Organization Structure (As At 31: Fill & Download for Free

Yes.There is usually ample work to be done to get disparate data sets aligned and in usable formats. Most commonly, we are dealing with data sets over varying periods and organized in different formats.That said, I once did a text-mining project where pretty much the whole project was just cleaning data. The script was ~150 lines of code, but the actual analysis was only like 10.Here is a very simple example. Let’s use R to pull price data on the S&P 500, the US recession indicator, and the 10-year US Treasury yield so we can understand how these variables interact.library(quantmod) library(ggplot2) getSymbols(c("USREC", "DGS10"), src="FRED") getSymbols("^GSPC", from="1950-01-01", to="2018-12-31") When you inspect the data, you’ll notice that USREC is monthly starting in 1855, while the GSPC data is daily starting in 1950, and DGS10 is daily starting in 1962. We have different time lengths, starting points, and DGS10 has several missing data points. To further complicate matters, GSPC data is structured as open-high-low-close-volume-adjusted close. We need to clean, organize, and structure the data to get it into formats we can use.I’ll give you an example of how I would ‘clean’ DGS10’s data:dgs10 = 0 #Set up a dummy variable to fill in the for loop for(i in 1:length(DGS10)){  if(is.na(DGS10[i]) == TRUE ){ #Check if the value at this point is NA  dgs10[i] = DGS10[i-1] #If it is NA, then fill this value with previous  } else {   dgs10[i] = DGS10[i] #Otherwise keep the value  } } dgs10 = as.xts( dgs10, order.by=index(DGS10) ) #Convert to time series dgs10 = dgs10[ xts:::startof(dgs10, "months") ] #Convert from daily to monthly Not a big deal, but 10 lines of code to remove/replace the NA values. Imagine having data from numerous sources which all need to be cleaned and formatted.Eventually, after cleaning and organizing, I get to this:If you are interested in R topics, come join us in ouR Space and the blog, Rticles.R Code to generate the plot above is below. Note that of the 30 lines, only 5 are used to visualize the final product, the other 25 lines are simply getting, cleaning and organizing! This is a pretty typical ratio for me.library(quantmod) library(ggplot2) getSymbols(c("USREC", "DGS10"), src="FRED") getSymbols("^GSPC", from="1950-01-01", to="2018-12-31") start.date = as.Date("1963-01-01") end.date = as.Date("2018-12-31") spx = GSPC[ xts:::startof( GSPC, "months") ] spx = Delt( spx$GSPC.Adjusted, k=1 ) spx = window( spx, start=start.date, end=end.date ) dgs10 = 0 for(i in 1:length(DGS10)){  if(is.na(DGS10[i]) == TRUE ){  dgs10[i] = DGS10[i-1]  } else {  dgs10[i] = DGS10[i]  } } dgs10 = as.xts( dgs10, order.by=index(DGS10) ) dgs10 = dgs10[ xts:::startof(dgs10, "months") ] dgs10 = window( diff( dgs10, 1), start=start.date, end=end.date ) recs = window( USREC, start=start.date, end=end.date ) data = data.frame( spx, dgs10, recs ) colnames(data) = c("SPX", "d10y", "Recession") data$Recession = as.factor(data$Recession) ggplot( data, aes(x=d10y, y=SPX, color=Recession ) )+  geom_jitter( )+  geom_hline(yintercept=0,   linetype="dotted", color="seagreen", size=1.0)+  geom_vline(xintercept=0,   linetype="dotted", color="seagreen", size=1.0)+  scale_color_manual(values=c("dodgerblue4", "firebrick4"))+  xlab("MoM Change in 10-year Yield")+  ylab("MoM Change in S&P 500")+  geom_smooth() 

Introduction to Data StructuresData Structure is a way of collecting and organising data in such a way that we can perform operations on these data in an effective way. Data Structures is about rendering data elements in terms of some relationship, for better organization and storage. For example, we have data player's name "Virat" and age 26. Here "Virat" is of String data type and 26 is of integer data type.We can organize this data as a record like Player record. Now we can collect and store player's records in a file or database as a data structure. For example: "Dhoni" 30, "Gambhir" 31, "Sehwag" 33In simple language, Data Structures are structures programmed to store ordered data, so that various operations can be performed on it easily.Basic types of Data StructuresAs we discussed above, anything that can store data can be called as a data strucure, hence Integer, Float, Boolean, Char etc, all are data structures. They are known as Primitive Data Structures.Then we also have some complex Data Structures, which are used to store large and connected data. Some example of Abstract Data Structure are :Linked ListTreeGraphStack, Queue etc.All these data structures allow us to perform different operations on data. We select these data structures based on which type of operation is required. We will look into these data structures in more details in our later lessons.

The East India Trading Company(EITC), was a joint-stock company and mega-corporation formed for pursuing and monopolizing trade with the East Indies and the Caribbean. The Company was granted a Royal Charter by Queen Elizabeth I on December 31, 1600. Shares of the Company were owned by wealthy merchants and aristocrats. The government owned no shares and had only indirect control. The Company eventually came to rule large areas of India with its own private armies, exercising military power and assuming administrative functions.The company was led by one governor and 24 directors, who made up the Court of Directors. They, in turn, reported to the Court of Proprietors (or body of shareholders) which appointed them. Ten committees reported to the Court of Directors. Court of Directors was headed by a chairman and deputy chairman who, aided by permanent officials, were responsible for the daily conduct of Company business.First Governor : Thomas SmytheOther governors : Josiah Child, i couldn't find a list of other governors.List of East India Company directors, charimans and deputy charimans.(Note : London governors should not be confused with List of governors-general of India.)Company structure :(src : The East India Company - Organization Structure, Control and Governance)You can read this book "The Trading World of Asia and the English East India Company, 1660-1760",It contains many details of the company structure and policies and how they carried out trade. It is a wonderful resource to read. Also read about rothschild family and other powerful merchants that were driving force behind the finance of military operations in different parts of world.Other resources :The East India CompanyIndia Office Records: History and scopeThe East India CompanyAlso, a peek into it's current ownership :East India Co is back, with Indian owner - The Times of Indiae-commerce site of East India Company : Luxury Gift Hampers & Christmas Gift Ideas | The East India Companyhttp://gulfnews.com/business/investment/lulu-group-makes-85m-investment-in-east-india-company-1.1396574