dataMnp: dataMnp
In sontron/madis: Manipulating and Analyzing Data Interactively with Shiny

a function provides data manipulating procedures, mainly based on data.table.

dataMnp(data, subset = NA, newVars = NA, newVarsFormulas = NA,
  newVarsBy = NA, indexNames, Formulas, dimVars, dimNames = NA,
  dateVar = NA, dtOrders = "ymd", margin = 0, revisedNames = NA,
  revisedFormulas = NA, revisedMargin = 0, orderVars = NA,
  orders = NA, Digits = 2, tbVars = NA, hbVars = NA,
  colOrder = NA)

`data`	data.frame
`subset`	character string could be parsed as a logical expression or NA, eg. subset="sex==1"
`newVars`	new vars names, could be character string or NA, eg. newVars='ageNew'
`newVarsFormulas`	character string could be parsed as formulas or NA, eg. "sum(age)"
`newVarsBy`	groupby var name or NA
`indexNames`	variable names generated in the jth procedre as data.table.
`Formulas`	character string could be parsed as expression, and seperated with ";" eg. "mean(disp);sum(disp)"
`dimVars`	group by variable names, same as k in data.table
`dimNames`	rename the dimVars
`dateVar`	set the dateVar in the data.frame if any
`dtOrders`	set the date variable format, could be 'ymd', 'mdy', 'ymd hms', please refer to lubridate::parse_date_time for more detail.
`margin`	calculate margin results. 0 means no margin results should calculated, 1 for the first 1 dimVars, 2 for the first 2 dimVars, etc.
`revisedNames`	new variable name generated using the results
`revisedFormulas`	formulas corresponding to revisedNames
`revisedMargin`	same as margin but only for revised vars
`orderVars`	please refer to data.table::setorderv for more detail.
`orders`	please refer to data.table::setorderv for more detail.
`Digits`	set digits
`tbVars`	vars needed to calculate tongbi(chinese, means Year over Year) index.
`hbVars`	vars needed to calculate huanbi(chinese, means month over month, quater over quater, etc.)
`colOrder`	reorder column orders.

expand.grid(2017:2018,1:12,1:28)->X
apply(X,1,function(x)paste(x,collapse='-'))->date
dt<-data.frame(ts=date,grp1=sample(letters[1:5],length(date),rep=T),y=rnorm(length(date)))
dataMnp(data=dt,indexNames=c('a','b','c'),Formulas='mean(y);sd(y);sd(y)/mean(y)',dimVars='year(ts);month(ts);grp1',dimNames = 'year;month;grp',dateVar = 'ts',dtOrders = 'ymd',orderVars = 'grp',orders='1',tbVars='a;b',hbVars=c('c','tt'),revisedNames = 'tt',revisedFormulas = 'a+b',colOrder='1;2;3;4;5;6;8;9')->res

# generate new variable 
dataMnp(data=mtcars,subset='vs==1',newVars='test',newVarsFormulas='mpg+disp',indexNames='sumMPG',Formulas='sum(mpg)',dimVars='gear',dimNames='VS')

# revise the result using revisedNames, revisedFormulas,revisedMargin args. it's same as DT[i,j,k][c('revisedvars'):=list(...),by=.(...)]
# the revisedMargin means groupby which dimVars, eg. 1 means the first 1 dimVars, and 2 means the first 2 dimVars, 0 means no groupby variables.

dataMnp(data=mtcars,newVarsFormulas='mpg+disp',indexNames='sumMPG',Formulas='sum(mpg)',dimVars='vs;gear',dimNames='VS;Gear',revisedNames='x',revisedFormulas='sum(sumMPG)',revisedMargin=o)
dataMnp(data=mtcars,newVarsFormulas='mpg+disp',indexNames='sumMPG',Formulas='sum(mpg)',dimVars='vs;gear',dimNames='VS;Gear',revisedNames='x',revisedFormulas='sum(sumMPG)',revisedMargin=1)
dataMnp(data=mtcars,newVarsFormulas='mpg+disp',indexNames='sumMPG',Formulas='sum(mpg)',dimVars='vs;gear',dimNames='VS;Gear',revisedNames='x',revisedFormulas='sum(sumMPG)',revisedMargin=2)