mattjcamp

Step One: Copy Everything

• Copy SQLite.exe into the directory
• Copy database into the directory
• Copy source data file into the directory

NOTE Can also just reference paths if preferred

Step Two: Open Database

mattjcamp

get.timing.data <- function(task, run_order){
  
  start.time <- Sys.time()
  time <- system.time({CODE TO EXECUTE HERE})
  df <- data.frame(list(Task = task,
                        Run_Order = run_order,
                        Elapsed = time[3]))
  
  return(df)
  

mattjcamp

f$Sector <- sapply(f$Sector,
                   FUN = data.vacuum.adapt,
                   category = "Sector")

mattjcamp

# s$SCORE is a vector

freq <- cbind(
    Freq = table(s$SCORE),
    Cumm_Freq = cumsum(table(s$SCORE)),
    Perc = round(prop.table(table(s$SCORE)) * 100, 4),
    Cumm_Perc = round(cumsum(prop.table(table(s$SCORE))) * 100, 4)
)

freq <- as.data.frame(freq)

mattjcamp

  d3.csv("aggregated_total.csv", function(d) {

  var table = d3.select('#CSV_Table')
                .append('table')
                .attr("class", "center");

  var trh = table.append('tr');

  trh.append('td')
      .text("Year")

mattjcamp

# Returns the standard deviation for a
# population (using N and not N-1 as
# denominator)

sdp <- function(x){
  
  # I adapted this from an answer I found
  # on Stack Overflow
  
  # Reference

mattjcamp

# Reference 
https://developer.apple.com/library/mac/documentation/Darwin/Reference/Manpages/man1/xsltproc.1.html">Apple document on xsltproc

# submit the line below to the Mac terminal

xsltproc index.xsl index.xml > output.txt

mattjcamp

if(!grepl("^[A-Z]{2}$", location))
  stop(sprintf("***%s*** is not a valid value for input parameter location. 
               Choose the two letter state abbreviation", location))
               
# Replace
# Replaces anything with _#### with %i in a data frame

temp$TABLE_NAME <- sub("_[1,2][0-9][0-9][0-9]", "_%i", temp$TABLE_NAME)

# Look at records that fit a pattern

mattjcamp

/*Make Table Wide, Rows to Columns*/

SELECT Cohort, State,
    MAX(CASE WHEN GENDER = 'F' THEN N ELSE NULL END) AS N_F,
    MAX(CASE WHEN GENDER = 'M' THEN N ELSE NULL END) AS N_M,
    MAX(CASE WHEN GENDER = 'F' THEN SAT_Verbal ELSE NULL END) AS SAT_Verbal_F,
    MAX(CASE WHEN GENDER = 'M' THEN SAT_Verbal ELSE NULL END) AS SAT_Verbal_M,
    MAX(CASE WHEN GENDER = 'F' THEN SAT_Math ELSE NULL END) AS F_SAT_Math_F,
    MAX(CASE WHEN GENDER = 'M' THEN SAT_Math ELSE NULL END) AS M_SAT_Math_M,
    MAX(CASE WHEN GENDER = 'F' THEN SAT_Writing ELSE NULL END) AS SAT_Writing_F,

mattjcamp

'Macro to help mine data from an Excel workbook
'This reads through each worksheet in a workbook and outputs each value into
'a destination sheet.  For each row it reads until it reaches a blank cell (across columns).
'For each sheet, it reads until it reaches a blank cell (down rows)

Sub MineDataFromWorkbook()
    
    Dim wb As Workbook
    'Replace NAME with workbook name (must be open in Excel)
    Set wb = Application.Workbooks("NAME")