that are suitably covered by this 13 day storage?

Locations and travelling times for an oil tanker to travel from their port to an Indian Port of Paradip:

Thus, a SPR of 13 days will reduce the Indian dependency on Gulf states but will not cover the oil imports from African and South American countries. Details of port and OPEC annual production data are as under:

An SPR of 90 days will however cover all the oil imports requirements from the 13 places considered. However, we don't have the volumetric import data of India from each of these place which would help in preparing an optimization study.

Thank you.


References:

1. Transit Times and Distance using https://www.searates.com

Comparison of top 10 and bottom 11 Fortune 500 firms

Hello readers,

A text analytics based comparison was done to find unique characteristics of firms belonging in the two clusters:

Cluster 1:
Rank 1: Walmart
Rank 2: Exxon Mobil
Rank 3: Apple
Rank 4: Berkshire Hathaway
Rank 5: McKesson
Rank 6: United Health Group
Rank 7: CVS Health
Rank 8: General Motors
Rank 9: Ford Motor
Rank 10: AT&T

Cluster 2:
Rank 490: Rockwell Collins
Rank 491: Lam Research
Rank 492: Fiserv
Rank 493: Spectra Energy
Rank 494: Navient
Rank 495: Big Lots
Rank 496: Telephone & Data Systems
Rank 497: First American Financial
Rank 498: NVR
Rank 499: Cincinnati Financial
Rank 500: Burlington Stores

Download report:
Detailed report containing observation commentary, correlation plots and word clouds is available for download here: Report

Correlation plot for Ford Motor

R programming language (along with packages "tm", "RGraphviz", "graph" and "slam") was used to prepare this analysis report. Citation for each has been provided below.

Do leave comments below. Thanks.



Citations:

• R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
• Kurt Hornik, David Meyer and Christian Buchta (2016). slam: Sparse Lightweight Arrays and Matrices. R package version 0.1-35. https://CRAN.R-project.org/package=slam
• Kasper Daniel Hansen, Jeff Gentry, Li Long, Robert Gentleman, Seth Falcon, Florian Hahne and Deepayan Sarkar (2016). Rgraphviz: Provides plotting capabilities for R graph objects. R package version 2.16.0.
• R. Gentleman, Elizabeth Whalen, W. Huber and S. Falcon (2016). graph: graph: A package to handle graph data structures. R package version 1.50.0.
• Ingo Feinerer and Kurt Hornik (2015). tm: Text Mining Package. R package version 0.6-2. https://CRAN.R-project.org/package=tm 
• Ingo Feinerer, Kurt Hornik, and David Meyer (2008). Text Mining Infrastructure in R. Journal of Statistical Software 25(5): 1-54. URL: http://www.jstatsoft.org/v25/i05/.
• Latest annual reports were collected from individual websites of each of the 21 companies analyzed in the report.

Chilcot Report : Text analytics (Wordcloud and correlation plots)

Hello readers,

The Chilcot Report has been published.
You can read the report here:
http://www.iraqinquiry.org.uk/the-report/

I have taken a shot at it by merging all the 58 PDF files into a merged PDF document.
I then converted it into text and made a wordcloud.
The wordcloud is as under:

More analysis to follow.
Thanks.

UPDATE:

The correlation plot has been prepared. It can be viewed from the following link:
CHILCOT REPORT ANALYSIS